WHITE PAPER:
The Impact of Values on
Performance at Work
Clark Amistad – Talent Assessment
Developer, and
Wyn Davies – Global Product Strategist
January 20, 2020
Introduction
For decades, work psychologists and other researchers
have tried to answer the question of what makes a
person successful at work. They examined factors
like a person’s personality and their cognitive ability,
finding that both are strong predictors of performance.
However, that same research also showed that a large
part of a person’s performance is explained by other
factors, leading to research into other predictors of
performance. One of the most promising areas of
research surrounds a person’s values. This paper delves
into the research on values, explaining what values are,
examples of values at play, and how a strong fit between
a person’s own values and the values required for a role,
team, and organisation are paramount for being
motivated and performing successfully at work.
In practice, it is common for the terms “personality” and
“values” to be used interchangeably, causing individuals
to confuse the two with one another. However, there are
key distinctions between these two factors. Personality
traits are relatively stable dispositions that distinguish
one individual from another. While personality profiles
are unique, most personality assessments measure a
core set of personality traits that all people have some
level of, allowing a person’s personality profile to be
compared against others. Personality traits tell us how
we tend to do something (e.g. a tendency to focus on
the big-picture vs. the details) and our preferred ways of
behaving. Values, on the other hand, are why we tend to
do something (e.g. to enjoy striving to master a difficult
problem). They are the things that interest us, give
enjoyment, and motivate us.
Measuring traits and values cannot predict with absolute
certainty how capable a person is to carry out a job.
However, they are still widely used in recruitment,
individual and team development, and career
counseling contexts to offer a strong indication of
certain characteristics:
•
How likely a candidate’s behaviours and traits fit
those required in a job
•
How well a person’s values align with or it
those of a profession, a manager, a team and an
organisation
How a candidate’s personality traits align with the
behaviours on the job offers insight into their likely
suitability for the job. By comparison, how a candidate’s
values align with the values of the business is closely
linked to employee engagement. Both of these, in turn,
impact job performance. Measuring the importance
0345 099 1485 | TalentLens.co.uk
Copyright © 2019 Pearson Education, Inc. or its affiliate(s). All rights reserved.
that a candidate or employee places on different values
can offer real insight into how likely they are to be
motivated and engaged at work, their preferred ways of
engaging with others, and how they can best develop.
Predicting Job Performance
There are four key factors that affect job performance:
1. Job-relevant skills, learned knowledge, and
experience
2. The ability to think and reason (cognitive ability)
3. Behavioural/personality fit to those behaviours and
soft skills required in a job
4. The levels of motivation, (which are closely linked to
how personal values and interests are fulfilled in the
job)
Many recruiters focus heavily on assessing skills and
qualifications, thereby missing insight into other key
areas. A 2016 meta-analysis1 analysed hundreds of
research studies and found that cognitive ability tests
on average predicted job performance better than any
other assessment method (with a correlation coefficient
of .65). This meta-analysis also showed that combining
cognitive ability tests with personality measures such
as conscientiousness increased predictive validity.
However, even when combining both assessments,
measuring cognitive ability and conscientiousness
together only explains a part of what impacts an
employee’s job performance.
Motivation
Motivation is rarely measured by recruiters, but it is a
factor that impacts quite heavily on performance. An
employee can have all the right skills, behaviours and
abilities but their job satisfaction and performance are
likely to suffer if they are demotivated. Motivation is
strongly influenced by values, interests, and strengths.
Values
Compared to the rich history of personality, motivation,
and interest research, interest in values is relatively
recent. However, companies have realised the benefits of
incorporating “values-based hiring” into the recruitment
process.2 While assessing values by themselves is not
enough to predict who will succeed in a role, measuring
them can certainly help formulate interview questions and
hypotheses that can be explored in both selection and
development situations. The following sections define the
concepts of values and provide examples of the benefits
of measuring them.
Values defined
The social psychologist Shalom Schwartz proposed the
most accepted definition of values as “prioritised, transsituational, and guiding beliefs that persons hold about
desired end states or behaviors”.3 This definition holds
several implications:
1. Prioritised: Employees prioritise certain values over
others. This means that given a certain decision,
people will look to whichever value is more important
than another to determine which action to take. The
more important a certain value is to a person, the
greater the impact it is likely to have on their decisions
and behaviour.
2. Trans-situational: Values go beyond any single
situation. That is, values apply to all areas of our lives,
from our lifestyle at home, to the kind of friends we
spend time with, and to how we act at work. In a work
context, a person’s values are consistent even when
they move to a different team or company.
3. Guiding: Last and most importantly, values act as
a guide for decision making. That is, values provide
“the why” for people’s actions. Values can influence
why someone decides to go the extra mile, as people
whose values strongly match the values of the
organisation see themselves as part of something
bigger than themselves. Conversely, having values that
are misaligned with the company can influence people
to take actions that can harm a company. If an
employee doesn’t feel the company values match their
own, they may be more likely to disagree with
company decisions, purposefully go against managers’
requests, or act passively, deciding instead to only put
half their effort toward their work.
The importance of measuring values
Values are distinct in that no one value is more predictive
of performance than another. Of greater importance
is how much a person’s own values fit that of their
profession, manager, team, and organization. The more
an employee’s values align, the more likely the
0345 099 1485 | TalentLens.co.uk
Copyright © 2019 Pearson Education, Inc. or its affiliate(s). All rights reserved.
employee is to stay and thrive in the role and the
organisation.
Value fit increases employee engagement
The empirical literature shows that high value fit is
strongly related to employee engagement. The next
sections demonstrate that, across multitudes of studies,
and using different engagement metrics, how an
employee’s own values fit with the work they are doing
and the team and organisation they are in influences how
engaged they are at work.
Job satisfaction
In a study of nurses working in surgical wards at a regional
hospital, researchers found that value congruence (the
extent to which an employee’s values matched the
values they experienced at work) was linked with job
satisfaction.4 Importantly, this occurred because greater
value congruence affected the attitude nurses had toward
their ward. Nurses with higher value congruence had
more pride working on their ward, were happier with
their choice of ward, and were more likely to agree to the
statement: “No matter what kind of work I have to do, I
want to stay on this ward”.
Organizational commitment
This level of engagement also extends to an employee’s
commitment to their company. Researchers have
generally separated commitment into three levels of
positivity5:
1. Continuance commitment: “I have to stay because I
have no better options”
2. Normative commitment: “I have to stay because my
organisation needs me”
3. Affective commitment: “I want to stay because I’m
emotionally invested”
Affective commitment is the most positive form of
commitment; it has the strongest relationship with
outcomes such as productivity and intentions to stay
with a company. Conversely, continuance commitment
is the least positive as it is more closely tied to an
employee’s willingness to leave a company. Researchers
from the University of Tennessee at Chattanooga were
interested in the impact that value fit has on these
different types of commitment.6 They found that value fit
was strongly positively related to affective commitment.
Conversely, value fit had no relationship with continuance
commitment. This meant that employees who feel their
values align with their company are more willing to
emotionally attach themselves to the company they work
for.
Values fit reduces turnover
According to the Society of Human Resources
Management, the average cost of a new hire in 2017
was $44007, and this amount generally increases as the job
level rises, the role becomes more complex, and the job
market becomes tighter. This means that turnover can be
incredibly costly; going through the selection process again
means additional costs. Turnover also has downstream
effects on team members such as lost productivity and lost
revenue. Importantly, strong evidence shows a negative
relationship between value fit and turnover intentions.
That is, when employees feel like their values fit with their
company, they are less likely to leave the organisation.
Value fit is often expressed in terms of an employee’s
perceptions about their company’s culture. Using data
from 4717 participants, researchers at Columbia University
found that only 13.9% of subjects were likely to quit when
they were highly satisfied with their company’s culture
whereas 48.4% of subjects were likely to quit when they
reported low satisfaction with their company’s culture.8
Employees want to work for companies whose
values fit their own
People are willing to put their money where their mouth is
when it comes to their values. In late 2017, the insurer
MetLife announced the results of their “Role of the
Company Survey”. In it, they found that nine out of ten
employees said they were willing to trade some of their
salary to work at a company whose values match their
own.9 On average, employees were willing to take a 21%
pay cut to work for a company whose values aligned with
their own, and these numbers were relatively consistent
(+/- 2%) regardless of whether participants were earning
less than $50,000 or more than $100,000.
Measuring values for manager and team fit
It is often said that an individual leaves a manager, not
a company. While there are many reasons for leaving,
a poor working relationship between an individual and
their boss or co-workers is still cited as one of the main
reasons why people leave. A 2015 Gallup survey found that
about 50% of the 7,200 adults surveyed left a job “to get
away from their manager.” 10
In addition to clashes between individuals, a poor
understanding or acceptance of the different interpersonal
values of individual team members can often lead to poor
communication and disharmony.
What type of fit is most important?
The most comprehensive research in this field was done by
University of Iowa professor Amy Kristof-Brown and her
colleagues in 2005.11 They assessed the results of 172
studies to examine the effect of different types of fit on
work outcomes. They were interested in answering the
question of “which fit was most important?” Fit with the
0345 099 1485 | TalentLens.co.uk
Copyright © 2019 Pearson Education, Inc. or its affiliate(s). All rights reserved.
job? The manager? The team? Or the organisation? What
they found was that the importance of fit depended on
the outcome measured (see Table 1).
For performance, the most important type of fit was fit
with the job. This was closely followed with fit with the
manager and fit with the team. However, when it came
to indicators of employee engagement, fit with the
organisation became very important. Organisational fit
was found to be quite positively related to job satisfaction
and organisational commitment and negatively related to
intentions to quit.
Validity Results Performance
Job
Satisfaction
Organizational
Commitment
Turnover
Intentions
Organizational
Fit
.11
.35
.42
-.29
Team Fit
.15
.24
.15
-.17
Supervisor Fit
.15
.35
.07
.08
Job Fit
.16
.44
.39
-.37
Table 1. Correlation coefficients for different forms of fit and work outcomes
Note: Due to the large sample sizes (N = 943 – 42922), all values are
significant.
Values and Performance
A good example of the importance of value fit can be
found in research on mergers and acquisitions. Often,
one key component of successful M&As is the similarity in
values between companies. Even if both companies were
successful before the merger, opposing values can cause
major repercussions. Researchers from the University of
Kansas School of Business were interested in confirming
this hypothesis. To do so, they studied 173 acquisitions
in the U.S. Manufacturing industry (Datta, 1991)12 and
looked at the effect of organizational fit between
companies. Specifically, they were interested in whether
certain indicators of value fit (i.e. similarity in management
styles, rewards, and evaluation systems) influenced
subsequent firm performance. They hypothesized
though that this would only be true when companies
needed to integrate operations after the acquisition.
As expected, they found higher firm performance with
greater organizational fit. Interestingly, they found the
importance of organisational fit was true even in cases of
low post-acquisition integration. So even when companies
continue to work relatively separately, similar values
between companies ensured they were able to improve
performance.
The case study for values: Bridgewater Associates
“Weigh values and abilities more heavily than skills
in deciding whom to hire…what’s most important is
determining whether you and they are working toward
the same goals and can work in the same ways and share
the same values.”
– Ray Dalio, Founder, Bridgewater Associates
With nearly $160 Billion in assets under management,
Bridgewater Associates is one of the largest hedge
funds in the world.13 Bridgewater clients have included
some of the most sophisticated public and corporate
pension funds, university endowments, and central banks,
despite its humble beginnings as an investment fund
being run out of their founder’s apartment. According to
Bridgewater’s founder, Ray Dalio, the key to their success
is the unwavering dedication to finding people that fit the
company’s values. Dalio developed a set of core values
that he believes all employees should follow. He compiled
these into an employee handbook and, in 2017, published
them in the book “Principles”.
In his book, Dalio extols the importance of hiring for the
right value fit. As he states: “Weigh values and abilities
more heavily than skills in deciding whom to hire. Avoid
the temptation to think narrowly about filling a job with
a specific skill. While having that skill might be important,
what’s most important is determining whether you and
they are working toward the same goals and can work in
the same ways and share the same values.” 14
How are values assessed? Presenting SOSIE
SOSIE is an online questionnaire designed to measure
eight personality traits and twelve values in one
instrument. SOSIE was first published in 1991 and is
based on three existing questionnaires developed
by Leonard V. Gordon, an eminent North American
psychologist. The three tests are the Gordon Personality
Profile-Inventory (GPP-I), the Survey of Interpersonal
Values (SIV) and Survey of Personal Values (SPV). The 2nd
generation of the SOSIE was launched in 2011.
SOSIE measures both the how (traits) and the why (values)
of behaviour. The eight traits in SOSIE correlate with
the Costa and McCrae’s Big Five factors of personality,
described in Table 2. Further information on the eight
competencies and what they measure can be found in the
SOSIE technical manual.
Big Factor Five
Low Scores
Openness to
Likely to prefer
routine tasks and
stick to what they
know
Experience
Conscientiousness
Extraversion
Agreeableness
Neuroticism
High Scores
The tendency to be
curious, creative,
innovative, and open
to new ideas
Likely to procrastinate, be bored by
routine tasks, and to
be impulsive
The tendency to be
reliable, organised,
and doggedly
pursuing goals
Likely to be quiet,
in-trospective,
reserved, and
thoughtful
Less likely to trust
others and be liked
by others. They can
be antagonistic and
task-focused
The tendency to be
talkative and enjoy the
company of others
Rarely worries, happygo-lucky and secure
Likely to be well-liked
by and trusting of
others and to want to
please or help others
The predisposition to
worry, feel insecure
and self-conscious
Table 2. Low and high score descriptors of the Big Five factors
Numerous instruments have been developed to
assess values, but these have been less widely used in
organisational contexts than measures of personality.
Also, unlike personality where the Big Five is most
relevant, there is no single widely agreed-upon framework
for the structure of values.
Despite this, when the values assessed by different
instruments are reviewed, these measures tend to
share much in common. For example, values such as
Independence, Achievement, Influence, and Recognition
appear in many assessments. One of the most
researched framework for values is the Schwartz’s Value
Taxonomy. This taxonomy identifies ten value areas and
has been widely tested in different cultures.15 Many of
Schwartz’s values map to those found in SOSIE including
Independence, Support, Achievement, Variety, Structure,
Influence, Recognition and Conformity.
SOSIE values and examples of low and high fit
Many researchers have tried to place sets of values into
different categories. For example, one way to think about
these concepts is by grouping them into intrinsic and
extrinsic values. Intrinsic values are intangible rewards
that keep you motivated and engaged in your job. They
have a strong impact on the type of job or profession that
people enter. Extrinsic values are the tangible rewards or
conditions found at work. Often the rewards related to
these values are contingent or external to the receiver.
SOSIE measures several intrinsic and extrinsic values, but
separates them into interpersonal and personal values.
Interpersonal values are those values that are important
in communicating with others.
0345 099 1485 | TalentLens.co.uk
Copyright © 2019 Pearson Education, Inc. or its affiliate(s). All rights reserved.
Measuring Interpersonal values offers insight into
areas where there may be a clash of values between
an individual and team members or a manager.
Interpersonal values are both intrinsic (e.g. independence
and benevolence) and extrinsic (e.g. power and
recognition).
Personal values are those that relate to a person’s own
internal desires and needs, irrespective of others. These
values often only affect ourselves or do not require others
to fulfill. Intrinsic personal values include achievement and
variety while one example of an extrinsic personal value is
materialism.
The following sections show the different interpersonal
and personal values that questions in the SOSIE measure:
SOSIE Interpersonal Values
1. Support: Support focuses on the importance given
to friendliness, help, support, and understanding in
the workplace. People with high scores appreciate
being treated with kindness and understanding.
People with low scores don’t actively seek support or
encouragement from others. They care little about
others’ opinions, and they accept conflict if it arises.
2. Conformity: Conformity deals with the importance
given to rules and social norms. People with high
scores have great respect for social conventions,
rules, and doing what is socially accepted and
proper. People with low scores give little credence to
conventions and to following social rules.
3. Recognition: Recognition focuses on the
importance given to social recognition such as praise,
consideration, or status. People with high scores
enjoy the respect and admiration others express
towards them. People with low scores are unmoved
by social recognition, status, or special treatment.
4. Independence: Independence focuses on the
importance placed on one’s autonomy regarding
actions or decisions. People with high scores on
independence care strongly about their freedom to
make their own decisions and do things their own
way. People with low scores are grateful for advice
and guidelines, and they work well under tight task
constraints.
5. Benevolence: Benevolence deals with the
importance given to generosity and helping others.
People with high scores are attentive to the needs
of others and value helping them. People with low
scores don’t prioritize others’ needs, difficulties, or
requests for help.
6. Power: Power focuses on the importance given to
workplace influence and the desire to lead others.
People with high scores enjoy positions or situations
0345 099 1485 | TalentLens.co.uk
Copyright © 2019 Pearson Education, Inc. or its affiliate(s). All rights reserved.
that enable them to influence, direct or control
others. People with low scores on power rarely seek
to influence or control others.
SOSIE Personal Values
SOSIE measures six personal values that are the essential
signposts that influence choices and direct actions.
1. Materialism: Materialism focuses on the importance
given to profits, material goods, or immediate results.
People with high scores are attracted to material
goods, profit, and short term, tangible or practical
results. People with low scores are generally
uninterested in short-term financial returns or
material goods.
2. Achievement: Achievement focuses on the
importance given to reaching personal goals and
achieving success. People with high scores on
achievement are unafraid of challenges, difficulties, or
the effort needed to achieve them. People with low
scores generally care little about going beyond their
possibilities.
3. Variety: Variety focuses on the importance given
to change, variety, and novelty. People with high
scores enjoy being challenged by new experiences or
different situations and dislike daily, repetitive tasks.
People with low scores are more likely to be motivated
by routine tasks that they are familiar with and that
occur in a predictable context.
4. Conviction: Conviction focuses on the importance
placed on personal commitment to decisions. People
with high scores have a strong attachment to their
beliefs and the possibility of putting them into
practice. People with low scores attach little
importance to personal commitments.
5. Orderliness: Orderliness concerns the importance
given to structured organisations, procedures, and
methods. People with high scores enjoy structured
work environments and systematic approaches. They
prefer that planned tasks occur within an organisation
run in a methodical and orderly way. People with low
scores grant little importance to organisation,
methods, or procedures, preferring instead to seek
out more flexible environments.
6. Goal Orientation: Goal orientation addresses the
importance of having clear, precise, and relatively
stable objectives. People with high scores prefer to
have everything laid out for them, working through
clearly defined and precise objectives. People with low
scores do not require clear or precise objectives to
act. They are likely to enjoy doing several things at
once and seeing their objectives change does not
hinder them.
SOSIE Values and the Big Five
Other examples include the following:
Whilst the eight traits measured in SOSIE correlate highly
with the Big Five, Pearson TalentLens’s R&D team carried
out global research to better understand how values
relate to the Big Five personality factors. The research
yielded several interesting findings about the relationship
between values and personality. For example, across
all the countries where the research study was carried
out, high levels of support correlate with high levels of
agreeableness, whilst power shows a negative correlation
with agreeableness. Variety showed a negative correlation
with conscientiousness, whilst the correlation of
conscientiousness with orderliness was strongly positive.
Conformity and Goal Orientation were both negatively
correlated with openness to experience. The complete
results of this study can be found in the SOSIE technical
manual.
•
A manager who does not value receiving support
from others may view staff who do value this as
“needy” whilst the staff may perceive the manager as
unsupportive and unfriendly.
•
A manager who values benevolence highly may find
that they become focused on the needs of their team
members and lose sight of the task at hand.
•
The team member who values receiving support from
others but shows little support or concern for others
(high support, low benevolence) may come across as
self-centered to others with different values.
•
A subordinate who values Goal Orientation highly
working for a manager who sets no clear goals or
guidelines is likely to become frustrated.
•
An individual who values achievement and
materialism highly may become demotivated if
they are unable to achieve their goals or their
achievements do not lead to material gain in the short
term.
Do Values Differ Between Generations?
A recent research study was carried out by psychologists
at Pearson TalentLens to measure differences in SOSIE
scores between Generations X and Y. The findings were
that there were small but significant differences. The full
results can be found in the whitepaper: Personality and
Values: The Generation Game.
Examples of insights that can be gained from SOSIE
values.
The effect of values on behaviour may not always be as
easy to identify. This is because the links between values
and behaviour are often more complex. For example, two
people in the workplace may both be keen to volunteer
for any new opportunities that come along, but their
reasons for this could be quite different. Whereas one
person may value the variety new opportunities bring, the
other may see it as a way of getting ahead which might
be aligned to values such as power or achievement. A
third person may also volunteer for these opportunities,
even though they hold none of these values. In this case,
they might volunteer just because they think it is what is
expected of them, rather than that behaviour reflecting
one of their values.
Consider for example the following scenario: Jan leads
a team of ten people. In her team, three people value
power very highly while three others care little about
power. There is only room for one official leader (Jan),
so conflict is likely to occur especially as some team
members look for opportunities to lead. However, by
understanding the value preferences of the team there
may be opportunities for those who enjoy power to lead
small sub-teams or projects. Those who do not value
power are likely to be happy being led by others.
0345 099 1485 | TalentLens.co.uk
Copyright © 2019 Pearson Education, Inc. or its affiliate(s). All rights reserved.
The above are hypotheses relating to only one or two
values. However, behaviour is multifaceted and
determined by more than an employee’s fit to any
particular value. By measuring a combination of
important traits and values in SOSIE employers can
observe a detailed and unique profile of their candidates
and employees.
Conclusion
The importance of measuring values for hiring employees
and developing top talent cannot be overstated.
Measuring values can help employers select the best
candidates by truly understanding how well the candidate
can fit the job, manager, team, and organisation they want
to be a part of. They can also help employers develop
their existing talent by understanding what best motivates
their employees. SOSIE measures both personality and
values, and in doing so, SOSIE is a smart, easy way for
employers to incorporate values into their performance
management system.
Learn how you can use
TalentLens’ range of Cognitive
Ability and Personality
Assessments at
www.TalentLens.co.uk
References
1. Schmidt, F. L. (2016). The Validity and Utility of Selection Methods in Personnel Psychology:
Practical and Theoretical implications of 100 Years. Retrieved from www.researchgate.net/
publication/309203898
2. Gulati, A. (2016). Is values-based hiring right for your business? Society for Human Resource
Management. Retrieved from https://www.shrm.org/resourcesandtools/hr-topics/talentacquisition/pages/values-based-hiring-culture-fit.aspx
3. Schwartz, S. H. (1992). Universals in the content and structure of values: Theory and empirical
tests in 20 countries. In M. Zanna (Ed.), Advances in Experimental Social Psychology (Vol. 25, pp.
1-65). New York: Academic Press. http://dx.doi.org/10.1016/S0065-2601(08)60281-6
4. Verplanken, B. (2004). Value congruence and job satisfaction among nurses: A human relations
perspective. International Journal of Nursing Studies, 41, 599-605. https://doi.org/10.1016/j.
ijnurstu.2003.12.011
5. Allen, N. J., & Meyer, J. P. (1990). The measurement and antecedents of affective, continuance
and normative commitment to the organization. Journal of Occupational Psychology, 63(1),
1–18. doi:10.1111/j.2044-8325.1990.tb00506.x
6. Amos, E. A., & Weathington, B. L. (2008). An analysis of the relation between employee
organization value congruence and employee attitudes. The Journal of psychology, 142(6),
615–31. doi:10.3200/JRLP.142.6.615-632
7. Society for Human Resource Management. (2017). 2017 Talent Acquisition Benchmarking
Report. Retrieved from https://www.shrm.org/hr-today/trends-and-forecasting/research-andsurveys/Documents/2017-Talent-Acquisition-Benchmarking.pdf
8. Medina, E. (2012). Job satisfaction and employee turnover intention: What does
organizational culture have to do with it? Retrieved from https://static1.1.sqspcdn.com/
static/f/1528810/23319899/1376576545493/Medina+Elizabeth.pdf
9. Metlife. (2017). Metlife role of the company survey. Retrieved from https://www.metlife.com/
content/dam/metlifecom/us/homepage/corporate-responsibility/pdf/reports-and-research/
role-of-the-company-key-findings.pdf
10. Weber, L. (2015). What do workers want from the boss? The Wall Street Journal. Retrieved from
https://blogs.wsj.com/atwork/2015/04/02/what-do-workers-want-from-the-boss/?mod=e2tw
11. Kristoff-Brown, A. L., Zimmerman, R. D., & Johnson, E. C. (2005). Consequences of individuals’
fit at work: A meta-analysis of person-job, person-organization, person-group, and personsupervisor fit. Personnel Psychology, 58, 281-342.
12. Datta, D. K. (1991). Organizational fit and acquisition performance: Effects of post-acquisition
integration. Strategic Management Journal, 12, 282 -297.
13. Bridgewater. (n.d.). What we do. Retrieved from https://www.bridgewater.com/
14. Dalio, R. (2017). Principles. New York, NY: Simon & Schuster
15. Schwartz, S. H., & Boehnke, K. (2004). Evaluating the structure of human values with
confirmatory factor analysis. Journal of Research in Personality, 38, 230-255. https://doi.
org/10.1016/S0092-6566(03)00069-2
0345 099 1485 | TalentLens.co.uk
Copyright © 2019 Pearson Education, Inc. or its affiliate(s). All rights reserved.
Psychological Bulletin
2005, Vol. 131, No. 6, 803– 855
Copyright 2005 by the American Psychological Association
0033-2909/05/$12.00 DOI: 10.1037/0033-2909.131.6.803
The Benefits of Frequent Positive Affect:
Does Happiness Lead to Success?
Sonja Lyubomirsky
Laura King
University of California, Riverside
University of Missouri—Columbia
Ed Diener
University of Illinois at Urbana–Champaign and The Gallup Organization
Numerous studies show that happy individuals are successful across multiple life domains, including
marriage, friendship, income, work performance, and health. The authors suggest a conceptual model to
account for these findings, arguing that the happiness–success link exists not only because success makes
people happy, but also because positive affect engenders success. Three classes of evidence— crosssectional, longitudinal, and experimental—are documented to test their model. Relevant studies are
described and their effect sizes combined meta-analytically. The results reveal that happiness is associated with and precedes numerous successful outcomes, as well as behaviors paralleling success.
Furthermore, the evidence suggests that positive affect—the hallmark of well-being—may be the cause
of many of the desirable characteristics, resources, and successes correlated with happiness. Limitations,
empirical issues, and important future research questions are discussed.
Keywords: happiness, subjective well-being, positive affect, positive emotions, meta-analysis
(1999) reviewed the correlations between happiness and a variety
of resources, desirable characteristics, and favorable life circumstances. Although the authors recognized that the causality can be
bidirectional, they frequently used wording implying that cause
flows from the resource to happiness. For example, they suggested
that marriage might have “greater benefits for men than for
women” (p. 290), apparently overlooking the possibility that sex
differences in marital patterns could be due to differential selection
into marriage based on well-being. Similarly, after reviewing links
between money and well-being, Diener and his colleagues pointed
out that “even when extremely wealthy individuals are examined,
the effects [italics added] of income are small” (p. 287), again
assuming a causal direction from income to happiness. We use
quotes from one of us to avoid pointing fingers at others, but such
examples could be garnered from the majority of scientific publications in this area. The quotes underscore the pervasiveness of the
assumption among well-being investigators that successful outcomes foster happiness. The purpose of our review is not to
disconfirm that resources and success lead to well-being—a notion
that is likely valid to some degree. Our aim is to show that the
alternative causal pathway—that happy people are likely to acquire favorable life circumstances—is at least partly responsible
for the associations found in the literature.
“A merry heart goes all the day, Your sad tires in a mile-a.”
—William Shakespeare
“The joyfulness of a man prolongeth his days.”
—Sirach 30:22
“The days that make us happy make us wise.”
—John Masefield
Research on well-being consistently reveals that the characteristics and resources valued by society correlate with happiness. For
example, marriage (Mastekaasa, 1994), a comfortable income
(Diener & Biswas-Diener, 2002), superior mental health
(Koivumaa-Honkanen et al., 2004), and a long life (Danner, Snowdon, & Friesen, 2001) all covary with reports of high happiness
levels. Such associations between desirable life outcomes and
happiness have led most investigators to assume that success
makes people happy. This assumption can be found throughout the
literature in this area. For example, Diener, Suh, Lucas, and Smith
Sonja Lyubomirsky, Department of Psychology, University of California, Riverside; Laura King, Department of Psychological Sciences, University of Missouri—Columbia; Ed Diener, Department of Psychology,
University of Illinois at Urbana–Champaign and The Gallup Organization,
Omaha, Nebraska.
This work was supported in part by grants from the Positive Psychology
Network. We are grateful to Fazilet Kasri, Rene Dickerhoof, Colleen
Howell, Angela Zamora, Stephen Schueller, Irene Chung, Kathleen Jamir,
Tony Angelo, and Christie Scollon for conducting library research and
especially to Ryan Howell for statistical consulting.
Correspondence concerning this article should be addressed to Sonja
Lyubomirsky, Department of Psychology, University of California, Riverside, CA 92521. E-mail: sonja@citrus.ucr.edu
A PRELIMINARY CONCEPTUAL MODEL
In this article, we review evidence suggesting that happy people—those who experience a preponderance of positive emotions—tend to be successful and accomplished across multiple life
domains. Why is happiness linked to successful outcomes? We
propose that this is not merely because success leads to happiness,
but because positive affect (PA) engenders success. Positively
803
LYUBOMIRSKY, KING, AND DIENER
804
valenced moods and emotions lead people to think, feel, and act in
ways that promote both resource building and involvement with
approach goals (Elliot & Thrash, 2002; Lyubomirsky, 2001). An
individual experiencing a positive mood or emotion is encountering circumstances that he or she interprets as desirable. Positive
emotions signify that life is going well, the person’s goals are
being met, and resources are adequate (e.g., Cantor et al., 1991;
Carver & Scheier, 1998; Clore, Wyer, Dienes, Gasper, & Isbell,
2001). In these circumstances, as Fredrickson (1998, 2001) has so
lucidly described, people are ideally situated to “broaden and
build.” In other words, because all is going well, individuals can
expand their resources and friendships; they can take the opportunity to build their repertoire of skills for future use; or they can
rest and relax to rebuild their energy after expending high levels of
effort. Fredrickson’s model (Fredrickson, 2001) suggests that a
critical adaptive purpose of positive emotions is to help prepare the
organism for future challenges. Following Fredrickson, we suggest
that people experiencing positive emotions take advantage of their
time in this state—free from immediate danger and unmarked by
recent loss—to seek new goals that they have not yet attained (see
Carver, 2003, for a related review).
The characteristics related to positive affect include confidence,
optimism, and self-efficacy; likability and positive construals of
others; sociability, activity, and energy; prosocial behavior; immunity and physical well-being; effective coping with challenge and
stress; and originality and flexibility. What these attributes share is
that they all encourage active involvement with goal pursuits and
with the environment. When all is going well, a person is not well
served by withdrawing into a self-protective stance in which the
primary aim is to protect his or her existing resources and to avoid
harm—a process marking the experience of negative emotions.
Positive emotions produce the tendency to approach rather than to
avoid and to prepare the individual to seek out and undertake new
goals. Thus, we propose that the success of happy people rests on
two main factors. First, because happy people experience frequent
positive moods, they have a greater likelihood of working actively
toward new goals while experiencing those moods. Second, happy
people are in possession of past skills and resources, which they
have built over time during previous pleasant moods.
This unifying framework builds on several earlier bodies of
work—the broaden-and-build model of positive emotions
(Fredrickson, 1998, 2001), the notion that positive emotions convey specific information to the person (Ortony, Clore, & Collins,
1988), the idea of positivity offset (Ito & Cacioppo, 1999), work
on the approach-related aspects of PA (Watson, 2000), and, finally, Isen’s (e.g., 2000) groundbreaking research on the behaviors
that follow positive mood inductions. We extend the earlier work
in predicting that chronically happy people are in general more
successful, and that their success is in large part a consequence of
their happiness and frequent experience of PA. Although the vast
majority of research on emotions has been on negative states, a
body of literature has now accumulated that highlights the importance of positive emotions in people’s long-term flourishing.
Classes of Evidence
Figure 1 displays our general conceptual model, which proposes
that successful outcomes are caused by happiness and do not
merely correlate with it or follow from it. Specifically, below the
conceptual model, we display four classes of evidence that can be
used to test it. The first type of evidence (Type A) represents
positive correlations derived from cross-sectional studies. Although it is a truism that correlation does not imply causation,
correlations must generally be positive to be consistent with propositions about causality. Except in the rare case in which strong
third-variable suppressor effects exist across studies, an absence of
correlation between two variables indicates an absence of causality
in either direction. Thus, correlational evidence is germane to our
argument because the absence of positive correlations suggests
that happiness does not cause success.
The second class of evidence (Type B) is based on longitudinal
research, and is somewhat more informative about causal direction
than cross-sectional correlations. If one variable precedes another
in time and other potential causal variables are statistically controlled, the resulting causal model can be used to reject a causal
hypothesis. In cases in which changes in variable X are shown to
precede changes in variable Y, this form of evidence is even more
strongly supportive of a causal connection, although the influence
of third variables might still contaminate the conclusions and leave
the direction of cause in doubt. Evidence of Type C, the classic
laboratory experiment, is commonly believed to represent the
strongest evidence for causality, although even in this case it can
be difficult to determine exactly what aspect of the experimental
manipulation led to changes in the dependent variable. Finally,
long-term experimental intervention studies (Type D evidence)
would offer the strongest test of our causal model, although again
the active ingredients in the causal chain are usually not known
with certainty.
Empirical Tests of Model and Organizational Strategy
Because no single study or type of evidence is definitive, an
argument for causality can best be made when various classes of
evidence all converge on the same conclusion. Therefore, we
document several types of evidence in our article in order to most
rigorously test the idea that happiness leads to success. Our review
covers the first three classes of evidence (Types A, B, and C) and
is organized around five focal questions arising from these three
categories:
1.
Cross-sectional studies (Type A)
Question 1: Are happy people successful people?
Question 2: Are long-term happiness and short-term
PA associated with behaviors paralleling success—
that is, with adaptive characteristics and skills?
2.
Longitudinal studies (Type B)
Question 3: Does happiness precede success?
Question 4: Do happiness and positive affect precede
behaviors paralleling success?
3.
Experimental studies (Type C)
Question 5: Does positive affect lead to behaviors
paralleling success?
First, we document the extensive cross-sectional correlational
evidence (Type A), as shown in Figure 1. The first question
addressed by this evidence is the one that forms the basis of our
causal hypothesis—that is, are happy people more likely to suc-
BENEFITS OF FREQUENT POSITIVE AFFECT
805
Figure 1. Empirically testing the conceptual model. PA ⫽ positive affect; Grp. ⫽ group.
ceed at culturally valued goals (e.g., concerning work, love, and
health) than their less happy peers? However, the large number of
available correlational studies in this category also includes relevant research examining behavior and cognition that parallel successful life outcomes—that is, the characteristics, resources, and
skills that help people succeed (e.g., attributes such as selfefficacy, creativity, sociability, altruism, immunity, and coping).
Accordingly, the second question addressed by this evidence explores the relations of behavior paralleling success to long-term
happiness and short-term PA. Because we define happiness as the
LYUBOMIRSKY, KING, AND DIENER
806
frequent experience of positive emotions over time (see below),
our model assumes that the correlations involving long-term happiness are parallel to those of short-term positive moods. In conclusion, only if the correlations generated by Questions 1 and 2 are
generally positive will we consider our causal hypothesis further.
Second, we consider longitudinal studies, which address two
further questions. Is happiness at Time 1 associated with successful outcomes at Time 2 (Question 3)? Is happiness and PA at Time
1 correlated with behaviors paralleling success at Time 2 (Question 4)? In summary, prior levels of happiness and positive affect
must correlate with later levels of successful outcomes and behavior for our causal hypothesis not to be rejected.
In laboratory experimentation, the third type of evidence, causality is put to a stronger test. In this case, however, because of the
limits of the laboratory, only short-term changes in behavior and
cognitions that parallel successful life outcomes are assessed.
Thus, the fifth and final question we address is whether PA causes
the cognitive and behavioral characteristics paralleling success.
Again, because positive affect is defined here as the basic constituent of happiness, our model requires that the outcomes of shortterm positive moods are parallel to the successful outcomes in our
conceptual model. Furthermore, this question is critical, as it
speaks to whether PA may be a mediator underlying the relationship between happiness and flourishing—that is, whether PA
causes the adaptive characteristics that help happy people succeed.
Although the fourth type of evidence shown in Figure 1 (Type
D) would provide the strongest type of data for our model, unfortunately, to our knowledge no studies of this type exist. Nevertheless, support for our conceptual model from all three of the
previously described types of evidence, while not definitive, will
suggest a likelihood that our causal model is correct. Furthermore,
combining the three types of evidence represents an advance
beyond laboratory experimentation alone, because the relatively
greater rigor and control provided by experimentation are supplemented by the relatively greater ecological validity provided by the
other types of studies. Thus, the first two classes of evidence
(Types A and B) speak to the plausibility of generalizing the causal
laboratory findings to the context of success and thriving in everyday life. Meanwhile, by revealing the processes uncovered in
the laboratory, the experimental evidence (Type C) illuminates the
possible causal sequence suspected in the correlational data. Taken
together, consistent findings from all three types of data offer a
stronger test than any single type of data taken alone.
After describing our methodology and defining our terms, we
address each of the five focal questions in order, documenting the
three classes (A, B, and C) of relevant empirical evidence. Then,
we turn to a discussion of several intriguing issues and questions
arising out of this review, caveats and limitations, and important
further research questions.
Methodological Approach
To identify the widest range of published papers and dissertations, we used several search strategies (Cooper, 1998). First, we
searched the PsycINFO online database, using a variety of key
words (e.g., happiness, satisfaction, affect, emotion, and mood).
Next, using the ancestry method, the reference list of every empirical, theoretical, and review paper and chapter was further
combed for additional relevant articles. To obtain any papers that
might have been overlooked by our search criteria, as well as to
locate work that is unpublished or in press, we contacted two large
electronic listserves, many of whose members conduct research in
the area of well-being and emotion—the Society of Personality
and Social Psychology listserv and the Quality of Life Studies
listserv. Twenty-four additional relevant articles were identified
with this method.
The final body of literature was composed of 225 papers, of
which 11 are unpublished or dissertations. From these 225 papers,
we examined 293 samples, comprising over 275,000 participants,
and computed 313 independent effect sizes. A study was included
in our tables if it satisfied the following criteria. First, measures of
happiness, PA, or a closely related construct had to be included, in
addition to assessment of at least one outcome, characteristic,
resource, skill, or behavior. Second, the data had to include either
a zero-order correlation coefficient or information that could be
converted to an r effect size (e.g., t tests, F tests, means and
standard deviations, and chi-squares). If a study did not report an
r effect size, we computed one from descriptive statistics, t statistics, F ratios, and tables of counts (see Rosenthal, 1991). If no
relevant convertible statistics were presented, other than a p value,
we calculated the t statistic from the p value and an
r-sub(equivalent) (Rosenthal & Rubin, 2003). When a paper reported p ⬍ .05, p ⬍ .01, or ns, we computed rsub(equivalent) with
p values of .0245, .005, and .50 (one-tailed), respectively, which
likely yielded a highly conservative estimate of the effect size.
Finally, the sample size had to be available. When possible, we
also contacted authors for further information.
Descriptions of the critical elements of each study (i.e., authors,
year, sample size, happiness/PA measure or induction, related
construct, and effect size [r]) are included in Tables 1, 2, and 3,
which present cross-sectional, longitudinal, and experimental
work, respectively. Table 2 additionally presents the length of time
between assessments, and Table 3 includes the comparison groups
used in the studies. Studies with subscripts after their name are
those that appear in more than a single section or table, usually
because multiple outcome variables are included.
Furthermore, mirroring our documentation of the literature presented in this paper, Tables 1–3 are subdivided into substantive
categories (or panels). For example, Table 1 is subdivided into
nine categories—work life, social relationships, health, perceptions of self and others, sociability and activity, likability and
cooperation, prosocial behavior, physical well-being and coping,
and, finally, problem solving and creativity. The mean and median
effect size (r), weighted and unweighted by sample size, as well as
a test of heterogeneity, is provided for each category for the three
classes of data (cross-sectional, longitudinal, and experimental) in
Table 4.
Tables 1, 2, and 3 report all effect sizes of interest to readers—
including instances of two or more effect sizes generated from the
same sample or dataset. For example, the relation of happiness
with income and marital status derived from a single study may
appear in two different panels of a table (i.e., work life and social
relationships). Alternatively, the correlation between happiness
and coping derived from a single longitudinal study may appear in
two different tables (e.g., the cross-sectional table and the longitudinal table). However, in order to meta-analytically combine the
464 effect sizes listed in Tables 1–3, we had to ensure a degree of
(text continues on page 816)
BENEFITS OF FREQUENT POSITIVE AFFECT
807
Table 1
Study Information and Effect Sizes for Nine Categories of Cross-Sectional Research
Study
n
Happiness/PA measure
Effect size
(r)
Correlated construct
Work life
Credé et al., 2005
Credé et al., 2005
Credé et al., 2005
Cropanzano & Wright, 1999a
(first assessment)
Cropanzano & Wright, 1999a
(second assessment)
DeLuga & Mason, 2000
Donovan, 2000
Donovan, 2000
Donovan, 2000
Donovan, 2000
Donovan, 2000
Foster et al., 2004
Foster et al., 2004
Frisch et al., 2004
George, 1989
George, 1995
George, 1995
Graham et al., in pressa (1995 assessment)
Graham et al., in pressa (2000 assessment)
Howell et al., in press
Jundt & Hinsz, 2001
Krueger et al., 2001a
Lucas et al., 2004
Magen & Aharoni, 1991a
Magen & Aharoni, 1991a
Miles et al., 2002
959
959
959
60
PANAS
PANAS
PANAS
Index of Psychological Well-Being
Organizational citizenship behavior
Counterproductive work behavior
Job withdrawal
Supervisory evaluations
60
Index of Psychological Well-Being
Supervisory evaluations
Job performance
Organizational citizenship behavior
Turnover intentions
Work withdrawal
Organizational retaliatory behavior
Satisfaction with work
Organizational climate for performance
Employee health and well-being
Academic retention absenteeism
111
111
24
52
47
Affectometer 2
Current Mood Report
Current Mood Report
Current Mood Report
Current Mood Report
Current Mood Report
Job Affect Scale
Job Affect Scale
Quality of Life Inventory
Job Affect Scale
PANAS (leader)
PANAS (aggregated group)
One-item happiness
One-item happiness
SWLS
Seven-point semantic differentials
MPQ positive emotionality
One-item happiness
Four-item positive affect
Four-item positive affect
Job-Related Affective Well-Being
Scale
Attributional Style Questionnaire
Three-measure composite of positive
affectivity
Experience and expression of
positive emotion on the job
Experience and expression of
positive emotion on the job
Experience and expression of
positive emotion on the job
One-item happiness
One-item happiness (12 times over
4 days)
PANAS
PANAS
Fordyce HM Scale
PANAS
Index of Psychological Well-Being
37
45
92
188
188
188
188
188
41
41
3,638
254
53
53
4,524
5,134
307
164
397
24,000
260
260
203
Judged customer service
Judged customer service
Income
Income
Material wealth
Task performance
Self-reported altruism
Income
Transpersonal commitment
Involvement in community service
Organizational citizenship behavior
Quarterly insurance commissions
Judged managerial performance
.18
.20
Job autonomy, meaning, and variety
.22
Gross annual salary
.12
Supervisory evaluations (creativity)
.30
Time spent volunteering
Cricket batting average
.09
.36
Interpersonal conflict
Intention to quit
Job satisfaction
Emotional exhaustion
Job performance
⫺.12
⫺.33
.29
⫺.39
.32
Index of Psychological Well-Being
Index of Psychological Well-Being
Supervisory evaluations
Supervisory evaluations
.34
.33
62
Index of Psychological Well-Being
Supervisory evaluations
.25
64
Index of Psychological Well-Being
Supervisory evaluations
.43
94
83
Staw et al., 1994a
272
Staw et al., 1994a
272
Staw et al., 1994a
272
Van Katwyk et al., 2000a (Study 3)
Van Katwyk et al., 2000a (Study 3)
Weiss et al., 1999a
Wright & Cropanzano, 1998
Wright & Cropanzano, 2000
(Study 1)
Wright & Cropanzano, 2000 (Study 2)
Wright & Staw, 1999a (Study 1,
second assessment)
Wright & Staw, 1999a (Study 2,
first assessment)
Wright & Staw, 1999a (Study 2,
second assessment)
.34
.22
.20
⫺.38
⫺.20
⫺.22
.50
.32
.29
.18
⫺.28
.41
.35
.20b
.16b
.23
.19
.44
.20
.21
.36
.23
Seligman & Schulman, 1986a (Study 1)
Staw & Barsade, 1993a
Thoits & Hewitt, 2001a
Totterdell, 2000*
.37
⫺.25
⫺.25
.29
3,617
17
Social relationships
Baldassare et al., 1984
Baldassare et al., 1984
Baldassare et al., 1984
Berry & Willingham, 1997
Cooper et al., 1992a (Study 1 & Study 2)
Cooper et al., 1992a (Study 2)
202
202
202
127
118
118
Four-item happiness
Four-item happiness
Four-item happiness
PANAS
SWLS
SWLS
Instrumental support
Emotional support
Companionship
Commitment to current relationship
Satisfaction with friends
Satisfaction with social activities
.17
.15
.30
.27
.31
.37
(table continues)
LYUBOMIRSKY, KING, AND DIENER
808
Table 1 (continued )
Study
n
Happiness/PA measure
Correlated construct
Effect size
(r)
Social relationships (continued)
Diener & Seligman, 2002a
Diener et al., 2000
Gladow & Ray, 1986a
Gladow & Ray, 1986a
Glenn & Weaver, 1981a (Black female
sample)
Glenn & Weaver, 1981a (Black male
sample)
Glenn & Weaver, 1981a (White female
sample)
Glenn & Weaver, 1981a (White male
sample)
Graham et al., in pressa (1995 assessment)
Graham et al., in pressa (2000 assessment)
Headey et al., 1991a (1981 assessment)
Headey et al., 1991a (1983 assessment)
Headey et al., 1991a (1985 assessment)
Headey et al., 1991a (1987 assessment)
Kozma & Stones, 1983
Lee & Ishii-Kuntz, 1987 (male sample)
Lee & Ishii-Kuntz, 1987 (male sample)
Lee & Ishii-Kuntz, 1987 (female sample)
Lee & Ishii-Kuntz, 1987 (female sample)
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Mastekaasa, 1994
Mishra, 1992a
Mroczek & Spiro, 2005a
Pfeiffer & Wong, 1989a
Phillips, 1967* (healthy sample)
Requena, 1995 (Spanish sample)
Requena, 1995 (U.S. sample)
Ruvolo, 1998a (husbands sample)
Ruvolo, 1998a (husbands sample)
Ruvolo, 1998a (wives sample)
Ruvolo, 1998a (wives sample)
Stack & Eshleman, 1998 (male sample)
Stack & Eshleman, 1998 (female sample)
Staw et al., 1994a
106
SWLS, affect balance, memory
recall
One-item life satisfaction
One-item happiness
One-item happiness
One-item happiness
Relationshipswithclosefriends
.48
Marital status
Support from friends
Support from neighbors
Marital happiness
.07b
.35
.31
.18
167
One-item happiness
Marital happiness
.22
820
One-item happiness
Marital happiness
.53
1,872
One-item happiness
Marital happiness
.37
4,524
5,134
649
649
649
649
600
1,321
1,321
1,551
1,551
621
621
25,810
One-item happiness
One-item happiness
Life-as-a-Whole Index
Life-as-a-Whole Index
Life-as-a-Whole Index
Life-as-a-Whole Index
MUNSH
Seven-item morale
Seven-item morale
Seven-item morale
Seven-item morale
SHS
SHS
Bradburn’s Scales, one-item life
satisfaction, one-item happiness
Index of Life Satisfaction
Marital status
Marital status
Satisfaction with marriage
Satisfaction with marriage
Satisfaction with marriage
Satisfaction with marriage
Marital status
No. of close friends
Loneliness
No. of close friends
Loneliness
Satisfaction with friends
Satisfaction with recreation
Marital status
59,169
63
63
89
720
1,927
59
430
1,084
1,534
317
317
317
317
9,237
10,127
272
Strayer, 1980a
14
Life Satisfaction Inventory
MUNSH
One-item happiness
One-item happiness
One-item happiness
One-item happiness
One-item happiness
One-item happiness
One-item happiness
One-item happiness
One-item happiness
Experience and expression of
positive emotion on the job
Observational count of happy affect
Willi, 1997
383
Relationship-relevant happiness
Achat et al., 2000a
Bogner et al., 2001
Chang & Farrehi, 2001
Chang & Farrehi, 2001
Collins et al., 1992
Diener & Seligman, 2002a
659
168
402
402
73
106
Diener & Seligman, 2002a
106
Diener & Seligman, 2002a
106
Gil et al., 2004a
Gil et al., 2004a
Gil et al., 2004a
Gil et al., 2004a
Gil et al., 2004a
Gil et al., 2004a
41
41
41
41
41
41
LOT
SWLS
LOT-Revised
SWLS
MAACL-Revised
SWLS, affect balance, memory
recall
SWLS, affect balance, memory
recall
SWLS, affect balance, memory
recall
Daily Mood Scale
Daily Mood Scale
Daily Mood Scale
Daily Mood Scale
Daily Mood Scale
Daily Mood Scale
Social interactions with nonfamily
members
Marital status
Jealousy in specific relationship
Social participation
No. of friends
No. of friends
Marital well-being
Spouse’s marital well-being
Marital well-being
Spouse’s marital well-being
Marital status
Marital status
Emotional and tangible support from
supervisors
Observational count of empathic
responses to others
Extent in love with partner
.03b
.02b
.47
.55
.49
.47
.20
.23
⫺.50
.19
⫺.51
.50
.51
.29
.41
.23
⫺.03
.17
.13
.08
.12
.16
.41
.34
.15b
.16b
.33
.59
.19
Health
Vitality
History of substance abuse
Depressive symptoms
Depressive symptoms
Quality of life
Depression
.14b
⫺.27
⫺.36
⫺.57
.32
⫺.61
Hypochondriasis
⫺.24
Schizophrenia
⫺.53
Pain
ER visits
Hospital visits
Doctor calls
Medication use
Work absences
⫺.42
⫺.06b
⫺.06b
⫺.08b
⫺.08b
⫺.09b
BENEFITS OF FREQUENT POSITIVE AFFECT
809
Table 1 (continued )
Study
n
Happiness/PA measure
Correlated construct
Effect size
(r)
Health (continued)
Graham et al., in pressa (1995 assessment)
Graham et al., in pressa (2000 assessment)
Kashdan & Roberts, 2004a
Kehn, 1995a
Laidlaw et al., 1996
Lobel et al., 2000
Lu & Shih, 1997
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Mroczek & Spiro, 2005a (1978-1980
sample)
Mroczek & Spiro, 2005a (1981-1983
sample)
Mroczek & Spiro, 2005a (1984-1986
sample)
Mroczek & Spiro, 2005a (1987-1989
sample)
Mroczek & Spiro, 2005a (1990-1992
sample)
Mroczek & Spiro, 2005a (1993-1995
sample)
Mroczek & Spiro, 2005a (1996-1998
sample)
Mroczek & Spiro, 2005a (1999-2000
sample)
Phillips, 1967a
Røysamb et al., 2003a
Røysamb et al., 2003a
Windle, 2000a
⫺.03b
⫺.05b
⫺.34
.43
⫺.33
⫺.20
⫺.36
.43
⫺.29
⫺.49
.23
4,524
5,134
104
98
38
129
191
621
621
621
1,254
One-item happiness
One-item happiness
PANAS
Life Satisfaction Index
One-item peacefulness
LOT
Chinese Happiness Inventory
SHS
SHS
SHS
Life Satisfaction Inventory
Health problems
Health problems
Social phobia/anxiety
Global health
Size of allergic reaction
Delivery of low-birth-weight infants
Poor mental health
Satisfaction with health
Physical symptoms
Depressed affect
Global health
1,267
Life Satisfaction Inventory
Global health
.31
1,283
Life Satisfaction Inventory
Global health
.31
1,641
Life Satisfaction Inventory
Global health
.24
965
Life Satisfaction Inventory
Global health
.26
974
Life Satisfaction Inventory
Global health
.29
919
Life Satisfaction Inventory
Global health
.29
389
Life Satisfaction Inventory
Global health
.34
One-item happiness
SWB Index
SWB Index
Revised Dimension of Temperament
Survey
Overall mental health
Global health
Musculoskeletal pain
Delinquent activity
.22
.50
⫺.25
⫺.22
PANAS
SWLS
PANAS
SWLS
PANAS
Inventory of Personal Happiness
One-item happiness
One-item happiness
One-item happiness
Quality of conversation
Satisfaction with relatives
Satisfaction with relatives
Satisfaction with friends
Satisfaction with friends
Hostility toward other women
Support received from friends
Support received from relatives
Satisfaction with friendships
.27
.22
.12
.31
.23
⫺.21
.35
.14
.22
167
One-item happiness
Satisfaction with friendships
.23
820
One-item happiness
Satisfaction with friendships
.29
89
One-item happiness
Satisfaction with friendships
.13
1,872
One-item happiness
Satisfaction with family life
.25
167
One-item happiness
Satisfaction with family life
.15
820
One-item happiness
Satisfaction with family life
.39
89
One-item happiness
Satisfaction with family life
.17
110
Neutral Objects Satisfaction
Questionnaire
Neutral Objects Satisfaction
Questionnaire
SWLS
SWLS
Judged favorability of reference letter
(hypothetical)
Judged favorability of reference letter
(actual)
Self-esteem
Optimism
.29
593
6,576
6,576
1,016
Positive perceptions of self and others
Berry & Hansen, 1996a (Study 1)
Cooper et al., 1992a (Study 1 & Study 2)
Cooper et al., 1992a (Study 1 & Study 2)
Cooper et al., 1992a (Study 1 & Study 2)
Cooper et al., 1992a (Study 1 & Study 2)
Cowan et al, 1998
Gladow & Ray, 1986a
Gladow & Ray, 1986a
Glenn & Weaver, 1981a (White male
sample)
Glenn & Weaver, 1981a (Black male
sample)
Glenn & Weaver, 1981a (White female
sample)
Glenn & Weaver, 1981a (Black female
sample)
Glenn & Weaver, 1981a (White male
sample)
Glenn & Weaver, 1981a (Black male
sample)
Glenn & Weaver, 1981a (White female
sample)
Glenn & Weaver, 1981a (Black female
sample)
Judge & Higgins, 1998 (Study 1)
112
118
118
118
118
90
63
63
1,872
Judge & Higgins, 1998 (Study 2)
95
Lucas et al., 1996 (Study 1)
Lucas et al., 1996 (Study 1)
212
212
.17
.59
.60
(table continues)
LYUBOMIRSKY, KING, AND DIENER
810
Table 1 (continued )
Study
n
Happiness/PA measure
Correlated construct
Effect size
(r)
Positive perceptions of self and others (continued)
Lucas et al., 1996 (Study 2)
Lucas et al., 1996 (Study 2)
Lucas et al., 1996 (Study 3)
Lucas et al., 1996 (Study 3)
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Lyubomirsky & Tucker, 1998a (Study 1)
Lyubomirsky & Tucker, 1998a (Study 3)
Lyubomirsky & Tucker, 1998a (Study 3)
Mayer et al., 1988 (preliminary study)
Mayer et al., 1988 (Study 2)
Mongrain & Zuroff, 1995
Pfeiffer & Wong, 1989a
Pfeiffer & Wong, 1989a
Pfeiffer & Wong, 1989a
Ryff, 1989
Schimmack et al., 2004a (Study 1)
Schimmack et al., 2004a (Study 2)
Schimmack et al., 2004a (Study 1)
Tarlow & Haaga, 1996
Totterdell, 2000a
109
109
172
172
621
621
621
621
621
621
621
621
621
621
621
105
47
38
206
193
152
123
123
123
321
136
124
136
124
18
Weiss et al., 1999a
24
SWLS
SWLS
SWLS
SWLS
SHS
SHS
SHS
SHS
SHS
SHS
SHS
SHS
SHS
SHS
SHS
SHS
SHS
SHS
Mood-State Introspection Scale
Mood-State Introspection Scale
Four positive adjectives
MUNSH
MUNSH
MUNSH
Life Satisfaction Index
SWLS
SWLS
SWLS
PANAS
One-item happiness (12 times over
4 days)
Fordyce HM Scale
Self-esteem
Optimism
Self-esteem
Optimism
Self-esteem
Optimism
Sense of mastery
Perceived control
Satisfaction with family relations
Satisfaction with friends
Satisfaction with health
Satisfaction with education
Satisfaction with recreation
Satisfaction with housing
Satisfaction with transportation
Evaluations of past life events
Liking of videotaped target
Evaluations of real-life target
Inferences about people
Inferences about people
Self-criticism
Cognitive jealousy
Emotional jealousy
Behavioral jealousy
Personal growth
Self-rated assertiveness
Self-rated assertiveness
Self-rated warmth
Self-esteem
Self-rated performance
.65
.59
.54
.57
.62
.60
.55
.47
.41
.50
.43
.27
.51
.43
.34
.41
.29
.36
.29
.29
⫺.39
⫺.08
⫺.24
⫺.17
.38
.21
.36
.27
.57
.50
Satisfaction with job
.29
Attendance at club meetings
Quality of conversation
Degree of disclosure in conversation
Degree of engagement in conversation
Intimacy of conversation
No. of daily interactions
Extraversion
Extraversion
.31
.27
.06
.10
.09
.34
.31
.43
Extraversion
Extraversion
Social activities
Extraversion
Extraversion
Informant-rated energy
Extraversion
.21
.54
.40
.16
.16
.39
.49
Peer ratings of target’s relationships
.65
Performance-approach goals
Personal conversations
Intrinsically motivating
experiences (%)
Extraversion
Self-rated affiliation
Observer-rated affiliation
Extraversion
Extraversion
Flow
Satisfaction with activities
.15
.35
.28
Sociability and activity
Bahr & Harvey, 1980
Berry & Hansen, 1996a (Study 1)
Berry & Hansen, 1996a (Study 1)
Berry & Hansen, 1996a (Study 1)
Berry & Hansen, 1996a (Study 1)
Berry & Hansen, 1996a (Study 2)
Brebner et al., 1995
Brebner et al., 1995
44
112
112
112
112
105
95
95
Brebner et al., 1995
Burger & Caldwell, 2000a
Burger & Caldwell, 2000a
Costa & McCrae, 1980a
Costa & McCrae, 1980a
Diener & Fujita, 1995a
Diener & Seligman, 2002a
95
134
134
753
554
186
106
Diener & Seligman, 2002a
106
Elliot & Thrash, 2002
Gladow & Ray, 1986a
Graef et al., 1983
176
63
107
Griffin et al., in press
Harker & Keltner, 2001a
Harker & Keltner, 2001a
Headey & Wearing, 1989
Headey & Wearing, 1989
Hektner, 1997a
Kahana et al., 1995
1,051
49
114
649
649
281
257
One-item happiness
PANAS
PANAS
PANAS
PANAS
PANAS
Oxford Happiness Inventory
Personal State Questionnaire,
Version 5
LOT
PANAS
PANAS
Bradburn’s Scales
Bradburn’s Scales
SWLS
SWLS, affect balance, memory
recall
SWLS, affect balance, memory
recall
General Temperament Survey
One-item happiness
One-item happiness
PANAS
FACS Duchenne smile
FACS Duchenne smile
Life Satisfaction Index
Bradburn’s Scales
One-item happy mood
Fifteen items from the 22-item
screening score
.32
.33
.69
.20
.18
.27
.38
BENEFITS OF FREQUENT POSITIVE AFFECT
811
Table 1 (continued )
Study
n
Happiness/PA measure
Effect size
(r)
Correlated construct
Sociability and activity (continued)
Kashdan & Roberts, 2004a
Kashdan & Roberts, 2004a
Lu & Argyle, 1991
Lu & Argyle, 1991
Lucas et al., 2000
Lucas et al., 2000
Lucas et al., 2000
Lucas, 2001a (daily study)
Lucas, 2001a (daily study)
Lucas, 2001a (daily study)
Lucas, 2001a (moment study)
Lucas, 2001a (moment study)
Lyubomirsky et al., in pressa
Lyubomirsky et al., in pressa
Matikka & Ojanen, in press
Matikka & Ojanen, in press
Mishra, 1992a
104
104
114
114
5,842
5,842
5,842
144
144
144
124
124
621
621
376
376
720
PANAS
PANAS
Oxford Happiness Inventory
Oxford Happiness Inventory
PANAS
PANAS
PANAS
PANAS
PANAS
PANAS
Time felt happy and pleasant (%)
Time felt happy and pleasant (%)
SHS
SHS
Three-item happiness
Three-item happiness
Index of Life Satisfaction
Mishra, 1992a
720
Index of Life Satisfaction
Mishra, 1992a
Schimmack et al., 2004a (Study 1)
Schimmack et al., 2004a (Study 1)
Schimmack et al., 2004a (Study 1)
Schimmack et al., 2004a (Study 2)
Schimmack et al., 2004a (Study 2)
Stones & Kozma, 1986a
Watson, 1988a
Watson et al., 1992a (Study 1)
Watson et al., 1992a (Study 2)
Watson et al., 1992a (Study 1)
720
136
136
136
124
124
408
71
85
127
79
Watson et al., 1992a (Study 2)
Watson et al., 1992a (Study 2)
96
120
Index of Life Satisfaction
SWLS
SWLS
SWLS
SWLS
SWLS
MUNSH
Positive Emotionality Scale
PANAS (weekly, over 13 weeks)
PANAS (daily, over 6–7 weeks)
PANAS, extraversion, positive
temperament
PANAS, joviality
PANAS, extraversion, positive
temperament
Attraction to partner
Closeness to partner
Attitude toward joint activities
Attitude toward group activities
Extraversion
Ascendance
Affiliation
Experience of Affiliation/warmth
Time spent with friends
Time spent leading
Time spent leading
Time spent with friends and family
Extraversion
Satisfaction with recreation
Social participation
Social inclusion
Engaging in hobbies and special
interests
Interaction with members of voluntary
organizations
Engaging in occupational activities
Extraversion
Gregariousness
Informant ratings of how active
Friendliness
Gregariousness
Activity level
Social activity
Weekly social activity
Weekly social activity
Weekly social activity
.50
.30
.25
.22
.62
.30
.27
.48
.22
.20
.24
.19
.36
.51
.22
.21
.63
.64
.33
.26
.24
.43
.21
.13b
.34
.36
.39
.35
Weekly social activity
Weekly social activity
.31
.28
.50
Likeability and cooperation
Barsade et al., 2000
Barsade et al., 2000
Bell, 1978
Berry & Hansen, 1996a (Study 1)
Berry & Hansen, 1996a (Study 1)
Diener & Fujita, 1995a
62
20
120
112
112
186
Diener & Fujita, 1995a
186
Diener & Fujita, 1995a
186
Diener & Fujita, 1995a
186
Diener & Fujita, 1995a
186
Diener & Fujita, 1995a
186
Diener & Fujita, 1995a
186
Diener & Fujita, 1995a
186
Diener & Fujita, 1995a
186
Harker & Keltner, 2001a
Harker & Keltner, 2001a
Harker & Keltner, 2001a
Harker & Keltner, 2001a
114
114
114
114
MPQ well-being
MPQ well-being
Personal Feelings Scale
PANAS
PANAS
Delighted-Terrible Scale, Fordyce
one-item happiness
Delighted-Terrible Scale, Fordyce
one-item happiness
Delighted-Terrible Scale, Fordyce
one-item happiness
Delighted-Terrible Scale, Fordyce
one-item happiness
Delighted-Terrible Scale, Fordyce
one-item happiness
Delighted-Terrible Scale, Fordyce
one-item happiness
Delighted-Terrible Scale, Fordyce
one-item happiness
Delighted-Terrible Scale, Fordyce
one-item happiness
Delighted-Terrible Scale, Fordyce
one-item happiness
FACS Duchenne smile
FACS Duchenne smile
FACS Duchenne smile
FACS Duchenne smile
Task conflict
Group cooperativeness
Likeability as work partner
Intimacy of conversation
Degree of disclosure in conversation
Judged physical attractiveness
⫺.30
.38
.43
.09
.06
.33
Judged intelligence/competence
.30
Judged social skills
.41
Judged public speaking ability
.28
Judged self-confidence
.36
Judged assertiveness
.25
Judged number of close friends
.35
Judged likelihood of having a strong
romantic relationship
Judged likelihood of having family
support
Observer-rated affiliation
Observer-rated negative emotionality
Judged positive emotionality
Judged competence
.33
.34
.69
⫺.57
.71
.21
(table continues)
LYUBOMIRSKY, KING, AND DIENER
812
Table 1 (continued )
Study
n
Happiness/PA measure
Correlated construct
Effect size
(r)
Partner-rated attraction
Partner-rated closeness
Judged moral goodness
Judged likelihood of going to heaven
Judged moral goodness
Judged likelihood of going to heaven
Judged physical attractiveness
Judged physical attractiveness
Helpfulness
Selfishness
Personality strength
Informant-rated warmth
Informant-rated friendliness
Informant-rated assertiveness
Informant-rated assertiveness
Judged managerial potential
Judged positive personal qualities
Interpersonal conflict
.34
.30
.29
.25
.26
.26
.37
.09
.44
⫺.60
.21
.28
.33
.20
.25
.20
.28
⫺.12
Likeability and cooperation (continued)
Kashdan & Roberts, 2004a
Kashdan & Roberts, 2004a
King & Napa, 1998 (Study 1)
King & Napa, 1998 (Study 1)
King & Napa, 1998 (Study 2)
King & Napa, 1998 (Study 2)
Mathes & Kahn, 1975 (female sample)
Mathes & Kahn, 1975 (male sample)
Perry et al., 1986 (eighth grade sample)
Rimland, 1982
Scheufele & Shah, 2000
Schimmack et al., 2004a (Study 1)
Schimmack et al., 2004a (Study 2)
Schimmack et al., 2004a (Study 1)
Schimmack et al., 2004a (Study 2)
Staw & Barsade, 1993a
Taylor et al., 2003
Van Katwyk et al., 2000a (Study 3)
104
104
104
104
264
264
101
110
32
1,991
3,462
136
124
136
124
111
55
111
PANAS
PANAS
Three -item happiness
Three-item happiness
Three-item happiness
Three-item happiness
Happiness
Happiness
Dichotomous “Who is happier?‘
Dichotomous “Happy or not?‘
Four-item Index of Life Satisfaction
SWLS
SWLS
SWLS
SWLS
Three-measure composite
Ten-measure composite
PANAS
Prosocial behavior
Feingold, 1983 (male sample)
Feingold, 1983 (female sample)
George, 1991
George, 1991
Krueger et al., 2001a
Lucas, 2001a (daily study)
Lucas, 2001a (moment study)
Magen & Aharoni, 1991a
87
88
221
221
397
144
124
260
Magen & Aharoni, 1991a
260
Rigby & Slee, 1993
869
One-item happiness
One-item happiness
Job Affect Scale
Job Affect Scale
MPQ positive emotionality
PANAS
Time felt happy and pleasant (%)
Four-item intensity of positive
experience
Four-item intensity of positive
experience
Life-as-a-Whole Index
Strayer, 1980a
14
Observational count of happy affect
Williams & Shiaw, 1999
139
Watson 10-item positive affectivity
scale
Unselfishness
Unselfishness
Extrarole prosocial behavior
Customer service
Self-reported altruistic acts
Time spent helping
Time spent helping
Transpersonal commitment
.27
.09
.24
.26
.44
.36
.27
.21
Involvement in community service
.36
Tendency to act in a prosocial or
cooperative manner
Observational count of empathetic
responses
Anticipated organizational citizenship
behavior
.36
.59
.42
Physical well-being and coping
Achat et al., 2000a
Achat et al., 2000a
Audrain et al., 2001
Bardwell et al., 1999 (healthy sample)
Bardwell et al., 1999 (healthy sample)
Benyamini et al., 2000a
Carver et al., 1993a (presurgery assessment)
Carver et al., 1993a (presurgery assessment)
Carver et al., 1993a (presurgery assessment)
Carver et al., 1993a (presurgery assessment)
C. C. Chen et al., 1996
Dillon & Totten, 1989
Goldman et al., 1996
659
659
227
40
40
851
59
59
59
59
121
16
134
Irving et al., 1998
Kehn, 1995a
Keltner & Bonanno, 1997
Lox et al., 1999
Lutgendorf et al., 1999 (movers sample)
Lyons & Chamberlain, 1994
Lyons & Chamberlain, 1994
Lyubomirsky et al., in pressa
Lyubomirsky & Tucker, 1998a (Study 1)
115
98
39
121
26
158
158
621
105
LOT
LOT
PANAS
One-item vigor
One-item vigor
12-item positive affect
LOT
LOT
LOT
LOT
General Health Questionnaire
Coping Humor Scale
Repair Subscale of the Trait
Meta-Mood Scale
Hope Scale
Life Satisfaction Index
FACS Duchenne laughter
Affective Reactions Measure
Sense of Coherence Scale
Uplifts Scale
LOT
SHS
SHS
General health
Pain
Physical activity
Sleep quantity
Sleep quality
Self-reported health
Active coping
Coping by positive reframing
Coping by humor
Coping by denial
Engagement coping
Presence of upper respiratory infection
Reported illnesses
.23b
⫺.09b
.19
.32
.36
.49
.33
.41
.40
⫺.39
.31
⫺.58
⫺.21
Hope-related coping responses
Global health
Perceived adjustment
Amount of physical exercise
NK cell activity
Upper respiratory infection symptoms
Upper respiratory infection symptoms
Satisfaction with health
Perception of life events
.35
.43
.31
.19
.49
⫺.03
⫺.23
.43
.41
BENEFITS OF FREQUENT POSITIVE AFFECT
813
Table 1 (continued )
Study
n
Happiness/PA measure
Correlated construct
Effect size
(r)
Physical well-being and coping (continued)
McCrae & Costa, 1986 (Study 1)
McCrae & Costa, 1986 (Study 1)
Mishra, 1992a
Pettit et al., 2001a
254
254
720
140
Pettit et al., 2001a
Pettit et al., 2001a
Riddick, 1985 (male sample)
Riddick, 1985 (female sample)
Røysamb et al., 2003a
Røysamb et al., 2003a
Stone et al., 1987
Stone et al., 1994
Stones & Kozma, 1986a
Sullivan et al., 2001
Valdimarsdottir & Bovbjerg, 1997
(with daily NA)
Valdimarsdottir & Bovbjerg, 1997
(no daily NA)
Vitaliano et al., 1998a
140
140
806
753
6,576
6,576
30
96
408
105
26
PANAS
PANAS
Life Satisfaction Index
Life Satisfaction Index
SWB Index
SWB Index
Nowlis Mood Adjective Checklist
PANAS
MUNSH
PANAS
Profile of Mood States
22
42
Profile of Mood States
Uplifts-Hassles
10-item PA Scale (daily, over 6–8
weeks)
10-item PA Scale (daily, over 6–8
weeks)
Positive Emotionality Scale (daily)
Positive temperament
Positive temperament
PANAS (weekly, over 13 weeks)
PANAS (daily, over 6–7 weeks)
Positive mood checklist
Mood Adjective Check List
Watson, 1988a
80
Watson, 1988a
Watson, 1988a
Watson, 2000
Watson, 2000
Watson et al., 1992a (Study 1)
Watson et al., 1992a (Study 2)
Weinglert & Rosen, 1995
Zinser et al., 1992
80
80
354
354
85
127
71
22
Bradburn’s Scales
Bradburn’s Scales
Index of Life Satisfaction
PANAS
Coping effectiveness
Mature coping
Overall activity level
Presence and severity of medical
conditions
Cigarette use
Alcohol intake
Leisure activities
Leisure activities
Global health
Musculoskeletal pain
Secretory IgA antibody activity
Antibody activity
Global health
Self-reported physical health
NK cell activity
NK cell activity
NK cell activity
.27
.26
.61
⫺.26
⫺.24
⫺.22
.37
.44
.50
⫺.25
.44
.05
.19b
.23
0.64
.05
.26
Daily physical complaints
⫺.18
Daily physical exercise
Physical exercise
Injury visits to health center
Illness visits to health center
Weekly social activity
Weekly social activity
Somatic symptoms
Urges to smoke
.12
.12
.12
.15
.36
.39
⫺.10
⫺.38
Exploration strivings
Absorption in activities
Creative episodes
Creativity
Maximizing tendencies
Maximizing tendencies
Maximizing tendencies
Maximizing tendencies
Maximizing tendencies
Maximizing tendencies
.44
.33
.41
.25
⫺.21
⫺.34
⫺.17
⫺.10
⫺.28
⫺.17
Creativity and problem solving
Kashdan et al., 2004 (Study 2)
Kashdan et al., 2004 (Study 2)
Richards & Kinney, 1990
Schuldberg, 1990
Schwartz et al., 2002 (Sample 1)
Schwartz et al., 2002 (Sample 2)
Schwartz et al., 2002 (Sample 3)
Schwartz et al., 2002 (Sample 4)
Schwartz et al., 2002 (Sample 5)
Schwartz et al., 2002 (Sample 6)
214
214
48
334
82
72
100
401
752
220
Shapiro & Weisberg, 1999
52
Staw & Barsade, 1993a
83
Staw et al., 1994a
272
PANAS activated
PANAS activated
Diagnosis of manic periods
Hypomanic traits
SHS
SHS
SHS
SHS
SHS
SHS
General Behavior Inventory
(hypomanic plus biphasic)
Three-measure composite of
positive affectivity
Experience and expression of
positive emotion on the job
Trait creativity
.33
Judged managerial performance
.20
Judged creativity
.30
Note. PA ⫽ positive; PANAS ⫽ Positive and Negative Affect Schedule; MPQ ⫽ Multidimensional Personality Questionnaire; SWLS ⫽ Satisfaction With
Life Scale; HM ⫽ Happiness Measure; MUNSH ⫽ Memorial University of Newfoundland Scale of Happiness; SHS ⫽ Subjective Happiness Scale; LOT ⫽
Life Orientation Test; MAACL ⫽ Multiple Adjective Affect Checklist; SWB ⫽ Subjective Well-Being; FACS ⫽ Facial Action Coding System; NEO ⫽
Neuroticism/Extraversion/Openness Scale; ER ⫽ emergency room.
Subscript a indicates that the study appears in more than one section or table. Subscript b indicates that the effect size was calculated controlling for one
or more other variables.
LYUBOMIRSKY, KING, AND DIENER
814
Table 2
Study Information and Effect Sizes for Seven Categories of Longitudinal Research
Study
n
Happiness/PA measure
Correlated construct
Time period
Effect size
(r)
.35
.36
.27
.17
.18
.03b
.04b
⫺.02b
.03
⫺.36
.13
Work life
Burger & Caldwell, 2000a
Cropanzano & Wright, 1999a
Cropanzano & Wright, 1999a
Cropanzano & Wright, 1999a
Cropanzano & Wright, 1999a
Diener et al., 2002
Graham et al., in pressa
Graham et al., in pressa
Marks & Fleming, 1999
Pelled & Xin, 1999
Roberts et al., 2003
99
60
60
60
60
7,882
4,455
4,489
1,322
99
859
PANAS
Index of Psychological Well-Being
Index of Psychological Well-Being
Index of Psychological Well-Being
Index of Psychological Well-Being
On-item cheerfulness
One-item residual happiness
One-item residual happiness
Nine-item SWB index
PANAS
MPQ communal positive
emotionality
MPQ agency positive emotionality
MPQ communal positive
emotionality
MPQ agency positive emotionality
MPQ communal positive
emotionality
MPQ agency positive emotionality
Attributional Style Questionnaire
Proportion of second interviews
Supervisory evaluations
Supervisory evaluations
Supervisory evaluations
Supervisory evaluations
Income
Income
Unemployment
Income
Absenteeism
Financial security
3 months
1 year
4 years
4.5 years
5 years
19 years
5 years
5 years
1–15 years
5 months
8 years
Financial security
Occupational attainment
8 years
8 years
.06
.19
Occupational attainment
Work autonomy
8 years
8 years
.16
.06
Work autonomy
Quarterly insurance commissions
.13
.27
Job autonomy, meaning, and variety
8 years
6 months
to 1 year
1.5 years
Gross annual salary
1.5 years
.24
Judged creativity
1.5 years
.16
Supervisory evaluations
3.5 years
.47
Supervisory evaluations
1 year
.46
Roberts et al., 2003
Roberts et al., 2003
859
859
Roberts et al., 2003
Roberts et al., 2003
859
859
Roberts et al., 2003
Seligman & Schulman, 1986a
(Study 2)
Staw et al., 1994a
859
68
129
Staw et al., 1994a
191
Staw et al., 1994a
191
Wright & Staw, 1999a
(Study 1)
Wright & Staw, 1999a
(Study 2)
44
Experience and expression of
positive emotion on the job
Experience and expression of
positive emotion on the job
Experience and expression of
positive emotion on the job
Index of Psychological Well-Being
63
Index of Psychological Well-Being
.23
Social relationships
Harker & Keltner, 2001a
Harker & Keltner, 2001a
Harker & Keltner, 2001a
Headey et al., 1991a
Lucas et al., 2003
Marks & Fleming, 1999a
Neyer & Asendorpf, 2001
Ruvolo, 1998a
(wives sample)
Ruvolo, 1998a
(wives sample)
Ruvolo, 1998a
(husbands sample)
Ruvolo, 1998a
(husbands sample)
Spanier & Furstenberg, 1982
Staw et al., 1994a
71
111
112
649
1,761
1,322
489
317
FACS Duchenne smile
FACS Duchenne smile
FACS Duchenne smile
Life-as-a-Whole Index
One-item happiness
Nine-item SWB index
General Self-Esteem
One-item happiness
Marital satisfaction
Marital status
Single status
Satisfaction with marriage
Marital status
Marital status
Closeness with all relationships
Marital well-being
31 years
6 years
22 years
6 years
4⫹ years
1–15 years
4 years
1 year
.20
.19
⫺.20
.30
.20
.09
.19b
.30
317
One-item happiness
Spouse’s marital well-being
1 year
.15
317
One-item happiness
Marital well-being
1 year
.28
317
One-item happiness
Spouse’s marital well-being
1 year
.40
180
251
Cantril’s Ladder Scale
Experience and expression of
positive emotion on the job
Remarriage after divorce
Emotional and tangible support form
supervisors
2.5 years
1.5 years
.16
.25b
Mortality rate
Probability of dying relative to peers
Survival
CHD risk reduction
Age at death
Pain
Hospital visits
Emergency room visits
Health problems last 30 days
Lifetime
26–28 years
4 years
9 months
lifetime
2 days
1 day
1 day
5 years
⫺.31
⫺.11
.15
.30b
⫺.09
⫺.06b
⫺.04b
⫺.06b
⫺.06b
Health
Danner et al., 2001
Deeg & van Zonneveld, 1989
Devins et al., 1990
Fitzgerald et al., 2000
Friedman et al., 1993
Gil et al., 2004a
Gil et al., 2004a
Gil et al., 2004a
Graham et al., in pressa
180
2,645
97
42
1,178
3,565
3,546
3,546
4,455
No. of positive emotional words
One-item life satisfaction
Life Happiness Rating Scale
LOT
Cheerfulness-Humor
Daily Mood Scale
Daily Mood Scale
Daily Mood Scale
Two-item residual happiness
BENEFITS OF FREQUENT POSITIVE AFFECT
815
Table 2 (continued )
Study
n
Happiness/PA measure
Correlated construct
Time period
Effect size
(r)
Health (continued)
Four
databases
29,137
SWB
Automobile fatalities
8 years
⫺.56
Four-item life satisfaction
Suicides
⫺.03
14,348
Four-item life satisfaction
14,789
Four-item life satisfaction
11,037
Four-item life satisfaction
11,099
Four-item life satisfaction
330
Eight-item life satisfaction
Fatal intentional and unintentional
injuries
Fatal intentional and unintentional
injuries
Work disability pension for
psychiatric and nonpsychiatric
causes
Work disability pension for
psychiatric and nonpsychiatric
causes
Survival fatal and nonfatal coronary
heart disease
Up to 20
years
Up to 20
years
Up to 20
years
Up to 11
years
Kubzansky et al., 2001
1,306
Kubzansky et al., 2001
1,306
Kubzansky et al., 2001
1,306
513
2,276
772
Revised Optimism-Pessimism
Scale
Revised Optimism-Pessimism
Scale
Revised Optimism-Pessimism
Scale
Affect Balance Scale-Joy
Attitudes Toward Own Aging
Subscale
PANAS
CESD Positive Affect Scale
CESD Positive Affect Scale
1,706
Kirkcaldy & Furnham, 2000
Koivumaa-Honkanen et al.,
2001
Koivumaa-Honkanen et al.,
2002 (male sample)
Koivumaa-Honkanen et al.,
2002 (female sample)
Koivumaa-Honkanen et al.,
2004 (male sample)
Koivumaa-Honkanen et al.,
2004 (female sample)
Krause et al., 1997
Levy et al., 1988
Levy et al., 2002 (Study 2)
Maier & Smith, 1999
Ostir et al., 2000
Ostir et al., 2001
(male sample)
Ostir et al., 2001
(female sample)
Palmore, 1969
Peterson et al., 1998
36
660
265
1,097
Peterson et al., 1998
(male sample)
Peterson et al., 1998
(male sample)
Peterson et al., 1998
(male sample)
Pitkala et al., 2004
Reynolds & Nelson, 1981
Scheier et al., 1989a
Scheier et al., 1989a
Scheier et al., 1989a
Scheier et al., 1989a
Scheier et al., 1989a
Smith et al., 1997
Windle, 2000a
491
154
46
46
45
45
44
86
1,016
Windle, 2000a
1,016
Windle, 2000a
1,016
Zuckerman et al., 1984
(healthy sample)
Zuckerman et al., 1984
(unhealthy sample)
622
622
622
182
168
⫺.06
⫺.02
⫺.11
Up to 11
years
⫺.12
11 years
.18
12 years
⫺.14
Fatal coronary heart disease
12 years
⫺.07
Nonfatal angina and heart attacks
12 years
⫺.12
Survival
Days survival
7 years
22.6 years
.36
.25
Mortality rate
Survival
Stroke incidence
3–6 years
2 years
6 years
⫺.06
.08
⫺.13b
CESD Positive Affect Scale
Stroke incidence
6 years
⫺.05b
One-item interviewer-rated
happiness
Optimistic (global) attributional
style
Optimistic (global) attributional
style
Optimistic (global) attributional
style
Optimistic (global) attributional
style
S
Life satisfaction scale
LOT
LOT
LOT
LOT
LOT
One-item vigor
Revised Dimension of
Temperament Survey
Revised Dimension of
Temperament Survey
Revised Dimension of
Temperament Survey
One-item interviewer-rated
happiness
One-item interviewer-rated
happiness
Mortality rate
15 years
⫺.26
Mortality rate
Lifetime
⫺.11
Mental health problems
10 years
⫺.14
Poor adjustment
10 years
⫺.11
High levels of drinking
10 years
⫺.07
Survival
Survival
No. of days to begin walking
Physical recovery
Postsurgical quality of life
Resume vigorous exercise
Return to normal activities
Hockey injury
Delinquent activity
10 years
1 year
1 week
1 week
6 months
6 months
6 months
6 months
6 months
.13
.13
⫺.36
.35
.67
.33
.38
⫺.32
⫺.25
Delinquent activity
12 months
⫺.15
Delinquent activity
18 months
⫺.12
Mortality rate
2 years
⫺.07
Mortality rate
2 years
⫺.14
Positive perceptions of self and others
Harker & Keltner, 2000a
Harker & Keltner, 2001a
104
100
FACS Duchenne smile
FACS Duchenne smile
Self-rated competence
Self-rated competence
22 years
31 years
.20
.29
(table continues)
LYUBOMIRSKY, KING, AND DIENER
816
Table 2 (continued )
Study
n
Time period
Effect size
(r)
2–10 years
10–17 years
10 years
22 years
31 years
1.5 years
.20
.24
.23
.23
.16
.29b
Judged creativity
1.5 years
.31b
Time spent engaged in volunteer
work
3 years
.04b
1 year
3 years
5 years
3 months
3 months
3 months
3 months
1 month
3 months
6 months
5 weeks
5 years
5 years
5 weeks
.13b
.11b
.17b
.16
.26
.38
⫺.37
⫺.14
⫺.40
⫺.55
.19
⫺.04b
⫺.06b
⫺.31
1 week
1 week
1.5 years
1.5 years
.43
⫺.30
.28b
.48
Happiness/PA measure
Correlated construct
Sociability and activity
Costa et al., 1981
Costa et al., 1981
Costa & McCrae, 1980a
Harker & Keltner, 2001a
Harker & Keltner, 2001a
Stones & Kozma, 1986a
396
114
234
104
100
408
Chicago Attitude Inventory
Chicago Attitude Inventory
Bradburn’s Scales
FACS Duchenne smile
FACS Duchenne smile
MUNSH
Extraversion
Extraversion
Extraversion
Self-rated affiliation
Self-rated affiliation
Activity level
Creativity and prosocial behavior
Staw et al., 1994a
Thoits & Hewitt, 2001a
191
2,681
Experience and expression of
positive emotion on the job
One-item happiness
Physical well-being and coping
Benyamini et al., 2000a
Benyamini et al., 2000a
Benyamini et al., 2000a
Carver et al., 1993a
Carver et al., 1993a
Carver et al., 1993a
Carver et al., 1993a
Cohen et al., 2003
Epping-Jordan et al., 1999
Epping-Jordan et al., 1999
Fredrickson & Joiner, 2002
Graham et al., in pressa
Graham et al., in pressa
Pettit et al., 2001a
791
678
525
59
59
59
59
334
80
80
138
1,683
1,252
1,33
Scheier et al., 1989a
Scheier et al., 1989a
Stones & Kozma, 1986a
Vitaliano et al., 1998a
47
47
408
23
12-item positive affect
12-item positive affect
12-item positive affect
LOT
LOT
LOT
LOT
Positive emotional style
LOT
LOT
PANAS
One-item residual happiness
One-item residual happiness
PANAS
LOT
LOT
MUNSH
Uplifts-Hassles
Global health
Global health
Global health
Active coping
Coping by positive reframing
Coping by humor
Coping by denial
Presence of clinical infection
Symptoms of anxiety/depression
Symptoms of anxiety/depression
Broad-minded coping
Alcohol intake
Smoking
Presence and severity of medical
conditions
Coping by information seeking
Coping by suppression
Global health
NK cell activity
Note. PA ⫽ positive affect; PANAS ⫽ Positive and Negative Affect Schedule; MPQ ⫽ Multidimensional Personality Questionnaire; FACS ⫽ Facial
Action Coding System; CES-D ⫽ Center for Epidemiologic Depression Scale; SWLS ⫽ Satisfaction With Life Scale; LOT ⫽ Life Orientation Test;
MUNSH ⫽ Memorial University of Newfoundland Scale of Happiness; HM ⫽ Happiness Measure; SWB ⫽ Subjective Well-Being; NK ⫽ natural killer.
Subcript a indicates that the study appears in more than one panel or table. Subscript b indicates that the effect size was calculated controlling for one or
more other variables
independence among them. To this end, several guidelines were
followed.
First, when more than one effect size was generated from the
same sample, and these effect sizes involved moderately to highly
correlated constructs (e.g., judgments of friendliness, gregariousness, and assertiveness), they were not treated independently. As a
result, the unweighted average of each set of correlated effect sizes
was used in our analyses. This procedure was used for effect sizes
generated from the same sample and reported within a particular
panel of a table (e.g., those involving work life in Table 1).
Second, as mentioned previously, we recognized that sometimes
the same sample was used to generate effect sizes in more than one
panel of a table (e.g., sociability/activity and health) or even across
tables (e.g., supervisory evaluations assessed at a single point in
time [in Table 1] as well as two points in time [in Table 2]). In such
instances, we selected only one specific effect size for our analyses. If the rs came from the same table, the effect size tapping the
best fitting construct was chosen. If the rs spanned Tables 1 and 2,
the effect size reflecting a longitudinal correlation was selected, as
longitudinal data speak relatively more strongly to causation.
Third, even when generated from the same sample or dataset,
effect sizes were considered independent if they involved variables
that are not highly correlated with one another (e.g., income and
alcohol consumption; see Meng, Rosenthal, & Rubin, 1992).
Defining Our Terms
What Is the Hallmark of Happiness?
Our focus in this article is on happy individuals—that is, those
who experience frequent positive emotions, such as joy, interest,
and pride, and infrequent (though not absent) negative emotions,
such as sadness, anxiety, and anger. Although many definitions of
happiness have been used in the literature, ranging from life
satisfaction and an appreciation of life to momentary feelings of
pleasure, we define happiness here as a shorthand way of referring
BENEFITS OF FREQUENT POSITIVE AFFECT
817
Table 3
Study Information and Effect Sizes for Six Categories of Experimental Research
Study
n
Affect induction
Comparison groups
Effect size
(r)
Dependent variable
Positive perceptions of self and others
Baron, 1987
71
False feedback
Positive vs. negative
and control
Positive vs. negative
and control
Positive vs. control
Positive vs. control
Positive vs. negative
Likeability of accomplice
.44
Baron, 1987
71
False feedback
Judgment of whether employee
matches job requirements
Self-efficacy
Self-set goals
Overall evaluation of accomplice
for job
Overall rating of employee
.43
Baron, 1990a
Baron, 1990a
Baron, 1993
80
80
92
Fragrance
Fragrance
Recall event(s)
Baron et al., 1992 (Study 1)
91
Lighting
Baron et al., 1992 (Study 1)
91
Lighting
Baron et al., 1992 (Study 3)a
80
Gift
High illuminance vs.
low illuminance
High illuminance vs.
low illuminance
Positive vs. control
Hiring decision
.34
Judgment of whether hypothetical
employee deserves merit raise
Judgment of whether hypothetical
employee deserves promotion
Perceived task performance
Certainty of future success
Attribution of successes to stable
causes
Recall of positive aspects of past
experiences
Interpersonal attraction
.23
Baron et al., 1992 (Study 3)a
80
Gift
Positive vs. control
Barsade, 2002a
Brown, 1984
Brown, 1984
93
61
61
Confederate role playing
Velten
Velten
Positive vs. negative
Positive vs. negative
Positive vs. negative
Clark & Waddell, 1983
45
False feedback
Positive vs. control
Griffitt, 1970
40
Temperature
Hom & Arbuckle, 1988
Samson & Rachman, 1989
Sarason et al., 1986 (Study 2)
31
84
60
Recall event(s)
Music and thought
Self-description task
Schuettler & Kiviniemi, in pressa
Wright & Mischel, 1982
Wright & Mischel, 1982
50
72
72
Velten
Recall event(s)
Recall event(s)
Extreme heat vs. normal
temperature
Happy vs. sad
Happy vs. sad
Positive vs. negative
self-feelings
Positive vs. negative
Positive vs. negative
Positive vs. negative
.33
Goal setting
Self-efficacy
Positive self-references
.48
.28
.39
Self-efficacy regarding health
Satisfaction with performance
Recall of past successes
.43
.64
.75
Elated vs. neutral and
depressed
Elated vs. neutral and
depressed
Elated vs. neutral and
depressed
Positive vs. negative
Interest in being with friends
.20
Interest in social activities
.31
Interest in leisure activities
.33
High self-disclosure
.44
Positive vs. negative
Total communication
.53
Positive vs. negative
and control
Positive vs. negative
Positive vs. neutral
Amused vs. neutral
Interest in category-sorting task
.56
Attentive
Intrinsic interest
Perceived relationship closeness
.71
.74
.27
More monetary concessions
Resolving interpersonal conflict
through avoidance
Resolving interpersonal conflict
through competition
Preference to resolve conflict
through avoidance
Preference to resolve conflict
through avoidance
Preference to resolve conflict
through collaboration
Resolving interpersonal conflict
through collaboration
.23
⫺.23
.16
.22
.17
.53
.21
.21
.73
.26
.36
Sociability and activity
Cunningham, 1988a (Study 1)a
102
Velten
Cunningham, 1988a (Study 1)a
102
Velten
Cunningham, 1988a (Study 1)a
102
Velten
Cunningham, 1988b
77
Cunningham, 1988b
77
Hirt et al., 1996
194
False feedback and
videotape
False feedback and
videotape
Velten
McMillen et al., 1977 (Study 1)
Murray et al., 1990 (Study 3)
Waugh & Fredrickson, 2003
27
85
94
False feedback
Velten and film clip(s)
Film clip(s)
Negotiation and conflict resolution
Baron, 1990a
Baron, 1990a
80
80
Fragrance
Fragrance
Positive vs. control
Positive vs. control
Baron, 1990a
80
Fragrance
Positive vs. control
Baron et al., 1990 (Study 2)a
16
Humor
Humor vs. control
Baron et al., 1990 (Study 2)a
16
Flattery
Flattery vs. control
Baron et al., 1990 (Study 2)a
16
Flattery
Flattery vs. control
Baron et al., 1992 (Study 2)*
72
Lighting
Warm vs. cool lighting
⫺.23
⫺.50
⫺.50
.50
.29
(table continues)
LYUBOMIRSKY, KING, AND DIENER
818
Table 3 (continued )
Study
n
Affect induction
Comparison groups
Dependent variable
Effect size
(r)
Negotiation and conflict resolution (continued)
Baron et al., 1992 (Study 2)a
72
Lighting
Warm vs. cool lighting
Barsade, 2002a
Barsade, 2002a
Carnevale & Isen, 1986a
Forgas, 1998 (Study 1)
26
26
80
72
Confederate role playing
Confederate role playing
Cartoon(s) and gift
False feedback
Positive vs. negative
Positive vs. negative
Positive vs. control
Positive vs. control
Forgas, 1998 (Study 1)
72
False feedback
Positive vs. control
Forgas, 1998 (Study 2)
132
False feedback
Positive vs. negative
Forgas, 1998 (Study 2)
132
False feedback
Positive vs. negative
Forgas, 1998 (Study 3)
96
False feedback
Positive vs. negative
Forgas, 1998 (Study 3)
96
False feedback
Positive vs. negative
Resolving interpersonal conflict
through avoidance
Judged group cooperativeness
Judged group conflict
Persist at negotiation
Planned use of cooperation as
bargaining strategy
Planned use of competition as
bargaining strategy
Planned use of cooperation as
bargaining strategy
Planned use of competition as
bargaining strategy
Planned use of cooperation as
bargaining strategy
Planned use of competition as
bargaining strategy
⫺.30
.44
⫺.42
.41
.32
⫺.32
.21
⫺.21
.30
⫺.24
Prosocial behavior
Aderman, 1972
Baron & Bronfen, 1994 (Study 2)
Baron et al., 1992 (Study 3)a
120
72
80
Velten
Fragrance
Lighting and gift
Berkowitz, 1987 (Study 1)
Berkowitz, 1987 (Study 2)
Carnevale & Isen, 1986a
Cunningham, 1988a (Study 1)a
108
60
80
102
Velten
Velten
Cartoon(s) and gift
Velten
Cunningham et al., 1980 (Study 1)
Cunningham et al., 1980 (Study 2)
Cunningham et al., 1990 (Study 1)
Cunningham et al., 1990 (Study 2)
Isen, 1970 (Study 1)
Isen, 1970 (Study 2)
Isen, 1970 (Study 2)
Isen, 1970 (Study 3)
Isen, 1970 (Study 3)
Isen & Levin, 1972 (Study 1)
90
160
80
78
14
12
10
20
20
52
Find dime
Find dime
Velten
Velten
False feedback
False feedback
False feedback
False feedback
False feedback
Gift
O’Malley & Andrews, 1983
Rosenhan et al., 1974
Rosenhan et al., 1981
90
36
20
Recall event(s)
Recall event(s)
Stories
Elated vs. depressed
Positive vs. control
Positive/high illuminance
vs. control/low
illuminance
Positive vs. negative
Positive vs. negative
Positive vs. control
Elated vs. neutral and
depressed
Positive vs. neutral
Positive vs. neutral
Positive vs. neutral
Positive vs. neutral
Positive vs. negative
Positive vs. control
Positive vs. control
Positive vs. control
Positive vs. negative
Positive/help vs. control/
distraction
Happy vs. neutral
Positive vs. control
Positive vs. neutral
Volunteering
Time spent helping
Time willing to help
.45
.28
.25
Helping
Helping
Helping
Interest in prosocial activities
.34
.68
.62
.27
Helping
Donating to charity
Helping
Helping
Amount of donation
Helping
Attentiveness
Helping
Initiation of conversation
Willingness to help
.28
.21
.33
.34
.58
.57
.58
.58
.61
.36
Donating blood
Contributing to needy children
Helping experimenter
.26
.52
.59
Physical well-being and coping
Alden et al., 2001
Cogan et al., 1987 (Study 1)
Dillon et al., 1985
Fredrickson & Levenson, 1998
(Study 2)
Fredrickson et al., 2000 (Study 1,
Sample 1)
Fredrickson et al., 2000 (Study 1,
Sample 2)
Futterman et al., 1994
38
40
10
72
Mental imagery
Audiotape
Humorous videotape
Video clip(s)
Positive vs. negative
Positive vs. control
Happy vs. control
Smiling vs. not smiling
95
Video clip(s)
Content vs. sad
75
Video clip(s)
Content vs. neutral
25
Reflect on scenario(s)
Lefcourt et al., 1990 (Study 1)
Lefcourt et al., 1990 (Study 2)
45
34
Humorous audio clip(s)
Humorous video clip(s)
Positive and negative
vs. control
Pre- vs. postaudio clip
Pre- vs. postvideo clip
Lefcourt et al., 1990 (Study 3)
McClelland & Cheriff, 1997 (Study 1)
McClelland & Cheriff, 1997 (Study 3)
Schuettler & Kiviniemi, in pressa
Schuettler & Kiviniemi, in pressa
41
57
85
50
50
Humorous Audio clip(s)
Video clip(s)
Video clip(s)
Velten
Velten
Pre- vs. postaudio clip
Positive vs. negative
Positive vs. control
Positive vs. negative
Positive vs. negative
Pain ratings
Pain threshold
Immune function
Duration of cardiovascular
reactivity
Duration of cardiovascular
reactivity
Duration of cardiovascular
reactivity
Immune function
.51
.45
.38
⫺.26
⫺.27
⫺.28
.76
Immune function
Immune function
.47
.46
Immune function
Immune function
Immune function
Self-efficacy regarding health
Health perceptions
.50
.33
.05
.43
.53
BENEFITS OF FREQUENT POSITIVE AFFECT
819
Table 3 (continued )
Study
n
Affect induction
Comparison groups
Dependent variable
Effect size
(r)
Physical well-being and coping (continued)
Schuettler & Kiviniemi, in pressa
50
Velten
Positive vs. negative
Smith et al., 2004
82
Recall event(s)
Recall of close vs.
casual relationship
Treatment-related behavioral
intentions
Blood pressure reactivity to
stressful task
.31
⫺.23
Creativity and problem solving
Adaman & Blaney, 1995
Ambady & Gray, 2002 (Study 1)
Ambady & Gray, 2002 (Study 2)
Baron, 1990a
71
35
47
80
Music
Video clip(s)
Video clip(s)
Fragrance
Sad vs. neutral
Happy and control vs. sad
Happy and control vs. sad
Positive vs. control
Bless et al., 1996 (Study 1)
82
Write about event(s)
Happy vs. sad
Bless et al., 1996 (Study 2)
61
Video clip(s)
Happy vs. sad
Bless et al., 1996 (Study 3)
80
Video clip(s)
Happy vs. sad
Bodenhausen et al., 1994 (Study 4)
131
Recall event(s)
Bodenhausen et al., 2000 (Study 1)
Bodenhausen et al., 2000 (Study 2)
Dovidio et al., 1995
70
51
43
Recall event(s)
Recall event(s)
Candy
Happy/accountable/no
stereotype activated
vs. neutral/not
accountable/stereotype
activated
Neutral vs. sad
Neutral vs. sad
Positive vs. neutral
Elsbach & Barr, 1999
120
Erez & Isen, 2002 (Study 1)
Erez & Isen, 2002 (Study 1)
Erez & Isen, 2002 (Study 1)
Estrada et al., 1994
Estrada et al., 1997
Estrada et al., 1997
Forgas, 1989
97
97
97
44
29
29
72
Candy vs. difficult
anagram problems
Candy
Candy
Candy
Candy
Candy
Candy
False feedback
Forgas, 1989
72
False feedback
Isen et al., 1985 (Study 1)
29
Isen & Daubman, 1984 (Study 1)
162
Word associations to
affectively valenced
words
Gift
Isen & Daubman, 1984 (Study 2)
162
Video clip(s)
Positive vs. control
Isen & Daubman, 1984 (Study 3)
74
Gift
Positive vs. control
Isen & Means, 1983
22
False feedback
Positive vs. control
Isen & Means, 1983
22
False feedback
Positive vs. control
Isen & Means, 1983
Kahn & Isen, 1993 (Study 1)
Kahn & Isen, 1993 (Study 2)
Kahn & Isen, 1993 (Study 3)
Kavanagh, 1987
Kavanagh, 1987
Mackie & Worth, 1989 (Study 1)
22
69
54
45
85
85
215
False feedback
Gift
Gift
Gift
Recall event(s)
Recall event(s)
False feedback
Mackie & Worth, 1989 (Study 2)
260
Video clip(s)
Positive vs. control
Positive vs. control
Positive vs. control
Positive vs. control
Positive vs. negative
Positive vs. negative
Positive/limited viewing
of Argument vs.
remaining conditions
Positive vs. neutral
Positive vs. negative
Positive vs. neutral
Positive vs. neutral
Positive vs. neutral
Positive vs. control
Positive vs. control
Positive vs. control
Positive vs. negative
Positive/personal
relevance vs.
negative/impersonal
relevance
Positive vs. neutral
Positive vs. control
Originality
Judgment accuracy
Judgment accuracy
Use of efficient strategy on coding
task
Reliance on preexisting general
knowledge structures
Reliance on preexisting general
knowledge structures
Reliance on preexisting general
knowledge structures
Avoiding stereotypic judgments
⫺.31
.83
.63
.22
Anchoring bias
Anchoring bias
Making more inclusive group
representations
Careful execution of steps in
highly structured task
Performance on anagram task
Motivation
Time spent on anagram task
Creativity
Time before diagnosis considered
Anchoring bias
Speed and efficiency in reaching
decision
Decision-making efficiency
⫺.24
⫺.27
.39
.26
.31
.31
.21
⫺.33
.21
.30
.33
.33
⫺.48
⫺.40
.32
.43
No. of unusual word associations
.48
Tendency to group items as
belonging together
Tendency to group items as
belonging together
Tendency to group items as
belonging together
Propensity to return to alreadyreviewed information
Pieces of information considered
during decision making
Time to complete mental task
Variety seeking
Variety seeking
Variety seeking
Performance on anagram task
Time spent on anagram task
Differentiation of strong vs. weak
arguments
.23
.29
.40
⫺.51
⫺.26
⫺.43
.31
.31
.23
.32
.34
⫺.18
Differentiation of strong vs. weak
⫺.15
arguments
(table continues)
LYUBOMIRSKY, KING, AND DIENER
820
Table 3 (continued )
Study
n
Affect induction
Comparison groups
Dependent variable
Effect size
(r)
Creativitity and problem solving (continued)
Melton, 1995
Reed & Aspinwall, 1998
57
66
Cartoon(s)
Survey
Humor vs. control
Positive vs. control
Reed & Aspinwall, 1998
66
Survey
Positive vs. control
Sinclair & Mark, 1995 (Study 1)
39
Velten
Sinclair & Mark, 1995 (Study 2)
83
Velten
Positive vs. negative
and neutral
Positive vs. negative
Trope & Pomerantz, 1998 (Study 3)
68
False feedback
Positive vs. negative
Urada & Miller, 2000 (Study 1)
43
Recall event(s)
Positive vs. neutral
Urada & Miller, 2000 (Study 4)
61
Recall event(s), music,
candy
Positive vs. neutral
Note.
Performance on syllogisms
No. of facts ignored about caffeine
and fibrocystic breast disease
Recall of disconfirming
information about caffeine and
fibrocystic breast disease
Accuracy of correlational
judgments
Accuracy of correlational
judgments
Interest in receiving feedback
regarding liabilities vs. assets
Using broad definition of group
membership
Using broad definition of group
membership
⫺.43
⫺.22
.28
.43
.25
.35
.30
.25
Subscript a indicates that the study appears in more than one section or table.
to the frequent experience of positive emotions. In our theoretical
framework, it is the experience of positive emotions that leads to
the behavioral outcomes we review, and “happiness” describes
people who experience such emotions a large percentage of the
time (Diener, Sandvik, & Pavot, 1991). Although more inclusive
definitions of happiness have been offered by others (e.g., Veenhoven, 1984), we restrict our definition to the experience of
frequent positive affect because that definition encompasses the
findings we review.
The notion that frequent positive affect is the hallmark of
happiness has strong empirical support. Diener and his colleagues (1991) found that the relative proportion of time that
people felt positive relative to negative emotions was a good
predictor of self-reports of happiness, whereas the intensity of
emotions was a weaker predictor. That is, happy people feel
mild or moderate positive affect the majority of the time; they
do not appear to experience frequent intense positive states. In
several studies and using a variety of happiness measures,
Diener and his colleagues found that happy people experienced
positive moods and emotions most of the time (see also Diener,
Larsen, Levine, & Emmons, 1985). Indeed, people who report
high levels of happiness appear to have predominantly positive
affect—that is, stronger positive feelings than negative ones—
80% or more of the time. For example, in a large international
sample of more than 7,000 college students in 41 diverse
nations collected by Diener’s laboratory, individuals who reported that they were pleased with their lives expressed feelings
of joy over half of the time.
In the World Value Survey I, which comprises probability
samples of almost 60,000 adults in 41 nations, 64% of the respondents reported more positive than negative affect, with only 18%
reporting more negative than positive affect (World Value Survey
Group, 1994). Notably, of those reporting above-neutral happiness
on this survey, nearly everyone reported more positive than negative affect, prompting Diener et al. (1991) to conclude that
happiness is best regarded as a state in which people feel a
preponderance of positive emotions most of the time. One reason
for the tendency of happy people to feel positive emotions more
frequently may be that the chronically happy are relatively more
sensitive to rewards in their environment—that is, they have a
more reactive behavioral approach system (Gray, 1994)—and are
more likely to approach, rather than avoid, rewarding situations
(Watson, 1988). In addition, Larsen and colleagues demonstrated
that dispositional positive affectivity involves a susceptibility to
experience positive moods (Larsen & Ketelaar, 1991; Rusting &
Larsen, 1997).
Characterizing and Measuring High Average Positive
Affect
In short, the research evidence supports the notion that it is the
amount of time that people experience positive affect that defines
happiness, not necessarily the intensity of that affect. Furthermore,
happy people have been found to experience positive emotions the
majority of the time. Thus, in this article, we identify happy individuals as those who experience high average levels of positive affect.
These high average levels of positive affect, which we variously refer
to as chronic happiness, trait PA, or subjective well-being, may be
rooted in personality predispositions (e.g., a genetically determined
“set point”; Lyubomirsky, Sheldon, & Schkade, 2005), the person’s
current life circumstances, the person’s intentional activities, or all of
these. Because the existing literature does not discriminate which
effects of long-term PA come from which of these different sources,
we refer in our article to individuals who show high average level of
PA, without reference to the source of this state. However, the
findings from the experimental studies suggest that positive emotions
can produce desirable outcomes even in the absence of a very happy
disposition, although a happy disposition is likely to be a cause of
positive emotions.
The research we cite uses a variety of measures of long-term
PA, happiness, and well-being. The vast majority of assessment of
chronic PA is by self-report measures, which have been validated
BENEFITS OF FREQUENT POSITIVE AFFECT
821
Table 4
Measures of Central Tendency and Dispersion for Effect Sizes by Category
Mean of effect sizes
Category
n
Sampling
units
Unweighted
Weighted
Median of effect sizes
Unweighted
Weighted
2 test of
heterogeneity
Cross-sectional data
Work life
Social relationships
Health
Positive
perceptions of
self and others
Sociability and
activity
Likeability and
cooperation
Prosocial behavior
Physical well-being
and coping
Creativity and
problem solving
19
22
19
16
34,794
120,256
17,693
2,821
.27
.27
.32
.39
.20
.15
.32
.42
.29
.23
.31
.37
.20
.07
.31
.39
188.82****
3,079.60****
67.98****
59.36****
26
11,773
.33
.37
.32
.40
116.20****
15
6,930
.32
.34
.29
.21
217.64****
7
25
2,097
5,093
.32
.29
.35
.31
.32
.31
.36
.35
11.45
197.32****
10
2,275
.26
.24
.27
.28
18.25*
Longitudinal data
Work life
Social relationships
Health
Positive
perceptions of
self and others
Sociability and
activity
Creativity and
prosocial
behavior
Physical well-being
and coping
11
8
26
1
15,080
5,106
37,421
100
.24
.21
.18
.25
.05
.19
.09
N/A
.25
.20
.14
.25
.03
.20
.09
N/A
621.63****
30.43****
418.90****
N/A
4
1,117
.25
.29
.24
.33
4.66
2
2,872
.18
.06
.18
.04
55.67****
10
2,999
.27
.15
.29
.14
80.98****
Experimental data
Positive
perceptions of
self and others
Sociability and
activity
Negotiation and
conflict
resolution
Prosocial behavior
Physical well-being
and coping
Creativity and
problem solving
* p ⬍ .05.
** p ⬍ .01.
13
900
.36
.34
.36
.33
19.66
6
579
.51
.49
.52
.56
16.30**
8
574
.33
.29
.31
.27
4.15
17
14
1,170
749
.43
.38
.37
.34
.36
.40
.34
.28
26.53*
18.79
34
2,707
.25
.16
.30
.25
193.63****
*** p ⬍ .001.
**** p ⬍ .0001.
in a number of studies (e.g., Sandvik, Diener, & Seidlitz, 1993;
Watson, 2000). In experimental research on induced moods, positive moods are operationalized by the manipulations that induce
them; in longitudinal research, the measures depend on moods at
the moment or over a recent period such as the past week or
month; and, in individual difference research on chronic positive
emotions, the measures usually ask about the person’s moods in
general. Although these methods are not without shortcomings,
they appear to be at least moderately valid. A more detailed
discussion of measurement issues is available elsewhere (see Diener, 1994; Diener et al., 1999; Sandvik et al., 1993).
Discriminating Happiness and Positive Affect From
Related Constructs
Notably, a large number of studies have assessed life satisfaction as an indicator of well-being, and such investigations are
occasionally included here. Although the construct of satisfaction
822
LYUBOMIRSKY, KING, AND DIENER
is not identical to positive affect—some researchers argue that it
has an affective dimension (Veenhoven, 1997), whereas others
define it as a purely cognitive judgment of life or its facets (Diener
et al., 1999)—we review studies of satisfaction because they
frequently represent the only available evidence in an area. Furthermore, life satisfaction and positive affect have been found to
correlate at around .40 to .50 in undergraduates (Lucas, Diener, &
Suh, 1996) and .52 in business students (Staw & Barsade, 1993).
In addition, of people who say they are above neutral in satisfaction with their lives, 85% have been found to report that they feel
happy at least half of the time (Lucas et al., 1996). Thus, life
satisfaction is a defensible proxy for chronic happiness, in cases in
which no studies exist using more direct measures of happiness;
Lucas and his colleagues demonstrated that it is separable but not
independent from chronic PA. Similarly, Lucas et al. found that
optimism is also related to positive affectivity, but separable from
it. Again, we sometimes refer to findings based on measures of
optimism because the findings can be striking, but we eagerly
await the day when a full set of findings based on measures of
positive affect, as well as related concepts, is available.
The sections of this article that address research on positive
affect similarly include studies using a variety of affect measures
and mood inductions. Most researchers focus on global pleasant
affect, without discriminating among specific positive emotions or
between emotions and moods, and our review reflects this characteristic of the field. Finally, when no research on positive affect
is available, we infrequently cite the literature on negative affect or
depression. Although positive affect and negative affect often
exhibit a degree of independence in the long run (e.g., Diener,
Smith, & Fujita, 1995), these two types of affect regularly show
moderate inverse relations across individuals, justifying the use of
such negative states as the inverse of PA or subjective well-being,
to address our questions when more direct measures are absent.
Furthermore, depression has been defined not only by high levels
of negative affect, but also low levels of PA (Watson & Clark,
1995).
CROSS-SECTIONAL EVIDENCE
Question 1: Are Happy People Successful People?
Being successful means accomplishing those things that are
valued by one’s culture, flourishing in terms of the goals set forth
by one’s society. Hence, our focal question is whether happy
people on average are better able to achieve the values and goals
they have been socialized to believe are worthwhile. As Sigmund
Freud reportedly once said, lieben und arbeiten—to love and to
work—are what a “normal” person should be able to perform well.
Few people would oppose, in any culture, the addition of health to
love and work as a critical ingredient to a successful life.
Accordingly, the following section is divided into three parts:
work life, social relationships, and health. Specifically, in this
section, we review the cross-sectional evidence addressing the
question of whether happy people are relatively more successful in
various life domains, ranging from marriage to work, from altruistic community involvement to making money, and from mental
health to physical health and longevity.
Work Life
In modern Western society, work fills a large number of people’s waking hours. Furthermore, it is important in terms of producing income, influencing self-esteem, creating opportunities for
meaningful activities, and producing the goods and services
needed by society. Thus, work is highly valued. Are happy people
more successful than their less happy peers on job-related and
performance variables? We will first review the correlational evidence bearing on this question (for study information and effect
sizes, see Panel 1 of Table 1).
Employment and Quality of Work
The cross-sectional evidence reveals that happy workers enjoy
multiple advantages over their less happy peers. Individuals high
in subjective well-being are more likely to secure job interviews,
to be evaluated more positively by supervisors once they obtain a
job, to show superior performance and productivity, and to handle
managerial jobs better. They are also less likely to show counterproductive workplace behavior and job burnout.
Even before entering the workforce, people with high subjective
well-being are more likely to graduate from college (Frisch et al.,
2004). Furthermore, happy individuals appear to secure “better”
jobs. In one study, employees high in dispositional positive affect
had jobs, as rated by trained observers, that had more autonomy,
meaning, and variety (Staw, Sutton, & Pelled, 1994). Finally,
evidence from a variety of sources shows that happy people are
more satisfied with their jobs (e.g., Connolly & Viswesvaran,
2000; Tait, Padgett, & Baldwin, 1989; Weiss, Nicholas, & Daus,
1999). In a meta-analysis of 27 studies of affect and job satisfaction, Connolly and Viswesvaran concluded that 10%–25% of the
variance in job satisfaction was accounted for by measures of
dispositional affect. In their analyses, the mean corrected correlation between positive affect and job satisfaction was .49.
Once a happy person obtains a job, he or she is more likely to
succeed. Employees high in dispositional positive affect receive
relatively more favorable evaluations from supervisors and others
(Staw et al., 1994). For example, in Staw and colleagues’ study,
managers of high positive affect employees of three Midwestern
organizations gave them higher evaluations for work quality, productivity, dependability, and creativity. Wright and his colleagues
have replicated this effect, showing that happy people receive
higher ratings from supervisors (Cropanzano & Wright, 1999;
Wright & Staw, 1999). Finally, work performance may be more
strongly predicted by well-being than by job satisfaction. In two
studies, Wright and Cropanzano (2000) found that job performance, as judged by supervisors, was significantly correlated with
well-being (rs of .32 and .34, respectively), but uncorrelated with
measures of job satisfaction (rs of ⫺.08 and .08, respectively).
Staw and Barsade (1993) found that, as rated by objective
observers, those high in dispositional positive affect performed
objectively better on a manager assessment task (including leadership and mastery of information). Other evidence for happy
people’s relative success on the job includes findings that individuals high in dispositional positive affect are more likely to be in the
supervisory in-group (Graen, 1976). Dormitory resident advisors
were rated by residents as being more effective if they were high
on trait positive affect (DeLuga & Mason, 2000), and happier
BENEFITS OF FREQUENT POSITIVE AFFECT
cricket players had higher batting averages (Totterdell, 2000).
George (1995) found that service departments with happy leaders
were more likely to receive high ratings from customers, and that
the positive affective tone of the sales force was an independent
predictor of customer satisfaction. Corroborating these results, a
recent study showed that CEOs of manufacturing companies with
high positive affect were relatively more likely to have employees
who rated themselves as happy and healthy, and who reported a
positive, warm climate for performance. In turn, organizational
climate was correlated with productivity (r ⫽ .31) and profitability
(r ⫽ .36; Foster, Hebl, West, & Dawson, 2004). Of interest, these
patterns were not found for negative affect. Finally, optimistic life
insurance agents appear to sell more insurance (Seligman & Schulman, 1986), and optimistic CEOs receive higher performance
ratings from the chairpersons of their boards and head companies
with greater returns on investment (Pritzker, 2002). Coté (1999)
reviewed the effects of well-being on job performance, and concluded that the causal relation between pleasant affect and strong
performance is bidirectional.
Undoubtedly, one of the reasons that happy, satisfied workers
are more likely to be high performers on the job is that they are less
likely to show “job withdrawal”—namely, absenteeism, turnover,
job burnout, and retaliatory behaviors (Donovan, 2000; Locke,
1975; Porter & Steers, 1973; Thoresen, Kaplan, Barsky, Warren, &
de Chermont, 2003). For example, positive moods at work predicted lower withdrawal and organizational retaliation and higher
organizational citizenship behavior (Donovan, 2000; see also
Credé, Chernyshenko, Stark, & Dalal, 2005; Miles, Borman, Spector, & Fox, 2002; Thoresen et al., 2003), as well as lower job
burnout (Wright & Cropanzano, 1998). Positive affect at work has
also been found to be directly associated with reduced absenteeism
(George, 1989). Finally, those who experience low arousal positive
affect on the job are less likely to want to quit and to be in conflict
with other workers (Van Katwyk, Fox, Spector, & Kelloway,
2000).
823
comes from studies of individuals who are satisfied with their jobs.
Notably, both positive affect on the job and chronic happiness have
been found to predict job satisfaction (Weiss et al., 1999). In turn,
job satisfaction predicts organizational citizenship behavior—that
is, acts that go beyond the requirements of the job, such as
spreading goodwill and aiding coworkers (Donovan, 2000; George
& Brief, 1992; Organ, 1988). However, studies of recurring positive affect corroborate these results. Borman, Penner, Allen, and
Motowildo (2001) reviewed evidence showing that positive affect
predicts organizational citizenship, and that negative affect inversely correlates with it, even when peer ratings rather than
self-ratings of citizenship are used. In addition, George and Brief
argued that habitual positive affect at work is pivotal in understanding so-called “organizational spontaneity,” which includes
helping coworkers, protecting the organization, making constructive suggestions, and developing one’s own abilities within the
organization (see also Donovan, 2000).
Community Involvement
Despite a scarcity of studies in this area, some evidence underscores the contributions of happy people to their communities.
Happy people appear to volunteer at higher levels than their
unhappy peers for charity and community service groups, including religious, political, educational, and health-related organizations (Krueger, Hicks, & McGue, 2001; Thoits & Hewitt, 2001)
and to invest more hours in volunteer service (Thoits & Hewitt,
2001). Furthermore, in a study of Israeli high school students,
those with high positive affect were more likely to be involved in
community service and to express a desire to contribute to society
and be of assistance to others (Magen & Aharoni, 1991). In
summary, as we describe in the section on prosocial behavior,
happy people seem to be relatively more inclined to help others
(Feingold, 1983).
Social Relationships
Income
An important indicator of success in modern societies is income.
Do happier people earn higher incomes? Several studies suggest
the answer to be yes. For example, a study of 24,000 German
residents revealed a correlation between income and life satisfaction of .20 (Lucas, Clark, Georgellis, & Diener, 2004), and a study
of Russians revealed correlations between real household income
and happiness of .48 in 1995 and .39 in 2000 (Graham, Eggers &
Sukhtankar, in press). Among indigenous Malaysian farmers, the
correlation between life satisfaction and material wealth (their only
available indicator of income) was found to be .23 (Howell,
Howell, & Schwabe, in press). According to Diener and BiswasDiener (2002), most surveys report correlations between income
and happiness in the range of .13–.24. In a meta-analysis of 286
empirical investigations of older adults, income was significantly
correlated with happiness and life satisfaction, and, surprisingly,
more so than with education (Pinquart & Sörensen, 2000).
Organizational Citizenship
Are happy workers relatively better organizational “citizens”?
Much of the cross-sectional evidence pertaining to this question
Berscheid (2003) highlighted the centrality of social relationships to successful human functioning when she wrote that “relationships constitute the single most important factor responsible
for the survival of homo sapiens” (p. 39). Do happy people have
better social relationships than their less happy peers? Our review
reveals this to be one of the most robust findings in the literature
on well-being. Next, we begin by presenting cross-sectional evidence regarding the question whether individuals high in trait
positive affect, happiness, and life satisfaction have more friends
and more social support, as well as experience happier interpersonal relationships. Relevant study information is contained in
Panel 2 of Table 1.
Friendship and Social Support
Do happy people have more friends and stronger social support
networks than less happy people? Cross-sectional studies have
documented an association between chronic happiness and the
actual number of friends or companions people report they can rely
on (Baldassare, Rosenfield, & Rook, 1984; Lee & Ishii-Kuntz,
1987; Mishra, 1992; Phillips, 1967; Requena, 1995), as well as
overall social support and perceived companionship (Baldassare et
LYUBOMIRSKY, KING, AND DIENER
824
al., 1984; see Pinquart & Sörensen, 2000, for a large metaanalysis). In the workplace, employees with high dispositional
positive affect have been found to receive more emotional and
tangible assistance from both coworkers and supervisors (Staw et
al., 1994).
Friendship has been found to have one of the highest positive
correlations with self-rated happiness (Campbell, Converse, &
Rogers, 1976). For example, the happiest college students (the top
10%) have been shown to have high-quality social relationships
(Diener & Seligman, 2002). In a meta-analysis of 286 studies, the
quantity and quality of contacts with friends was a strong predictor
of well-being, even stronger than that of contacts with family
members (Pinquart & Sörensen, 2000). Happy people also report
being more satisfied with their friends and their social activities
(Cooper, Okamura, & Gurka, 1992; Gladow & Ray, 1986; Lyubomirsky, Tkach, & DiMatteo, in press) and less jealous of others
(Pfeiffer & Wong, 1989). Not surprisingly, loneliness is negatively
correlated with happiness, especially in older adults (Lee & IshiiKuntz, 1987), and positively correlated with depression (Peplau &
Perlman, 1982; Seligman, 1991).
Marriage and Romance
More than 9 in 10 people worldwide eventually get married
(Myers, 2000), and an even greater percentage are in committed
intimate relationships. Surveys show that married people are happier than those who are single, divorced, or widowed (Diener et al.,
1999). For example, in a study of 19 countries, Mastekaasa (1994)
found that married people were happier than all of the other
groups. Numerous studies with respondents from diverse cultures
support this finding (e.g., Diener, Gohm, Suh, & Oishi, 2000;
Glenn & Weaver, 1979; Graham et al., in press; Kozma & Stones,
1983; Lee, Seccombe, & Shehan, 1991; Marks & Fleming, 1999;
Stack & Eshleman, 1998). Happy individuals tend to have fulfilling marriages and to be more satisfied with their marriages. Indeed, several writers have suggested that satisfaction with marriage and family life is the strongest correlate of happiness
(Headey, Veenhoven, & Wearing, 1991; Myers, 1992, 2000). For
example, data from six U.S. national surveys indicate that marital
happiness is more strongly related to global, personal happiness
than any other kind of domain satisfaction (Glenn & Weaver,
1981). Individual happiness is even associated with high marital
satisfaction in one’s spouse (Ruvolo, 1998).
The findings on marriage generalize to other romantic relationships. Undergraduates high in trait positive affect are more likely
than those low in trait positive affect to describe their current
romantic relationship as being of higher quality (Berry & Willingham, 1997), and happy people who are either married or in
committed relationships are more likely to describe their partner as
being their “great love” than their less happy peers (Willi, 1997).
Health
“A merry heart doeth good like a medicine: but a broken spirit drieth
the bones.”
—Proverbs 17:22
Are happier people healthier in general? In this section, we
review the cross-sectional evidence addressing the question
whether happiness is associated with superior mental and physical
health (see Table 1, Panel 3). Because only longitudinal studies
can address whether happy individuals have higher odds of survival and longevity, these studies are reviewed in the section
discussing the longitudinal literature. For a more detailed review,
focusing entirely on the relations between positive affect and
physical health, see Pressman and Cohen (2005).
Mental Health
Because positive affective experience has been described as an
important component of mental health (e.g., Jahoda, 1958; Taylor
& Brown, 1988), it would not be surprising to find that happy
individuals are more mentally healthy than their less happy peers.
Diener and Seligman (2002) reported that their happiest group of
people had few symptoms of psychopathology, such as depression,
hypochondriasis, or schizophrenia (see also Chang & Farrehi,
2001; Lu & Shih, 1997; Phillips, 1967). As the absence of positive
affect has been argued to be a distinguishing characteristic of
depression (L. A. Clark, Watson, & Mineka, 1994; Watson &
Clark, 1995), individuals high in trait positive affect are, of course,
less likely to suffer from this debilitating condition (e.g., Lyubomirsky et al., 2005), as well as from social phobia or anxiety
(Kashdan & Roberts, 2004). Parallel findings are observed when a
construct closely related to happiness— optimism—is examined.
Dispositional optimism has been shown, for example, to relate to
higher levels of self-reported vitality and mental health (Achat,
Kawachi, Spiro, DeMolles, & Sparrow, 2000) and lower levels of
depression (e.g., Chang & Farrehi, 2001).
Substance abuse is another indicator of poor mental health.
Although positive affect is clearly an initial outcome of engaging
in some potentially detrimental behaviors (i.e., individuals may
smoke or consume drugs to feel good), evidence suggests that
positive mood is related to a lower probability of drug use. Thus,
not surprisingly, happy individuals are less likely to report a
history of substance abuse (Bogner, Corrigan, Mysiw, Clinchot, &
Fugate, 2001). Furthermore, lowered positive affect is associated
with delinquent activity in adolescents (Windle, 2000).
Physical Health
According to the cross-sectional data, do happy people show
superior physical health? Unfortunately, direct, non–self-report
evidence is limited. Not surprisingly, happy people self-report
better health and fewer unpleasant physical symptoms (Kehn,
1995; Lyubomirsky et al., in press; Mroczek & Spiro, 2005;
Røysamb, Tambs, Reichborn-Kjennerud, Neale, & Harris, 2003).
Positive affect has been shown to relate to quality of life in cancer
patients over the course of their illnesses (Collins, Hanson, Mulhern, & Padberg, 1992) and to smaller allergic reactions among
healthy students (Laidlaw, Booth, & Large, 1996). In a study of
individuals with sickle cell disease, positive mood was associated
with fewer emergency room and hospital visits, fewer calls to the
doctor, less medication use, and fewer work absences (Gil et al.,
2004). In addition, those patients with positive moods were relatively less likely to report pain on the same day and 2 days later
(Gil et al., 2004). The number of days of work missed because of
health problems was also related to happiness in a large Russian
study (Graham et al., in press).
BENEFITS OF FREQUENT POSITIVE AFFECT
Finally, studies using variables correlated with subjective wellbeing show similar results. Optimism predicted less pain in a
sample of aging veterans (Achat et al., 2000), even after controlling for such variables as age, body mass index, and chronic health
conditions; optimistic women were less likely to deliver low-birth
weight infants (Lobel, DeVincent, Kaminer, & Meyer, 2000).
2.
sociability and activity,
3.
likability and cooperation,
4.
prosocial behavior,
5.
physical well-being and coping, and
Summary
6.
problem solving and creativity.
In summary, our review of the cross-sectional empirical literature suggests that happiness is positively correlated with indicators
of superior mental and physical health. Happiness, as well as the
concomitant experience of frequent positive affect, likely plays a
role in health through its effects on social relationships, healthy
behavior, stress, accident and suicide rates, and coping, as well as
possible effects on immune function. These variables are discussed
in the next section.
Conclusion
Are happy people better off? Although the research in some
areas is limited, our examination of the cross-sectional correlational literature thus far suggests that high subjective well-being is
related to positive outcomes in many areas of life. Specifically, as
displayed in the first three panels of Table 1 and on the top of
Table 4, happy people appear to be more successful than their less
happy peers in the three primary life domains: work (mean r ⫽
.27),1 relationships (mean r ⫽ .27), and health (mean r ⫽ .32).
Question 2: Are Long-Term Happiness and Short-Term
Positive Affect Associated With Behaviors Paralleling
Success?
The effect sizes presented in Tables 1 and 4 indicate robust
associations between happiness and desirable life outcomes. Is this
because successes bolster happiness, or the reverse? In this section,
we pull together evidence consistent with the argument that it is
happiness that promotes success, in part because happy individuals
show numerous adaptive characteristics. That is, we turn to examining whether happy people are relatively more likely to exhibit
behaviors and thoughts that parallel culturally valued success and
thriving—that is, the attributes, resources, and skills that help
people thrive and succeed.
Earlier, we reviewed evidence showing that the key indicator of
happiness is the experience of frequent positive emotions. Hence,
it is also important to investigate whether positive emotions and
moods are associated with desirable characteristics. We anticipate
that the correlations involving long-term happiness will be parallel
to those of short-term positive moods.
In summary, when the relevant data are available, we document
the characteristics that cooccur with happiness and PA. In conducting this review of the literature, we attempted to find as many
empirical investigations as possible that included measures of
happiness and positive affect and at least one other valenced
construct. The resulting collection of articles yielded six categories
of studies reporting significant correlates of long-term happiness
and short-term PA:
Each category is discussed in detail in the following sections,
and relevant study information is presented in the last six panels
(Panels 4 –9) of Table 1. Effect sizes appear in Tables 1 and 4.
Positive Perceptions of Self and Others
Self-Perceptions
Are self-nominated chronically happy people inclined to evaluate themselves and their futures in positive ways? It appears that
happy people are characterized by high personal competence and
self-esteem (Campbell et al., 1976; Kozma & Stones, 1978; Lyubomirsky et al., 2005; Scheufele & Shah, 2000; Schimmack,
Oishi, Furr, & Funder, 2004; Tarlow & Haaga, 1996), optimism
(Campbell, 1981; Lyubomirsky et al., in press), and a sense of
personal mastery and control (Csikszentmihalyi & Wong, 1991;
Grob, Stetsenko, Sabatier, Botcheva, & Macek, 1999; Lyubomirsky et al., in press; Ryff, 1989). For example, Lucas and colleagues
(1996) found that life satisfaction was consistently related to
self-esteem and optimism in multimethod assessments in which
one characteristic was measured by self-report and the other was
reported by informants. Happiness is also related to positive perceptions of all life domains. Happy and contented individuals have
been found to be satisfied with their family life, their romantic
relationships and their friends, their health, their education and
their jobs, their leisure activities, and even their housing and
transportation (e.g., Lyubomirsky et al., in press; Weiss et al.,
1999). Are the correlational findings regarding short-term positive
affect parallel to those for long-term happiness? The few correlational studies in this area examining happy moods suggest that PA
is also associated with relatively more positive self-perceptions.
For example, in a correlational study, higher levels of positive
affect were related to being less self-critical (Mongrain & Zuroff,
1995). Furthermore, participants in a naturally occurring good
mood set higher goals for themselves and reported more selfefficacy on a laboratory clerical task (Jundt & Hinsz, 2001), and
cricket players judged their performances more favorably (Totterdell, 2000).
Perceptions, Memories, and Judgments of Others
Chronically happy individuals have also been shown to have a
more positive attitude toward others. For example, in one study,
participants interacted with a female confederate in the laboratory,
then viewed a series of videotapes depicting an unfamiliar student
in various situations (Lyubomirsky & Tucker, 1998). Relative to
their unhappy peers, happy participants recalled the person they
1
1.
positive perceptions of self and others,
825
Mean rs cited within the text are all unweighted by sample size, as our
goal was to generalize across studies, not across individuals.
LYUBOMIRSKY, KING, AND DIENER
826
met in more favorable terms—for example, as kind, self-assured,
open, tolerant, and warm—and reported wanting to be friends with
her and to be her partner in a class project. Happy participants also
liked the person they saw on videotape more than did unhappy
ones. Berry and Hansen (1996) found that when participants were
“accidentally” left alone with a fellow student, those high in trait
PA liked their partner more than those low in trait PA. In another
study, happy faculty were found to write relatively more favorable
letters of recommendation, and happy undergraduates wrote relatively more positive recommendations for hypothetical employees
(Judge & Higgins, 1998). Finally, college women who were generally happy were less likely to be hostile toward other women
than women who were less happy (Cowan, Neighbors, DeLaMoreaux, & Behnke, 1998).
Happy people also feel more positive than their unhappy peers
toward the people that they know. They judge their friends,
spouses, and families more favorably (Cooper et al., 1992; Gladow
& Ray, 1986; Glenn & Weaver, 1981; Lyubomirsky et al., in
press), and are less jealous of other people competing for their
partner’s affections (Pfeiffer & Wong, 1989). However, we found
only one correlational study examining whether short-term PA is
also associated with greater liking and fondness for others. In this
investigation, happy moods were found to be associated with
positively toned inferences and attributions (Mayer, Mamberg, &
Volanth, 1988). For example, after reading a fictitious biography
of “Jim,” students who had relatively higher positive affect were
more likely to agree with positive inferences from the narrative
(e.g., “Jim is interesting”) and less likely to agree with negative
inferences (e.g., “Jim will get divorced”; Mayer et al., 1988).
Sociability and Activity
Do happy people tend to be social and active people? In this
section, we review the cross-sectional literature examining
whether chronically happy people are relatively more likely to
participate in a variety of social and physical activities, to enjoy
their leisure time, and to experience more energy and “flow”
(Csikszentmihalyi, 1999).
Sociability and Extraversion
The literature on the relations of happiness with sociability and
extraversion suggests that happy individuals have outgoing, extraverted personalities. Extraverts are warm, gregarious, sociable,
assertive, interested in new things, affiliative, lively, active, and
energetic (see Lucas, 2001, for a review). Extraversion has been
found to be related to happiness, chronic PA, and life satisfaction
in many investigations—among both undergraduates and old people, in questionnaire studies and in diary studies, and across many
nations (e.g., Brebner, Donaldson, Kirby, & Ward, 1995; Diener &
Seligman, 2002; Lucas, Diener, Grob, Suh, & Shao, 2000; Lyubomirsky et al., in press). Indeed, the findings of a meta-analysis
revealed that, of the most widely researched personality traits, the
highest average correlation with happiness was affiliation, the
inclination to relate to other people (DeNeve & Cooper, 1998). It
is noteworthy that Lucas and colleagues (2000) showed that positive affectivity is the “glue” holding together various aspects of
extraversion such as ascendance, sociability, and affiliation.
Cross-sectional studies have shown that levels of positive affect
are also positively correlated with measures of extraversion and
sociability (Costa & McCrae, 1980; Griffin, Mroczek, & Spiro, in
press; Headey & Wearing, 1989). For example, in one experience
sampling study, high school students from the United States and
Italy were beeped several times a day over the course of a week
(Csikszentmihalyi & Wong, 1991). Positive affect reported during
any particular time of day was related to feeling sociable. Harker
and Keltner (2001) found that women who expressed positive
affect in their college photos were more likely to describe themselves as high in affiliation—that is, as warm, cheerful, pleasant,
sociable, understanding, contented, and affectionate—and were
more likely to be described as such by observers.
Social Interaction, Activity, and Energy
The empirical evidence suggests that individuals high in trait
positive affect, happiness, or satisfaction tend to be more social,
active, and energetic. Cross-sectional investigations reveal that
happy and satisfied people report engaging in a greater frequency
of activities, in general (Burger & Caldwell, 2000; Matikka &
Ojanen, in press; Mishra, 1992; Veenhoven, 1994; Watson, Clark,
McIntyre, & Hamaker, 1992), and in social interactions (Gladow
& Ray, 1986; Lucas, 2001; Watson, 1988) and group leisure
activities, in particular (Mishra, 1992). Relative to their less happy
peers, happy individuals also report having stronger social support
(Matikka & Ojanen, in press), attending club meetings more frequently (Bahr & Harvey, 1980; Lebo, 1953), and holding more
organizational affiliations (Bahr & Harvey, 1980; Mishra, 1992).
This flurry of activity does not appear to go unnoticed. Happier
individuals are more likely to be rated as energetic and active by
their families and friends (Diener & Fujita, 1995; Schimmack et
al., 2004).
Okun and colleagues meta-analyzed 556 sources to determine
the relation between happiness and the frequency of social activities (both formal and informal) in older adults (Okun, Stock,
Haring, & Witter, 1984). A positive significant association was
found, regardless of type of activity (e.g., having to do with
voluntary organizations vs. friends) or activity partner (e.g.,
friends vs. neighbors). Furthermore, in a study of men and women
over 60 years old, happiness was related to a desire to learn a new
skill or take a class, an expressed need for a larger number of
cultural and educational activities in their community, and being
informed about politics (Lebo, 1953). Thus, happier people appear
to be not only more social and more active, but also more interested and more informed.
In summary, individuals high in happiness or trait PA appear to
be more likely to approach rewarding activities, especially social
ones, and may even be more sensitive to pleasurable stimuli in
general (such as social interactions or hobbies; Watson, 1988).
Indeed, positive emotionality has been found to relate to approach
goals (Elliot & Thrash, 2002).
What about research relevant to transient mood? The evidence
indicates that positive mood is also related to relatively greater
involvement in activities, more frequent social interactions, and
increased feelings of energy. For example, the results of 2- to
13-week long diary studies reveal that high levels of positive
affect, as reported in daily or weekly logs, are associated with
reports of spending relatively more time socializing with friends,
BENEFITS OF FREQUENT POSITIVE AFFECT
family, or romantic partners (Lucas, 2001; Watson et al., 1992)
and a greater frequency of being engaged in a variety of activities
(e.g., going to a party, a museum, or out for a meal; going shopping
or on a week-end trip; Cameron, 1975; Watson et al., 1992). In an
experience sampling study, positive affect reported during any
particular time of day was related to feeling alert and active, to
being with friends, and to engaging in a variety of leisure activities
(e.g., sports and games, socializing, and arts and hobbies;
Csikszentmihalyi & Wong, 1991; see also Lucas, 2001).
Enjoyment of Activities and Social Interactions
The data suggest that happy people participate in more activities
than their less happy peers. However, do they derive more satisfaction from them? Extensive correlational evidence indicates that,
indeed, happy individuals are more likely to enjoy their leisure
activities and social interactions, to experience more “flow” states,
and to be more satisfied with their activities in general. Lu and
Argyle (1991) found that happy community-dwelling men and
women were more likely to report enjoying leisure activities and
group activities. Happiness has been found to be significantly
related to satisfaction with one’s leisure and recreational activities
among both students and retirees (Kahana et al., 1995; Lyubomirsky et al., in press; Veenhoven, 1994). Laboratory and diary
studies corroborate these findings—that is, happy individuals appear to have more pleasurable and more successful social interactions with others. When female students were left alone in a room
with a peer, those high in trait PA were more satisfied with the
conversation that resulted; liked their partner more; and reported
that their conversation was more enjoyable, pleasant, smooth,
relaxed, and less awkward and forced than those low in trait PA
(Berry & Hansen, 1996). Kashdan and Roberts (2004) described
very similar findings. Furthermore, in a daily diary study, students
high in trait PA reported engaging in more enjoyable social interactions than their low positive affect peers (Berry & Hansen,
1996). Finally, in a study of working adults, global happiness was
found to be associated with intrinsically rewarding experiences—
that is, activities that the individual wants to be doing for their own
sake (Graef, Csikszentmihalyi, & Gianinno, 1983). The authors
speculated that chronically happy people may be able to perceive
any activity— even routine, commonplace situations—as intrinsically motivating, and therefore discover rewards even in ordinary,
mundane events.
Correlational studies of transient positive moods have also
found such moods to be associated with satisfying social interactions. For example, when engaged in an intimacy-building task,
those experiencing positive affect are relatively more likely to feel
closer and more attracted to their partner (Kashdan & Roberts,
2004). Furthermore, positive moods have been linked with the
intrinsically rewarding state called flow. The concept of flow was
introduced by Csikszentmihalyi (1975, 1997), who described it as
an experience so engrossing and enjoyable, it is worth doing for its
own sake. When in flow, people report feeling enraptured, as
though in a different reality, lacking self-consciousness, and lacking a sense of the passage of time. Indeed, transient positive affect
is often accompanied by flow (Hektner, 1997). For example, the
results of experience sampling studies suggest that hour-by-hour
experiences of positive affect are related to reports of being in flow
(Csikszentmihalyi & Wong, 1991; Hektner, 1997).
827
Likability and Cooperation
Likability
Is there truth in the sentiment that happy people are disliked
because they are shallow and annoyingly cheerful? The existing
cross-sectional studies actually show the reverse pattern of results.
That is, most respondents like happy people much more than they
like their less-than-happy peers. Happy and satisfied individuals
are judged as more physically attractive (Diener, Wolsic, & Fujita,
1995; Mathes & Kahn, 1975); more intelligent and competent
(Diener & Fujita, 1995); more friendly, warm, and assertive
(Schimmack et al., 2004); less selfish (Rimland, 1982); more
moral; and even more likely to go to heaven (King & Napa, 1998).
Diener and Fujita (1995) found that friends and family members of
happy students, relative to those of less happy ones, rated them as
more socially skilled (e.g., more articulate and well mannered),
better public speakers, self-confident, and assertive, and as having
more close friends, a strong romantic relationship, and more family support. These findings were replicated in a recent study, which
found that friends of students relatively high on chronic happiness
evaluated them more favorably relative to their peers on a variety
of attributes and skills, such as academic ability, self-respect,
selfishness, and pretentiousness (Taylor, Lerner, Sherman, Sage, &
McDowell, 2003). Furthermore, happiness in children, as rated by
their teachers, was found to relate to the children’s popularity
(S.-M. Chen, 1980).
In other studies exploring the happiness–likability relation, secondary school and college students read stories about hypothetical
people. Second through eighth graders judged the happiest targets
as the ones most likely to help (Perry, Perry, & Weiss, 1986), and
undergraduates, no matter what mood they themselves were experiencing, judged the happiest targets as being more likable (Bell,
1978). Finally, in laboratory studies, when female students were
left alone with a peer, the partners of the high PA women found the
social interaction to be more enjoyable and of higher quality, and
so did neutral observers of the interaction (Berry & Hansen, 1996);
objective observers rated participants high in dispositional positive
affect as evidencing stronger leadership while performing a management task (Staw & Barsade, 1993).
Happy moods also tend to lead people to appear more appealing
and inviting to possible interaction partners (Veenhoven, 1988).
Support for this assertion comes from an intriguing study by
Harker and Keltner (2001), who rated the positive affect expressed
in yearbook photographs of graduating seniors from a women’s
college. The personalities of the women in the photos were later
judged both by observers (who interacted with them in person
when the women were in their 20s) and by coders (who only
viewed the photos). The observers judged women who had shown
the highest levels of sincere PA (i.e., Duchenne smiles) as relatively higher on the personality dimension of affiliation (e.g.,
generous, considerate, protective of close ones, and capacity for
close relationships) and lower on the dimension of negative emotionality (e.g., not irritable, fearful, or hostile toward others). The
judges, who only had the opportunity to see the photos, inferred
that women with high positive affect were also relatively higher in
affiliation and lower in negative emotionality, as well as being
higher in positive emotionality (e.g., cheerful, sociable, and appreciative of and responsive to humor) and competence (e.g., productive, dependable, and high intellectual capacity). In summary,
LYUBOMIRSKY, KING, AND DIENER
828
women who expressed genuine happiness were liked more than
women who looked less happy. Indeed, the judges of the photos
reported that they expected future hypothetical interactions with
the high positive affect women to be relatively more rewarding.
A study by Kashdan and Roberts (2004) corroborated these
findings. Participants were asked to answer a series of questions
with two peers (actually confederates), such that ever-greater levels of self-disclosure and intimacy were required. The higher the
participants’ levels of PA, the more likely that the confederates felt
themselves interpersonally closer and more attracted to them.
It is worth noting that, although the correlational studies described in this section cannot definitively establish causality, the
causal direction is unlikely to flow solely from likability to happiness. That is, studies in which informants rate hypothetical
targets or fresh acquaintances are unlikely to suggest that the
informants’ high ratings are the cause of the target’s happiness.
Negotiation and Conflict Resolution
Are happy people or those experiencing pleasant moods superior at resolving conflict? The majority of research in this area
involves laboratory experiments, which will be described later. To
our knowledge, the only study to examine conflict resolution in
chronically happy people was an investigation of the CEOs of 62
U.S. companies and their top managers. The results of this study
revealed that work groups whose members were high in average
trait PA were less likely to experience conflict and more likely to
cooperate (Barsade, Ward, Turner, & Sonnenfeld, 2000). Furthermore, a correlational study of PA—also conducted in a work
setting—found that the experience of particular positive emotions
at the office is related to reduced conflict with colleagues (Van
Katwyk et al., 2000).
affect also related to generosity? The few studies in this area
support an affirmative conclusion. For example, according to the
results of experience sampling and diary studies, the percentage of
time spent in a good mood was associated with self-reported
altruism among school-age youths (Csikszentmihalyi, Patton, &
Lucas, 1997) and with amount of time spent helping others among
college undergraduates (Lucas, 2001). An investigation of high
school students found that those who reported having the most
intense positive experiences were relatively more likely to be
involved in community service activities (e.g., volunteering) and
reported more desires to contribute to society and to be of assistance to others (Magen & Aharoni, 1991, also cited previously).
Finally, in a study of preschoolers, those who displayed happy
moods most frequently were also most likely to show empathy
toward others—for example, by providing positive reinforcement
or comfort (Strayer, 1980).
Research with working adults has shown similar effects. For
example, positive affect experienced at work has been related to
intentions to perform behaviors that are beyond the call of duty
(Williams & Shiaw, 1999), even after controlling for such variables as demographics and trait positive affect. Positive moods
experienced at work have also been related to actual prosocial
organizational behavior. Even after controlling for dispositional
affect, positive affect in salespeople predicted more helping of
customers and more customer service, as well as more extrarole
prosocial behavior on the job (George, 1991).
In summary, cross-sectional investigations suggest that happy
people are inclined to be kind and charitable people. Furthermore,
these findings dovetail with the work on links between happiness
and interpersonal relationships. If happy people are more altruistic,
they will be liked more, will profit more from future social
interactions (i.e., through the norm of reciprocity), and will have
stronger and more supportive social networks.
Prosocial Behavior
“The good life, as I conceive it, is a happy life. I do not mean that if
you are good you will be happy; I mean that if you are happy you will
be good.”
—Bertrand Russell
In reviewing the cross-sectional research on prosocial behavior,
we address the question whether happy people, as well as those
experiencing pleasant moods, are inclined to be more altruistic,
generous, and charitable people.
Individuals who score high on happiness or trait PA report in
correlational questionnaire studies a relatively greater interest in
helping people (Feingold, 1983), a tendency to act in a prosocial or
cooperative manner (e.g., as enjoying sharing or helping others;
Rigby & Slee, 1993), and intentions to perform specific altruistic,
courteous, or conscientious behaviors at work (e.g., helping a
colleague with work problems despite one’s own heavy workload;
Williams & Shiaw, 1999). Happy people also report having performed more altruistic acts in the recent past (e.g., shopping for a
sick friend or stopping to help a stranger; Krueger et al., 2001).
Furthermore, in two studies that tracked subjects’ behaviors from
once to seven times a day, students high in trait PA reported
spending a relatively greater percentage of their time helping
others (Lucas, 2001).
Have similar effects been found in cross-sectional investigations
of transient mood—that is, is the day-to-day experience of positive
Physical Well-Being and Coping
The literature on physical well-being, healthy behavior, and
coping has not generally focused on positive affect or positive
experience (for some notable exceptions, see Antonovsky, 1988,
1993; Seligman, 1991; Snyder, 2000). Instead, the overwhelming
majority of research in this area has examined the effects of
hostility, stress, depression, and anxiety (Kubzansky & Kawachi,
2000). Thus, few studies on health have measured well-being,
although some have included assessments of such related constructs as optimism, hope, and sense of humor. Next, we review
the small number of relevant correlational studies available in this
area.
Health Perceptions
Happy people consistently report themselves as healthier. Relative to their less happy peers, happy respondents rate themselves
higher in global health (e.g., Achat et al., 2000; Kehn, 1995;
Lyubomirsky et al., in press; Mroczek & Spiro, 2005; Røysamb et
al., 2003; Stones & Kozma, 1986, as cited previously) and report
higher levels of social and physical functioning (Pinquart & Sörensen, 2000) and lower levels of pain (Achat et al., 2000;
Røysamb et al., 2003, as cited earlier). Additionally, well-being is
related to higher rates of patient compliance, a predictor of good
BENEFITS OF FREQUENT POSITIVE AFFECT
health (DiMatteo, Lepper, & Croghan, 2000). However, because
positive self-report biases could account for these findings, they
must be considered together with other data on the health and
coping abilities of happy people (see next). Furthermore, it is
notable that Watson (2000) reported small but positive correlations
between measures of positive emotionality (extraversion and positive temperament) and injury visits to a university health center
(rs ⫽ .12 and .15)—suggesting, perhaps, one of the downsides of
the active lifestyle of happy folk. In addition, extraversion and
positive temperament were related to more health visits for illness
(rs range from .15 to .17) in two samples. These modest correlations may suggest that extraverts show a “readiness to use services” (Rosenstock & Kirscht, 1979).
Not surprisingly, high positive affect and low negative affect
have also been associated with subjective reports of better health
(Benyamini, Idler, Leventhal, & Leventhal, 2000; Pettit, Kline,
Gencoz, Gencoz, & Joiner, 2001; Sullivan, LaCroix, Russo, &
Walker, 2001) and fewer physical symptoms (Watson, 1988; Weinglert & Rosen, 1995; though Watson & Pennebaker, 1989, found
no relation between PA and symptom reports [rs between –.19 and
.04]). In one investigation, individuals who worked hard to maintain their happy moods reported fewer illnesses (Goldman, Kraemer, & Salovey, 1996).
Healthy Behavior
As delineated previously, research evidence reveals that chronically happy people are relatively more energetic and more involved in a variety of social, recreational, occupational, and physical activities (e.g., Mishra, 1992; Riddick, 1985; Veenhoven,
1994; Watson, 1988; Watson et al., 1992). Happy individuals are
also less likely to engage in a variety of harmful and unhealthy
behaviors, including smoking, unhealthy eating, and abuse of
drugs and alcohol (e.g., Graham et al., in press; Piko, Gibbons,
Luszcynska, & Teközel, 2002). Within the Big Three approach to
personality (L. A. Clark & Watson, 1999), psychoticism and
neuroticism tend to be viewed as most relevant to addictions (e.g.,
Eysenck, 1997), although it is notable that drug addicts tend to
have relatively lower scores on extraversion (see Eysenck, 1997,
for a review). L. A. Clark and Watson (1999) likewise reported
that disinhibition (rather than negative or positive temperament)
tends to be related to drug use, smoking, drinking alcohol, and
positive attitudes about promiscuous sex. Thus, research has
tended to support the notion that, to the extent that positive
emotionality is relevant to the question of addictions and risky
behavior, it is related to lowered levels of these unhealthy states.
Although the data are quite limited, short-term positive emotions also appear to be associated with illness preventative and
health promotive behaviors and behavioral tendencies. For example, recent positive happy moods were associated with less cigarette use and alcohol intake (Pettit et al., 2001) and with higher
sleep quality and quantity (Bardwell, Berry, Ancoli-Israel, &
Dimsdale, 1999). Furthermore, in addition to its links with higher
levels of activity and energy, positive affect is positively correlated
with higher levels of physical exercise (Lox, Burns, Treasure, &
Wasley, 1999; Watson, 1988). In a study of women at moderate
risk for breast cancer, positive affect predicted engagement in
physical activity, particularly during leisure time (Audrain,
Schwartz, Herrera, Golman, & Bush, 2001). Physical activity, in
829
turn, is associated with many positive health outcomes (Fraser &
Shavlik, 2001; Shephard, 1993). Thus, positive affect might benefit health by indirect relations to health promoting activities.
Immunity
The evidence described previously suggests that happiness and
positive affect may be associated with enhanced physical wellbeing because of their relation to such variables as physical exercise and social support, which, in turn, are linked to improved
health. However, might long-term happiness and short-term positive affect also have direct effects on health? One mechanism
through which psychological states impinge on physical health
directly is through their effects on the immune system. Immune
system disruption has been implicated in the etiology and progression of a wide array of illnesses (cf. Baum & Poluszny, 1999;
Kiecolt-Glaser, McGuire, Robles, & Glaser, 2002).
Before highlighting the research on transient mood, we first
address whether happy people—that is, those who experience
habitual positive moods—might show enhanced immune function.
Unfortunately, direct evidence on this question is practically nonexistent. Certainly, research supports the notion that the chronic
absence of positive affect is related to immune deficiency. Longterm deficits in positive mood—that is, sadness or depressive
symptoms—are associated with decreased lymphocyte production
(McGuire, Kiecolt-Glaser, & Glaser, 2002).
Individuals with attributes closely related to happiness have also
been found to show heightened immunocompetence. For example,
in two separate investigations, humor was associated with enhanced immune function in participants who were predisposed to
use humor as a routine coping device (Dillon, Minchoff, & Baker,
1985; Dillon & Totten, 1989). Furthermore, sense of coherence
(Antonovsky, 1993) was associated with enhanced natural killer
(NK) cell activity among older adults facing the stress of relocation (Lutgendorf, Vitaliano, Tripp-Reimer, Harvey, & Lubaroff,
1999). Finally, in another relevant study, optimism was negatively
associated with incidence of upper respiratory infection (Lyons &
Chamberlain, 1994).
Research on naturally occurring moods corroborates these findings. It should be noted, however, that results linking positive
mood with immunity are rarely straightforward and depend on the
levels of negative affect experienced, as well as on the particular
immune measure used in a given study (Booth & Pennebaker,
2000). In one investigation, immunity was elevated on days when
positive mood predominated and was reduced on days when negative mood predominated (Stone, Cox, Valdimarsdottir, Jandorf, &
Neale, 1987). Controlling for negative mood, however, the effect
for positive mood fell to marginal significance. In a similar study,
Stone and colleagues (1994) found enhanced antibody activity on
days with more positive than negative moods. The experience of
uplifts during daily hassles has been related to heightened NK cell
activity in individuals with cancer histories (Vitaliano et al., 1998;
see also Lyons & Chamberlain, 1994). Other research has also
shown a relation between positive affect and NK cell activity. For
example, naturally occurring positive mood was found to be associated with higher levels of NK cells, but only among women
who reported some negative mood (Valdimarsdottir & Bovbjerg,
1997). These results may indicate a possible buffering of the
effects of negative mood by positive moods (Booth & Pennebaker,
830
LYUBOMIRSKY, KING, AND DIENER
2000), or they may distinguish the healthy happy from the repressive happy.
Coping
Do long-term and short-term PA also play a positive role in
effective coping with stress and challenge? If yes, this finding may
elucidate another pathway through which happiness and positive
emotions might have salutary effects on health. We explore this
issue in this section.
Cross-sectional research pertaining to the question of whether
happy people are better copers is primarily indirect, although a few
studies have assessed global happiness. For example, McCrae and
Costa (1986) examined personality variables as predictors of effective coping. They concluded that positive affectivity, or trait
PA, was associated with more effective and more “mature” coping
efforts. A strong correlation has also been found between positive
emotionality and coping by active engagement (Miller & Schnoll,
2000).
A number of constructs have been introduced in the coping
literature to explain the capacity of some individuals to maintain a
positive outlook during negative life circumstances. Optimism
(defined as attributional style, Seligman, 1991, or as general positive expectancy, Carver & Scheier, 2001), sense of coherence
(Antonovsky, 1988, 1993), hope (Snyder, 2000), and hardiness
(Maddi & Kobasa, 1991) all refer to general traits that are correlated with happiness and promote positive feelings during difficult
circumstances, and all have been linked with important health
outcomes (e.g., Maruta, Colligan, Malinchoc, & Offord, 2000;
Peterson, Seligman, Yurko, Martin, & Friedman, 1998; Snyder,
2000). For example, research has demonstrated that optimistic
individuals attend to and remember potentially threatening healthrelevant information more than pessimistic ones (Aspinwall, 1998;
Aspinwall & Brunhart, 1996) and use humor and positive reframing, instead of denial, when coping with highly stressful events
(Carver et al., 1993). A similar construct— hope—was also found
to relate to adaptive coping with cancer (Irving, Snyder, & Crowson, 1998). One possibility is that the effects of these constructs on
positive mood mediate their relations to physical health outcomes
(as has been shown by Segerstrom, 2000, in the case of optimism).
Although these concepts differ in a variety of ways, their correlations with positive affect are well established (cf. L. A. Clark &
Watson, 1991).
To the extent that happiness predisposes people to look on the
bright side, it should relate to superior coping during difficult
times. For example, in one study, happy students reported experiencing similar types of both positive and negative life events as
did their less happy peers, but the happy students tended to think
about both types of events more favorably and positively—for
example, by seeing humor and didactic value in adversity and by
emphasizing recent improvement in their lives (Lyubomirsky &
Tucker, 1998). In summary, research supports the argument that
the extent to which a person can maintain sensitivity to pleasurable
opportunities, even in difficult times, may be highly adaptive.
Research in a variety of areas demonstrates that positive experience and positive emotion, even in the midst of stress or challenge, may be associated not with maladjustment and denial, but,
rather, with particularly good outcomes. Indeed, Aspinwall (1998)
has argued cogently for the recognition of positive affect as a
resource in coping and self-regulation. Thus, although previous
models viewed positive affect as primarily sending a “maintain”
message to the goal seeker (e.g., Carver & Scheier, 1981, 1990),
Aspinwall pointed out the role of positive affect in harnessing
attention even to negatively tinged information.
A number of studies are consistent with this argument. Keltner
and Bonanno (1997) showed that the expression of genuine positive emotion (particularly Duchenne laughter) during bereavement
relates to heightened adjustment on a variety of levels. Fredrickson
and colleagues found that positive emotions undo the effects of
negative emotion on cardiovascular function (Fredrickson & Levenson, 1998; Fredrickson, Mancuso, Branigan, & Tugade, 2000).
A study of coping with stress following the September 11, 2001,
attacks in the United States found that resilient individuals were
less likely to experience depression and more likely to report
increases in psychological growth after the attacks (Fredrickson,
Tugade, Waugh, & Larkin, 2003). Of importance, positive emotions experienced after the attacks completely mediated the relation between resilience and coping variables. Finally, Pennebaker
(1993) found that those who used relatively more positive than
negative emotion words while writing expressively during difficult
or distressing times were most likely to benefit from disclosive
writing (cf. Pennebaker & Francis, 1996; Pennebaker, Mayne, &
Francis, 1997). Thus, the experience of the positive in the context
of traumatic or negative events has implications for psychological
and physical well-being. These moments of positive emotion may
be viewed as opportunities to replenish one’s system, which has
been depleted by grief (cf. Folkman & Moskowitz, 2000, for a
similar view).
Creativity and Problem Solving
“The happiest people are those who think the most interesting
thoughts.”
—William Lyon Phelps
Flexibility and Originality
The few existing correlational studies in this area suggest that
chronically happy people score higher on measures of creativity.
For example, relatively higher scores on tests of creativity have
been documented in happy, relaxed, and bold children (Cacha,
1976) and in individuals with hypomanic personality traits (Schuldberg, 1990). Certain personality characteristics such as flexibility
and openness are related to creativity, and these traits are most
common among those who have periods of hypomania without
depression, but are not as common in those who have hypomania
with intermittent depression (Shapiro & Weisberg, 1999). Notably,
the most creative group in the Shapiro and Weisberg study was
composed of individuals with elevated moods and without symptoms of depression. Furthermore, eminently creative people have
been shown to be characterized by dominance and self-confidence
(Feist, 1998)—two facets of extraversion to be consistently related
to long-term well-being (e.g., Lucas et al., 2000). However, Openness (the fifth major factor in the Big Five Factor Model) is usually
not related to chronic happiness (McCrae & Costa, 1991; rs ⫽ .01
and ⫺.05), suggesting that the connection between happiness and
flexibility is at the momentary level, not necessarily at the longterm level of personality.
BENEFITS OF FREQUENT POSITIVE AFFECT
Obviously, research on whether happy individuals are relatively
more flexible is scarce, and much more research is needed to draw
firm conclusions in this area. Fortunately, studies of naturally
occurring moods—although also rare— corroborate these findings.
For example, Richards (1994) described “everyday creativity” in
which people find new ways to approach activities and problems in
their daily lives. She found that everyday creativity occurred when
people were in a normal or elevated mood, and rarely when they
were depressed. Positive moods—particularly those involving
high-arousal emotions such as excitement or joy—are also related
to curiosity and desire for exploration (Kashdan, Rose, & Fincham,
2004). In a field study, positive affect expressed by employees on
the job was correlated .30 with supervisors’ evaluations of the
employees’ creativity (Staw et al., 1994). Finally, mildly manic
states have been found to be associated with creative episodes in
such fields as poetry (Richards, 1994; Richards & Kinney, 1990;
cf. Jamison, 1990).
831
positive construals of self and other (mean r ⫽ .39), sociability and
activity (mean r ⫽ .33), prosocial behavior (mean r ⫽ .32),
popularity (mean r ⫽ .31), healthy behavior (mean r ⫽ .33), high
immune functioning (mean r ⫽ .33), and good coping with distress
(mean r ⫽ .34). The evidence, although less conclusive, also
suggests that chronically happy people and those in pleasant
moods might be more creative as well as more efficient problem
solvers (mean r ⫽ .26) and might show superior conflict resolution
skills (mean r ⫽ .23). Most, if not all, of these attributes appear to
promote active goal involvement, which is adaptive in many
circumstances and likely facilitates success in a broad range of life
domains. However, additional research is needed in many of the
areas we reviewed, because only a handful of studies are available
that are relevant to certain domains.
LONGITUDINAL EVIDENCE
Question 3: Does Happiness Precede Success?
Performance on Complex Mental Tasks
Surprisingly, few cross-sectional studies have examined the
performance of chronically happy people on complex mental tasks.
One exception is an investigation by Staw and Barsade (1993),
who had participants perform a manager assessment task that was
based on a complex 3-hr “in-basket task”—that is, a procedure
assessing a person’s ability to effectively complete a series of
diverse assignments. As rated by objective observers, those high in
dispositional positive affect performed better on the manager assessment task—for example, they received relatively higher scores
on mastery of information. In another set of studies, after being led
to believe that they “failed” on an earlier task, chronically happy
individuals showed superior performance, relative to less happy
individuals, on the reading comprehension portion of the Graduate
Record Examination (Lyubomirsky, Kasri, Zehm, & Dickerhoof,
2005).
Research on choice and decision making, albeit indirect, further
suggests that happy people make better and more efficient decision
makers. For example, people high in well-being appear to be less
susceptible to negative influences from advertising (Geier,
Schwartz, & Brownell, 2003). Happy individuals are also more
likely than their unhappy peers to optimize or satisfice in their
decision making, rather than maximizing to achieve the best outcome regardless of the cost in time and effort (B. Schwartz et al.,
2002). That is, unhappy people carefully search for the very best
answer, regardless of the importance of the context or the novelty
of the problem. This effortful strategy is likely to be inefficient in
situations that have been frequently encountered in the past and for
which a reasonable solution has been found, as well as in much of
life in which time is limited and tasks are complex.
Is positive affect also associated with enhanced performance on
complex mental tasks? The overwhelming majority of the literature in this area consists of experimental studies; hence, these
investigations are discussed in a later section.
Conclusion
In this section, we reviewed cross-sectional evidence suggesting
that both long-term well-being and momentary positive affect are
associated with a number of desirable characteristics, including
Our review of the cross-sectional literature revealed how extensive and robust are the correlations found between chronic happiness, as well as short-term positive affect, and numerous indicators
of culturally valued success, including successful outcomes in
work, relationships, and health, as well as characteristics and
behaviors paralleling these outcomes. However robust and wideranging the correlations we observed, they offer only preliminary
evidence that a causal relationship might exist between happiness
and success. In the next two sections, we consider the much
smaller number of longitudinal studies, which increase our confidence—though not definitively—in the notion that long-term happiness and short-term positive moods might actually cause the
outcomes with which they correlate. The relevant study characteristics are presented in the first half of Table 2, and the effect sizes
are displayed in Table 2 and in the middle panel of Table 4.
Work Life
Employment and Quality of Work
Longitudinal studies corroborate the correlational literature linking happiness and desirable work outcomes. For example, people
with high subjective well-being who are interviewing for a job are
relatively more likely to receive a callback second interview 3
months later (Burger & Caldwell, 2000). A study by Roberts,
Caspi, and Moffitt (2003) is instructive regarding the causal direction between happiness and work outcomes because measures
of positive affect were collected at age 18 and the work outcomes
were assessed at age 26. Positive affectivity at the end of adolescence predicted outcomes such as financial independence, occupational attainment, and work autonomy in young adulthood.
However, positive job characteristics also led to increases in positive affect, suggesting a bidirectional influence. Paralleling these
findings, in a prospective longitudinal study, employees high in
dispositional positive affect had jobs 1.5 years later that allowed
them more autonomy, meaning, and variety (Staw et al., 1994).
Furthermore, Verkley and Stolk (1989) found that people who
were happy were less likely to lose their jobs in the ensuing period.
Additionally, unemployed individuals with high subjective wellbeing were more likely to be reemployed at follow-up than unhappy people. Although the effects of subjective well-being were
LYUBOMIRSKY, KING, AND DIENER
832
small in both directions in this study, they persisted when factors
such as length of unemployment and health were statistically
controlled.
Once employed, those who show high positive affect on the job
receive relatively more favorable evaluations from supervisors—
for example, for quality of work, productivity, and dependability—a year and a half later (Staw et al., 1994). Happy people have
also been shown to receive higher supervisory ratings over time in
other studies (Cropanzano & Wright, 1999; Wright & Staw, 1999).
For example, happier employees were rated by their administrative
officers as superior up to 3.5 years later in the four dimensions of
support, work facilitation, goal emphasis, and team building
(Wright & Staw, 1999, Study 1). Positive affect on the job has also
been found to predict reduced absenteeism 5 months later (Pelled
& Xin, 1999). Finally, a construct related to positive affect, dispositional optimism, predicted the success of life insurance agents
(Seligman & Schulman, 1986).
Income
Longitudinal and prospective studies of the link between happiness and income are more persuasive regarding causal direction
than cross-sectional investigations. For example, in an Australian
panel study, young adults who described themselves as happy
during a particular period of time were more likely to increase in
income during the following period (Marks & Fleming, 1999).
Similar results were obtained in a Russian panel study, in which
individuals’ happiness levels in 1995 were positively correlated
with higher income and lower unemployment in 2000, even after
controlling for other demographic variables (Graham et al., in
press).
Diener and his colleagues related measures of cheerfulness as
students entered college to the respondents’ income when they
were in their 30s (Diener, Nickerson, Lucas, & Sandvik, 2002).
Students with greater cheerfulness in the first year of college
earned more money 16 years later, and this effect persisted even
after controlling for their parents’ income. The effect of cheerfulness was strongest for the respondents whose parents were well
off. When the parents’ income was high (i.e., above $50,000 U.S.),
the most cheerful college students later made $25,000 more per
year than did the least cheerful college students. Furthermore, the
cheerful college students were less likely to experience long-term
unemployment after college. Corroborating these results, in a
study of working adults, employees who were high in dispositional
positive affect received greater pay increases over time than those
low in positive affect (Staw et al., 1994). These data suggest that
high subjective well-being leads to later financial prosperity.
Social Relationships
Friendship, Social Support, and Marriage
While a number of longitudinal studies have examined marriage, we are aware of only one longitudinal investigation relevant
to social support. In the workplace, employees who showed high
dispositional positive affect received more emotional and tangible
assistance more than a year later (Staw et al., 1994). This study
suggests that happy people may draw others to help and befriend
them.
As described earlier, numerous cross-sectional investigations
have documented a link between happiness and the state of being
married. However, the most powerful evidence for the argument
that happiness leads to marriage, as opposed to the reverse, comes
from several longitudinal investigations (Lucas, Clark, Georgellis,
& Diener, 2003; Marks & Fleming, 1999; Spanier & Furstenberg,
1982; see also Neyer & Asendorpf, 2001). Marks and Fleming
(1999) conducted a longitudinal study with four cohorts of nationally representative young Australians, who participated every 1 to
2 years over the course of a total of up to 15 years. Unmarried
respondents who were one standard deviation above the mean on
happiness were 1.5 times more likely to be married at a later time
period than those with mean levels of happiness. Unmarried respondents two standard deviations above the mean on happiness
were twice as likely to be married later. A 16-year panel study
carried out in Germany corroborated these results (Lucas et al.,
2003). German men and women who were highly satisfied with
their lives were more likely to get married 4 or more years later
than those who were initially less satisfied. Finally, U.S. women
who expressed sincere positive affect in their college yearbook
photos at age 21 were relatively more likely to be married by age
27 and less likely to remain single through middle adulthood
(Harker & Keltner, 2001).
Longitudinal investigations also bolster the cross-sectional findings regarding relationship satisfaction, suggesting that individual
happiness may bolster marital well-being (Headey et al., 1991;
Headey & Veenhoven, 1989; Ruvolo, 1998; Spanier & Furstenberg, 1982). For example, in a 6-year, four-panel study of Australians, participants’ individual happiness at earlier time periods
increased the likelihood that they would have a happy marriage at
later time periods (Headey & Veenhoven, 1989). Furthermore, in
a 2.5-year prospective study, Spanier and Furstenberg (1982)
found that happier people were more likely to remarry after a
divorce. An even longer term result was reported in the previously
mentioned study of women’s college yearbook photos (Harker &
Keltner, 2001). The amount of positive affect expressed in these
photos at age 21 predicted marital satisfaction 31 years later.2
Finally, an intriguing finding is that people’s global happiness at
one point in time can potentially influence the marital well-being
of their spouses a year later (Ruvolo, 1998).
Self-esteem has also been related to relationship quality in
longitudinal research. For example, German adults, ages 18 to 30
years, reported on several characteristics of their social relationships at two time periods (Neyer & Asendorpf, 2001). Respondents’ levels of self-esteem at Time 1 predicted, over the course of
four years, increases in the closeness and importance of their social
relationships (especially those with friends and colleagues) and
decreases in the feelings of security and amount of conflict participants had in their relationships.
2
These conclusions must be tempered in light of a meta-analysis by
Karney and Bradbury (1995). In their review of 115 longitudinal studies of
marital stability and satisfaction, extraversion was found to have a weak
negative relationship to marital stability (average r ⫽ ⫺.04 for wives, ⫺.08
for husbands, and ⫺.08 for couples). However, these results were based on
1 or 2 studies and the measures of extraversion used were not specified.
BENEFITS OF FREQUENT POSITIVE AFFECT
Why Might Happier People Reap Larger Social Rewards?
Both the cross-sectional evidence and the longitudinal evidence
we have reviewed thus far strongly suggest that happy people are
better able to develop social relationships and build a rich network
of support. To quote Wilson’s (1967) oft-cited review of the
literature on well-being, “Perhaps the most impressive single finding lies in the relation between happiness and successful involvement with people” (p. 304). Furthermore, the social rewards of
happiness cannot be overstated, as strong social bonds and social
support have been shown to further elevate positive emotions and
enhance social acceptance, health, and emotional adjustment (Argyle & Martin, 1991; Cohen, 1988; House, Landis, & Umberson,
1988; Myers, 1992) and, as some writers have suggested, even to
aid human survival (Berscheid, 2003; Myers, 1999).
We submit that the primary mechanism underlying the relation
between long-term happiness and the quality and quantity of social
relationships is the experience of frequent positive emotions. A
growing body of research suggests that happy feelings have a
marked positive influence on interpersonal behavior (Isen, 1999).
People are more likely to want to become friends with and to
provide emotional and tangible assistance to individuals with a
positive outlook (Salovey, Rothman, Detweiler, & Steward, 2000).
For example, an observational study of children found that displays of happy affect were most frequently responded to by other
kids with empathic behaviors—for example, positive reinforcement and physical or verbal comfort (Strayer, 1980). Befriending
and supporting a happy person may evoke positive feelings in the
friend or helper, increasing the likelihood that they will seek to
maintain the relationship (Staw et al., 1994). In Gottman’s work on
happy marriages, he has found that the longevity of marriages is
best predicted by the ratio of positive versus negative interactions
(Gottman & Levenson, 1999).
Furthermore, genuine Duchenne smiles and laughter, which
characterize chronically happy people, signal to other people that
one is friendly and open to social interaction, inviting them to
become engaged (Frijda & Mesquita, 1994; Keltner & Kring,
1998; Ruch, 1993). This argument is supported by theory and
research on the role of positive emotions in infant– caregiver
interactions. Smiles in infants appear to build infant– caregiver
attachment, ensuring that the caregiver will continue to care for the
child and secure his or her well-being (Fredrickson, 1998, 2001;
Tomkins, 1962). Mothers who express positive emotions have
infants who begin to express positive emotions as well (e.g.,
Haviland & Lelwica, 1987). Indeed, such observations led Eric
Fromm (1962) to go so far as to argue that “a mother must not only
be a ‘good mother,’ but also a happy person” (p. 49).
Mental health. Although few longitudinal studies address issues of mental health, the existing evidence parallels the crosssectional data. For example, a longitudinal investigation showed
that people who were high in subjective well-being were less likely
to suffer depressive symptoms if they became unemployed in the
ensuing period (Verkley & Stolk, 1989). Furthermore, in a longitudinal study of the Finnish Twin cohort, life satisfaction was
associated with lower risk of work disability that was due to
psychiatric causes (as well as nonpsychiatric ones) from 1 to 12
years later (Koivumaa-Honkanen et al., 2004). Within the same
sample, subjective well-being was also shown to be negatively
associated with suicide. That is, life satisfaction was found to
833
relate to a lower risk of suicide 20 years later, even after controlling for other risk factors such as substance use, smoking, physical
activity, age, and sex (Koivumaa-Honkanen et al., 2001). An
additional relevant study concerns substance use, another indicator
of poor mental health. In a longitudinal study of more than 1,700
adolescents, positive affect buffered the relation between negative
affect and substance use (Wills, Sandy, Shinar, & Yaeger, 1999).
Finally, a construct related to well-being— optimistic attribution
style—was found to predict mental health problems, poor adjustment, and high levels of drinking 10 years later (Peterson et al.,
1998).
Physical health. Longitudinal studies are also useful in giving
researchers a process picture of the relation between happiness and
physical health. For example, in a study of close to 5,000 individuals, happiness was related to relatively better health (as measured
by self-reported health problems, days missed that were due to
illness, and hospitalization) 5 years later (Graham et al., in press;
see also Koivumaa-Honkanen et al., 2004). The experience of
positive mood predicted a lower incidence of stroke 6 years later,
especially in men (Ostir, Markides, Peek, & Goodwin, 2001), as
well as sports-related injuries during the course of hockey season
(A. M. Smith, Stuart, Wiese-Bjornstal, & Gunnon, 1997). A related construct— optimism—was also associated with lowered incidence of cardiovascular disease (e.g., heart attacks and angina)
10 years later (Kubzansky, Sparrow, Vokonas, & Kawachi, 2001),
with higher quality of life, heightened physical recovery, and
quicker return to normal behaviors 6 months following cardiac
surgery (Scheier et al., 1989), and with better risk reduction for
cardiovascular heart disease 8 months after surgery (Fitzgerald,
Prochaska, & Pransky, 2000). Shorter term longitudinal studies
mirror these results. For example, low positive affect in adolescents predicted greater delinquent activity 6 months later (Windle,
2000). Furthermore, in two investigations, increasing numbers of
positive events were negatively associated with incidence of upper
respiratory infection over a 2-week period (Lyons & Chamberlain,
1994). An even shorter term study showed that positive mood
assessed on a particular day predicted fewer emergency room and
hospital visits on the next day (Gil et al., 2004).
Longevity and survival. Is happiness associated with superior
longevity and survival? A number of studies—all longitudinal, by
definition— have shown that happy people are less likely to die of
certain causes. In a study of more than 37 nations, subjective
well-being was negatively related to automobile fatalities (Kirkcaldy & Furnham, 2000). A recent study of Scandinavians found
that over a 19-year period, dissatisfaction with life predicted fatal
unintentional injuries as well as intentional injuries (KoivumaaHonkanen, Honkanen, Koskenvuo, Viinamaeki, & Kaprio, 2002).
Research on the influence of emotions on longevity has primarily
stressed the role of negative emotions in decreasing survival times
(e.g., Denollet & Brutsaert, 1998; Naughton et al., 2002). However, studies have also demonstrated longer survival times, after an
illness, for people with positive emotional traits. Individuals experiencing end-stage renal disease who scored highly on overall
happiness were more likely to survive 4 years later (Devins, Mann,
Mandin, & Leonard, 1990), women experiencing a recurrence of
breast cancer who reported joy were more likely to survive 7 years
later (S. M. Levy, Lee, Bagley, & Lippman, 1988), and those
individuals with spinal cord injuries reporting greater satisfaction
with their lives were more likely to survive 11 years later (Krause,
834
LYUBOMIRSKY, KING, AND DIENER
Sternberg, Lottes, & Maides, 1997). Additionally, a longitudinal
study using a sample of 513 Berlin residents revealed a significant
link between well-being and all-cause mortality (Maier & Smith,
1999). Because happiness is associated with a variety of life
outcomes related to survival (e.g., stable relationships, lower accident and suicide rates, superior coping, and less stress; Baum &
Poluszny, 1999; House et al., 1988), it would not be surprising if
sustained levels of positive affect should relate to overall longevity. A few large-scale prospective studies have examined the link
between positive traits and longevity. Levy and colleagues examined attitudes about aging in older adults (B. R. Levy, Slade,
Kunkel, & Kasl, 2002). Individuals with positive self-perceptions
of aging lived on average 7.5 years longer than those with less
positive perceptions, even after controlling for age, sex, socioeconomic status, loneliness, and functional health. Notably, the effect
for positive aging attitudes surpassed the effects for body mass,
smoking, and exercise. In a study of older individuals, 12% died
over the course of 2 years, but those rated as happy were significantly less likely to die than those rated as unhappy (Zuckerman,
Kasl, & Ostfeld, 1984; see also Pitkala, Laatkonen, Strandberg, &
Tilvis, 2004). Palmore (1969) investigated predictors of longevity
in a sample of 268 older adults. To control for age effects, the
author examined the number of years a person had survived
compared with the number of years he or she would be expected
to live. This “longevity quotient” was correlated .26 with
interviewer-assessed happiness. Of importance, the objective happiness rating was the second strongest predictor of longevity—
weaker than work satisfaction, but stronger than physical functioning and tobacco use. Corroborating these findings for the link
between happiness and longevity, Deeg and van Zonneveld (1989)
showed that a 70-year-old man of average health is expected to
live 20 months longer if he reports being satisfied with his life one
standard deviation higher than his peers. Danner and his colleagues
(2001) examined predictors of longevity in a large longitudinal
sample of Roman Catholic nuns. Higher levels of positive emotion
expressed in autobiographies written at an average age of 22 were
associated with a 2.5-fold difference in risk of mortality when the
nuns were in their 80s and 90s. These results are impressive given
that the environments of these nuns are expected to be quite similar
throughout their lives, and that other health relevant variables,
such as diet and activity levels, might be assumed to be relatively
homogeneous in this sample. In a study of 2,000 older Mexican
Americans (Ostir, Markides, Black, & Goodwin, 2000), positive
emotionality significantly predicted survival 2 years later, even
after controlling for such variables as marital status, diet, smoking,
and negative affect. Finally, it is notable that studies examining
optimism parallel these results. For example, optimism was associated with lower risk of death for 800 patients followed for 30
years (Maruta et al., 2000; see also Peterson et al., 1998), and men
with an optimistic explanatory style were less likely to die of
coronary heart disease 10 years later (Kubzansky et al., 2001). In
contrast to these recent studies, the well-known Terman Study of
gifted individuals found that a childhood measure of cheerfulness
(rated by parents and teachers) was associated with earlier death
(Friedman et al., 1993). However, the sample used in this study
showed little variability in happiness—most were extremely
happy. Thus, the results might reflect the fact that above some high
level, happiness might not be adaptive. However, this conjecture is
obviously speculative. As it stands, we are uncertain why the
results of the Terman Study diverge from other findings in this
area.
Conclusion
In summary, although the longitudinal literature is much less
extensive than the correlational work, it is still impressive in the
robustness and consistency of its results. Study after study shows
that happiness precedes important outcomes and indicators of
thriving, including fulfilling and productive work (mean r ⫽ .24),
satisfying relationships (mean r ⫽ .21), and superior mental and
physical health and longevity (mean r ⫽ .18). However, relatively
few longitudinal studies were identified altogether, and none were
found in the areas of citizenship and friendship, indicating a clear
need for future research. In the next section, we continue our
review of the longitudinal literature, examining studies that relate
short- and long-term happiness at Time 1 with resources and
characteristics paralleling successful outcomes at Time 2.
Question 4: Do Happiness and Positive Affect Precede
Behaviors Paralleling Success?
Positive Self-Perceptions
To our knowledge, the only relevant longitudinal investigations
in this area concern the link between life satisfaction and positive
affect, respectively, to self-perceptions. The first study indicates
that high life satisfaction can lead to feelings of self-confidence.
Using a panel design, Headey and Veenhoven (1989) investigated
the direction of influence between life satisfaction and feelings of
superiority, and found evidence for causality in both directions.
That is, feeling above average on a number of characteristics
preceded higher life satisfaction, but high life satisfaction was also
followed by greater feelings of superiority. The second relevant
investigation revealed that women who expressed positive affect at
age 21 were relatively more likely to rate themselves high in
competence two to three decades later (Harker & Keltner, 2001;
mean r ⫽ .25).
Sociability and Activity
Sociability and Extraversion
Longitudinal studies reinforce the cross-sectional findings linking happiness and extraversion, demonstrating that this link holds
even when the two variables are measured many months or years
apart (Costa & McCrae, 1980; Costa, McCrae, & Norris, 1981;
Headey & Wearing, 1989). Longitudinal studies have also shown
that levels of positive affect are positively correlated with measures of extraversion and sociability, assessed from 3 months to 10
years apart (Costa & McCrae, 1980; Headey & Wearing, 1989).
For example, returning once again to the yearbook study, women
who expressed positive affect at age 21 were more likely to
describe themselves as high in affiliation many years later—at
ages 43 and 52 (Harker & Keltner, 2001).
Social Interaction and Activity
Corroborating the fairly extensive correlational results, longitudinal studies of older people have shown a significant association
BENEFITS OF FREQUENT POSITIVE AFFECT
between chronic, global happiness, and participation in a variety of
activities 18 months later (Kozma & Stones, 1983; Stones &
Kozma, 1986). As another example, in a recent short-term prospective study, happy students were more likely than their less
happy peers to adopt over the course of a semester a variety of new
goals and activities that “gave them a boost” (Sheldon & Lyubomirsky, in press).
Another study focused on temporary pleasant moods, rather than
long-term happiness, as a possible stimulus for engagement in
social and recreational activities (Lucas, 2001). In this investigation, positive affect at Time 1 predicted the amount of time
participants spent on recreation and on activities with friends and
family members at Time 2, even after controlling for Time 1
activity levels.
Summary
As can be seen in Panel 5 of Table 2, reasonably strong evidence
exists for the hypothesis that happiness precedes desirable resources and behaviors relevant to sociability and activity, such as
extraversion and engagement in activities. The mean effect size (r)
for these studies is .25.
Prosocial Behavior
In the only relevant longitudinal work we identified, research
suggests that altruism may follow from happiness, as well as the
reverse. Thoits and Hewitt (2001) showed that the causal connection between volunteer work and subjective well-being is bidirectional. Following a large sample over two waves, they found those
with high happiness and life satisfaction increased in the hours
they spent in volunteer activities over the course of the study.
Controlling for other variables, a conservative estimate for the
effect size (r) is .04. At the same time, those who volunteered more
hours increased in happiness.
Physical Well-Being and Coping
Health Perceptions and Healthy Behavior
We identified only a few relevant longitudinal studies in this
area. A daily diary study of sickle cell disease patients found that
positive mood during Day 1 was related with lower reported pain
during Day 3 (Gil et al., 2004, cited previously). Furthermore,
happy people were less likely to drink and smoke 5 years later in
a Russian study (Graham et al., in press; see also Peterson et al.,
1998) and to describe themselves as healthy in a U.S. study
(Stones & Kozma, 1986).
Immunity
Intriguing short-term longitudinal results were obtained from a
recent study that examined immunity indirectly, by assessing susceptibility to illness (Cohen, Doyle, Turner, Alper, & Skoner,
2003). Healthy volunteers were exposed to a rhinovirus and monitored for host resistance to the common cold. Those with a
positive emotional style—that is, who typically reported experiencing positive emotions—were relatively less likely to develop a
cold, and, important to note, this association was independent of a
negative emotional style. Furthermore, typical negative emotional
835
experience was not associated with colds. Finally, in a study
assessing immune function directly, cancer survivors with more
uplifts than hassles showed enhanced NK cell activity 18 months
later (Vitaliano et al., 1998).
Coping
Research using prospective longitudinal designs has examined
coping as a function of traits linked with positive functioning, such
as optimism, as well as a function of preexisting positive mood.
For example, optimism has been associated with better psychological adjustment after breast cancer diagnosis (Epping-Jordan et al.,
1999), with the tendency to cope with breast cancer surgery
through active engagement (Carver et al., 1993) and with more
problem-focused coping and less denial following open-heart surgery (Scheier et al., 1989). Furthermore, two studies focused on
the link between positive mood and coping with potential and
actual breast cancer. C. C. Chen and colleagues (1996) found that
positive affective responses predicted engaged coping among
women who were undergoing biopsy for suspected breast cancer.
A study predicting coping and mood following surgery for breast
cancer showed that preexisting levels of positive mood predicted
the tendency to cope through active engagement (Carver et al.,
1993). The effect of positive affect on coping has also been
demonstrated in research by Fredrickson and Joiner (2002), who
found that experiences of positive emotion at one time period were
associated with more effective coping and even greater positive
experiences later.
Conclusion
In summary, accumulating research shows that happiness, pleasant moods, and closely related constructs precede indicators of
physical well-being and adaptive coping (mean r ⫽ .27; see Panel
7 of Table 2).
Creativity and Problem Solving
The vast majority of investigations in this area are experimental
and thus are described in the next section. The only longitudinal
study we identified was conducted by Staw and his colleagues
(2004), who found that positive affect expressed on the job by
employees predicted their supervisor’s evaluation of the employees’ creativity a year and a half later (r ⫽ .31).
Conclusion
The longitudinal literature is undoubtedly sparser than the crosssectional work. We were able to identify few relevant longitudinal
studies in several areas and none at all examining the topics of
perceptions of other people, enjoyment of social activities and
interactions, likability, negotiation and conflict resolution, and
performance of complex mental tasks. Despite the scarcity of
relevant studies, every single investigation we found corroborated
the correlational findings in the direction predicted by our model.
That is, both long-term happiness and short-term pleasant moods
tend to precede the desirable characteristics, resources, and behaviors with which they are correlated. Clearly, longitudinal research
should be a high priority for the future. Fortunately, many relevant
experimental studies exist, which offer an even stronger test of our
LYUBOMIRSKY, KING, AND DIENER
836
causal hypothesis regarding happiness and success. In the next
section, we document the fairly large and growing literature examining the effects of induced pleasant affect—the hallmark of
long-term happiness— on behaviors, resources, and skills paralleling culturally defined success. In short, this evidence addresses the
critical question of whether positive affect causes the adaptive
characteristics that help happy people thrive.
EXPERIMENTAL EVIDENCE
Question 5: Does Positive Affect Lead to Behaviors
Paralleling Success?
Positive Perceptions of Self and Others
Self-Perceptions
Experimental work on induced positive moods suggests that
positive emotions have a causal influence on positive self-feelings.
For example, students induced into experiencing a positive mood
thereafter describe themselves in more positive terms (Sarason,
Potter, & Sarason, 1986), assess their task performance as superior
(Barsade, 2002), report more favorable global self-evaluations, and
recall more positive experiences and successes from their past
(M. S. Clark & Waddell, 1983; Wright & Mischel, 1982). Happy
moods also appear to increase feelings of self-efficacy. Those put
in a good mood report higher self-efficacy (Baron, 1990; Samson
& Rachman, 1989; Schuettler & Kiviniemi, in press) and set
higher goals for themselves (Baron, 1990; Hom & Arbuckle,
1988). Induced positive moods also lead people to expect more
success on laboratory tasks (Brown, 1984; Wright & Mischel,
1982). Finally, positive mood leads individuals to attribute their
successes to stable factors within themselves (Brown, 1984). Thus,
the evidence indicates that positive affect makes people feel good
about themselves.
Perceptions, Memories, and Judgments of Others
A review of the experimental literature suggests that short-term
positive affect triggers not only positive feelings about oneself, but
also promotes greater liking and fondness for others. Experimental
studies show that individuals induced to feel happy are more likely
than those induced to feel sad to express liking for a stranger
(Baron, 1987, 1993; Griffitt, 1970). For example, in one set of
studies, students were asked to conduct a simulated job interview.
After the interview, those who had been previously induced into a
positive mood rated the applicant higher on a number of jobrelated and personal dimensions and were more likely to “hire”
him or her than those induced into a negative mood (Baron, 1987,
1993; see also Baron, Rea, & Daniels, 1992). Happy moods have
also been found to be associated with recollections of positive
information about a particular person (Baron, 1987).
Sociability and Activity
In this section, we consider the literature on sociability, activity,
and energy, to determine whether happy moods prompt more
frequent, more enjoyable, and higher quality social activities and
interpersonal interactions.
Sociability and Extraversion
Laboratory studies in which positive moods have been induced
support the causal direction from positive affect to sociability
(Isen, 1999). In seminal research in this area, Isen (1970) found
that participants induced into a positive mood were more sociable
with a confederate—for example, more likely to initiate conversation with her and be more attentive (see also McMillen, Sanders,
& Solomon, 1977). Almost 20 years later, a very similar study
found analogous results (Cunningham, 1988b). When left alone
with a female peer, male participants induced to feel happy were
more likely to engage in social interaction and self-disclosed more
to her than those induced to feel sad. Cunningham (1988b) suggested that the positive affect may have increased the men’s
feelings of energy for engaging in a social interaction and raised
their expectations for rewards from the communication. In another
study, participants who had been induced into a pleasant mood
reported that they would choose to engage in social activities if
they feel happy (Cunningham, 1988a). In summary, these studies
support the notion that positive moods have beneficial social
consequences. When feeling happy, people tend to seek out social
interactions, in part because they are likely to view such interactions as rich and rewarding (Schaller & Cialdini, 1990).
Social Interaction, Activity, and Energy
Evidence supporting the argument that positive affect promotes
activity, as opposed to the reverse, comes from a well-cited experimental study (Cunningham, 1988a). Students who were induced to feel happy, relative to those induced to feel neutral or sad,
showed greater interest in leisure activities (e.g., eating good
meals, planning a trip or vacation, or going to a party or a sporting
event, rock climbing, and shopping; Cunningham, 1988a). Thus,
one of the benefits of positive affect is that it appears to boost
activity, energy, and involvement in active leisure.
Enjoyment of Activities and Social Interactions
When experiencing a pleasant mood, people are more likely,
rather than less, to enjoy their activities and social interactions and
to derive more satisfaction from them. Laboratory studies have
shown that induced happy moods lead participants to derive
greater enjoyment from whatever task they are instructed to perform. For example, individuals in an induced positive mood are
more likely to enjoy category-sorting tasks (Hirt, Melton, McDonald, & Harackiewicz, 1996; Murray, Sujan, Hirt, & Sujan,
1990), and groups put in a positive mood are more likely to take
pleasure in a group negotiation task (Carnevale & Isen, 1986).
Summary
In summary, transient happy moods appear to lead people to
seek out others and to engage with the environment at large, to be
more venturesome, more open, and more sensitive to other individuals (Veenhoven, 1988). Supporting this thesis, temporary elation has been associated with greater perceived relationship closeness and self– other overlap (Waugh & Fredrickson, 2003; see also
Kashdan & Roberts, 2004); increased activity and physical arousal
(Schaller & Cialdini, 1990); as well as excited, affectionate, and
affiliative feelings (Lucas, 2001; Watson, 1988). Additionally,
BENEFITS OF FREQUENT POSITIVE AFFECT
positive mood is related to higher levels of energy (Lehr, 1982).
Watson (2000) reviewed evidence showing that both positive
affect and feeling lively and energetic are aspects of extraversion.
Indeed, feeling active is so highly correlated with positive affect
that Watson and colleagues used it as one marker for positive
emotions on their affect measure, the widely used Positive and
Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen,
1988).
Negotiation and Conflict Resolution
The experimental evidence supports the argument that pleasant
moods boost people’s abilities at resolving conflict. In one study,
those with induced positive affect showed a decreased preference
for resolving conflict through avoidance and an increased inclination for reducing conflict through collaboration (Baron, Fortin,
Frei, Hauver, & Shack, 1990). Similarly, participants with induced
positive mood were found to make more concessions during faceto-face negotiations, and to have a weaker preference for handling
future conflicts with avoidance and competition (Baron, 1990; see
also Baron et al., 1992). In the same study, those put in a positive
mood were more likely to solve conflicts through collaboration,
and were more likely to offer help to others. Finally, Forgas (1998)
found that an induced positive mood had a beneficial influence on
bargaining across a variety of negotiation tasks, with individuals in
pleasant moods revealing a marked penchant to be more cooperative and less competitive (see also Barsade, 2002). Similar results
have been obtained when investigating groups. Carnevale and Isen
(1986) found that a group put in a positive mood was more likely
to reach an optimal agreement and less likely to break off negotiation and to use aggressive tactics.
Prosocial Behavior
In reviewing the experimental research on mood and prosocial
behavior, we address the question of whether the experience of
pleasant moods stimulates people to be more altruistic, generous,
and charitable people.
Numerous experimental studies have found that happy moods
increase the likelihood and amount of helping. Indeed, this effect
is one of the most robust findings in the literature on positive mood
and social behavior, having been variously called the “feel good,
do good” phenomenon, the “glow of goodwill,” and the “warm
glow of success.” Both the inductions of positive mood and the
assessments of helping have taken numerous forms in these studies. For example, happy moods, in comparison with sad or neutral
moods, have promoted such behaviors as contributing money to
charity (Cunningham, Steinberg, & Grev, 1980; Isen, 1970) or to
needy children (Rosenhan, Underwood, & Moore, 1974), donating
blood (O’Malley & Andrews, 1983), and volunteering for an extra
experiment (Aderman, 1972; Baron & Bronfen, 1994; Baron et al.,
1992; Berkowitz, 1987; Isen & Levin, 1972; Rosenhan, Salovey,
& Hargis, 1981).
In summary, the extensive experimental evidence indicates that
positive affect fosters helping behavior. However, what about
negative affect? Of interest, negative moods such as sadness or
guilt have also been shown to promote helping—for example,
when the helping promises to improve mood (e.g., Manucia,
Baumann, & Cialdini, 1984), when the person in need calls atten-
837
tion to his or her plight (McMillen et al., 1977), when the negative
mood does not lead to self-preoccupation (Kidd & Marshall,
1982), or when individuals feel they have harmed someone
(Salovey, Mayer, & Rosenhan, 1991). Thus, researchers have
argued that positive moods lead to helping under the majority of
circumstances, whereas negative moods lead to helping only under
certain conditions—namely, when the rewards of helping are high
and the costs are low (e.g., Cunningham, Shaffer, Barbee, Wolff,
& Kelley, 1990). In contrast, there appear to be multiple reasons
that positive affect fosters helping (Carlson, Charlin, & Miller,
1988).
The research evidence consistently shows that happy moods
lead to increased helping. What are the mechanisms underlying
this effect? Considerable theoretical discussion has focused on this
question (e.g., Batson, 1990; M. S. Clark & Isen, 1982; Salovey &
Rosenhan, 1989; Schroeder, Penner, Dovidio, & Piliavin, 1995),
and a variety of hypotheses have been advanced. The most persuasive evidence supports the view that happy moods lead to
helping through increases in positive thoughts and more favorable
judgments of others—for example, by increasing liking for other
people (Baron, 1987, 1993; Griffitt, 1970) and enhancing one’s
sense of advantageous resources and good fortune that should be
shared equitably with others (Aderman, 1972). Furthermore, individuals in pleasant moods may expect that helpfulness will evoke
gratitude and appreciation—that is, they anticipate positive outcomes and rewards of helping, as opposed to the potential costs
(M. S. Clark & Waddell, 1983; Cunningham, 1988a). In addition,
people in a happy mood may be more likely to recall the positive
aspects of their past helping experiences (M. S. Clark & Isen,
1982, 1983) and to view themselves as more generous people, as
well as to feel more confident, efficacious, resource laden, in
control, and optimistic about their ability to help (M. S. Clark &
Isen, 1982; Cunningham, 1988a; Taylor & Brown, 1988).
In summary, the sizable experimental literature on helping offers persuasive evidence suggesting that positive affect heightens
generosity and helpfulness. Moreover, because this research primarily comprises studies involving experimental inductions of
mood, the causal direction is generally known. That is, although
helping undoubtedly elevates mood, we can be confident that
pleasant moods also foster helping.
Physical Well-Being and Coping
Health Perceptions
Although the experimental literature in the area of health perception is scarce, the results are intriguing. For example, individuals induced into a happy mood have shown relatively higher pain
thresholds (Alden, Dale, & DeGood, 2001; Cogan, Cogan, Waltz,
& McCue, 1987) and lower blood pressure reactivity to a stressful
task (T. W. Smith, Ruiz, & Uchino, 2004). Happy moods may also
promote health by boosting self-efficacy, optimism, and efforts to
battle illness. Participants who imagined being diagnosed with
kidney cancer and then induced into a pleasant mood reported
greater ability in managing the illness, more optimism about their
prognosis, and stronger intentions to follow the treatment regimen
and exert effort to overcome the illness than those induced into a
negative mood (Schuettler & Kiviniemi, in press, also cited
earlier).
LYUBOMIRSKY, KING, AND DIENER
838
Healthy Behavior
An intriguing line of research suggests that positive moods
might help people exert willpower and self-control over unhealthy
or harmful urges and addictions. For example, Tice and Wallace
(2000) showed that inducing positive mood replenishes the depleted ego, allowing individuals to demonstrate will power once
again after it has been worn down by temptation. This finding is
consistent with a correlational study of smoking cessation, which
found positive affect to be negatively associated with urges to
smoke in those withdrawing from smoking (Zinser, Baker, Sherman, & Cannon, 1992).
Immunity
Research on induced mood and immune activity provides some
support for a causal relation between positive moods and immune
function. For example, in several investigations, participants who
had watched a humorous videotape showed increased levels of
immunity (Dillon et al., 1985; Lefcourt, Davidson-Katz, & Kuenemen, 1990; McClelland & Cheriff, 1997; however, see Martin,
2002, for a critique of these data). Furthermore, in a small sample
of trained actors, induced positive and negative mood were found
to be related inversely to changes in immune function (Futterman,
Kemeny, Shapiro, & Fahey, 1994). That is, level of proliferative
response to phytohaemagglutininantigen, a marker of immune
function, increased in response to positive mood and decreased in
response to negative mood (see also Solomon, Segerstrom, Grohr,
Kemeny, & Fahey, 1997).
Creativity and Problem Solving
Flexibility and Originality
Does a happy mood prompt a person to be more original and
more flexible in his or her thinking? Many investigators, led by
Isen and her colleagues, have shown that laboratory inductions of
positive affect lead to elevated scores of originality and flexibility,
often labeled creativity in these studies. The manipulations used to
induce positive moods have been diverse, and several different
types of assessments of flexible and original thinking have been
used (e.g., Estrada, Isen, & Young, 1994; Hirt et al., 1996; Isen,
Johnson, Mertz, & Robinson, 1985; Sinclair & Mark, 1995). It
should be noted that, occasionally, people in a sad mood are also
more original than those in a neutral mood (Adaman & Blaney,
1995). However, in most studies, it is the positive group that shows
the most original responses. Isen (1993) reviewed the extensive
evidence linking induced positive affect to creativity on laboratory
measures and concluded that there is little doubt that induced
positive affect, compared with neutral affect, heightens performance on the laboratory tasks.
In conclusion, the laboratory findings on induced positive
moods suggest that pleasant emotions enhance performance on
simple measures of flexible thinking and originality. What are the
mechanisms by which positive affect leads to creativity? The
association might be due to the fact that positive moods make the
person feel safe and secure, and, therefore, lead him or her to think
in more divergent ways without feeling threatened—in other
words, to be more playful (Fredrickson, 1998, 2001). Kahn and
Isen (1993) found that individuals put in a good mood sought more
variety in their choices, suggesting the role of feeling secure and
wanting to try new things as a causal mechanism for the effects of
positive affect on creativity.
Performance on Complex Mental Tasks
The data reviewed previously persuasively suggests that positive affect enhances creativity. Does positive affect also boost
performance on complex mental tasks? The experimental evidence
regarding this question is rather mixed. One body of evidence
indicates that positive affect might be detrimental to accurate
judgments and logical, rational decision making. Early research on
affect and judgment suggested that people in a positive mood
might perform more poorly, compared with those in neutral or sad
moods, at decision and judgment tasks. Those induced to feel
positive affect have been shown, for example, to do worse at logic
problems (Melton, 1995) and to be less likely to differentiate
strong from weak arguments in a counterattitudinal essay paradigm (Mackie & Worth, 1989). In contrast, individuals induced to
be in a sad mood are more likely to value the quality of arguments
over the source (Bless, Bohner, Schwarz, & Strack, 1990), less
likely to rely on stereotypes (Edwards & Weary, 1993), and more
likely to carefully execute all steps in a highly structured task
(Elsbach & Barr, 1999). Furthermore, the literature on depression
suggests that people in normal moods, as compared with dysphoric
people, are often more likely to overestimate their degree of
control (Alloy & Abramson, 1979). However, it should be noted
that tests of the depressive realism hypothesis have yielded mixed
results, with about as many studies inconsistent with the idea as
there are supporting it, depending on the outcome measured (e.g.,
Dobson & Pusch, 1995; see Ackermann & DeRubeis, 1991, for a
review).
Other studies, however, have shown that those put in a pleasant
mood outperform others. For example, people in a positive mood
made faster and more efficient decisions regarding a personally
relevant task (Forgas, 1989), performed better on a clerical errorchecking task (Jundt & Hinsz, 2001), solved more anagrams
correctly (Erez & Isen, 2002), and considered the correct diagnosis
of a disease earlier (Estrada, Isen, & Young, 1997). The results of
other studies also suggested more efficient processing—that is,
participants placed in a positive mood were less likely to review
information they had already seen, were more likely to ignore
information judged as unimportant (Isen & Means, 1983) and to
adopt an efficient strategy for performing a clerical coding task
(Baron, 1990), and showed less anchoring when making a diagnosis (Estrada et al., 1997). In addition, the respondents high in
positive affect tended to eliminate alternatives that did not meet a
minimum cutoff on important dimensions, a more efficient strategy. People in induced happy moods also appear to persist longer
at tasks in which perseverance is required (Erez & Isen, 2002;
Kavanagh, 1987). Finally, people in a good mood have been
shown to make more inclusive group representations, defining
others as part of their in-group (Dovidio, Gaertner, Isen, & Lowrance, 1995; Isen & Daubman, 1984) and using a broader definition of group membership (Urada & Miller, 2000). Thus, individuals in a happy mood are more likely to use stereotypes, but they
are also more likely to include more diverse people within their
groups.
BENEFITS OF FREQUENT POSITIVE AFFECT
Complicating the picture, another body of evidence suggests
that, although individuals in a sad mood often perform well at
simple analytical tasks, they are not immune to errors. For example, sadness can open the decision maker to greater anchoring
effects (Bodenhausen, Gabriel, & Lineberger, 2000), because
greater analytical processing can make the anchor more salient.
Indeed, Staw and Barsade (1993) concluded that the evidence on
decision making and mood supports the happier-and-smarter effect
rather than the sadder-but-wiser hypothesis.
Heuristic versus analytical processing. Based on the research
reviewed previously, it appears that sometimes the performance of
people in positive moods is superior, sometimes equal to, and at
other times inferior to mildly depressed people and those in a
negative mood. How can we make sense of this seemingly contradictory evidence? One conclusion is that the experience of
positive affect is not beneficial—and perhaps harmful—when one
is engaged in mental tasks. Another response to the mixed evidence is to try to determine in which situations people in a happy
mood do better at judgment and decision problems and in which
situations they do worse. In recent years, a perspective has
emerged that people in positive moods interpret their affect as
signifying that events are going well. Thus, they are quicker to
make decisions and are likely to use general heuristic answers
learned in the past. After all, if all is well, then past successful
answers are likely to work. Thus, the person in a positive mood is
likely to rely on preexisting general knowledge structures (Bless et
al., 1996) that have previously succeeded, because the situation is
seen as predictable and safe. In contrast, people in negative moods
are likely to process problems analytically and vigilantly.
Heuristic shortcuts can be likened to mental habits, which allow
for less effortful processing. Because heuristic answers are efficient when they are appropriate to the task, people in happy moods
can solve complex tasks better and faster, thus freeing cognitive
capacity for other challenges. At the same time, when researchers
present respondents with analytical tasks for which past heuristics
are not suitable, the performance of sad participants is likely to be
superior, especially when no task performance feedback is involved. Because sad individuals are more likely to use effortful
and detailed processing for every task, they will do better at
problems for which past learning is not particularly helpful. However, the effortful processing of sad people will not be desirable for
complex tasks on which efficient strategies learned in the past can
be used. For instance, Isen and Means (1983) found that people
induced to feel happy were better at performing a complex mental
task—namely, eliminating unimportant information and discovering useful heuristics to help solve a difficult problem. Sad individuals, in contrast, are more likely to ignore heuristic shortcuts
and to use effortful, vigilant processing even when it is not
required, and therefore perform poorly in complex and timelimited situations (Gleicher & Weary, 1991). For example, in a
recent study, sad participants displayed reduced accuracy of social
judgments based on thin slices of nonverbal behavior (Ambady &
Gray, 2002). The authors showed that sadness impaired accuracy
by promoting a deliberative style of processing information, which
can interfere with a person’s ability to understand others.
Notably, happy moods can produce good performance even on
complex and novel tasks, but only when cues are present to
indicate that the situation is important and that care is required.
That is, because positive affect signals that all is well in the
839
situation, when novel problems are encountered, individuals in a
pleasant mood require information indicating that they need to
exert additional effort, to consider new and careful strategies, and
not to rely on preexisting mental structures. As Schwarz (1990)
noted, people in good moods see little need to expend effort unless
it is necessitated by currently active goals. However, cues about
motivation, an explicit goal to be accurate, or the negative affect
that is engendered by initial failures at the task can all motivate the
happy person to engage in more effortful processing when it is
needed. Thus, when the situation calls for it, a person in a positive
mood is capable of slowing down and analytically thinking
through a problem in a more careful and deliberate way. For
example, people placed in a positive mood overcame their stereotypes if they learned they would be held accountable for their
decisions (Bodenhausen, Kramer, & Süsser, 1994).
A number of studies support this argument. For example, research participants who are put into a good mood seem to make
riskier judgments if nothing is at stake, but make more conservative bets when real losses are possible (see Isen, 2000, for a
review). Aspinwall (1998) reviewed evidence suggesting that people in a positive mood do not ignore negative information if it is
important and self-relevant. She hypothesized that happy people
will use heuristics in many laboratory tasks that appear to be
unimportant, but will use more systematic processing when the
task is important and self-relevant (e.g., Forgas, 1989). For example, those put in a positive mood were less likely than those in a
control condition to ignore self-relevant medical information about
their risky health behaviors, and were better able to recall the risk
information at follow-up (Reed & Aspinwall, 1998). In another
study involving an important, self-relevant situation, students who
had undergone a positive experience were more open to receiving
feedback regarding their liabilities in reaching their life goals and
their careers, whereas those undergoing a negative experience
showed greater interest in hearing about their assets (Trope &
Pomerantz, 1998). These results indicate that, in a situation in
which people’s weaknesses are related to important life goals,
having a positive experience can lower ego defensiveness and
make people more open to learning about their weaknesses.
Further support of the notion that happy moods can instigate
careful processing, but only when appropriate cues are present,
comes from research showing that people in a good mood will do
better if the task is more ecologically valid. For example, in one
study, depressed respondents made relatively less realistic predictions about future events in their own lives in the upcoming
semester (Dunning & Story, 1991). That is, depressed participants
were less accurate in their predictions, and more overconfident
than nondepressed individuals, when predictions were of future
events in their own lives rather than predictions of laboratory
stimuli (for mixed evidence, however, see Shrauger, Mariano, &
Walter, 1998). Supporting the argument that positive affect is
likely to be helpful in natural settings, several researchers have
concluded that depressive realism is found in trivial, artificial
laboratory tasks (Dobson & Franche, 1989; Pacini, Muir, & Epstein, 1998). The authors argued that dysphoric individuals use
excessive rational control even in trivial situations, leading to their
superior performance in certain inconsequential laboratory tasks,
but that nondysphoric individuals perform more optimally in consequential contexts. Corroborating this conclusion, people in an
induced positive mood were found to take more risks when the
LYUBOMIRSKY, KING, AND DIENER
840
stakes were low, but to be more risk averse when the stakes were
high (Isen & Geva, 1987; for similar findings, see Isen & Patrick,
1983; Leith & Baumeister, 1996).
Summary. In conclusion, happy moods are not a panacea when
it comes to solving problems or tackling laboratory tasks. Happy
people’s reliance on simple heuristics is a handicap if they are
attempting a novel task for which previous knowledge is not
useful. On the other hand, their more frequent use of mental
shortcuts allows them to allocate additional resources to secondary
tasks, thus, permitting them to use their time and resources more
efficiently and to perform well at complex problems (Isen, 2000).
Furthermore, people in a positive mood are more likely to have
richer associations within existing knowledge structures, and thus
are likely to be more flexible and original. Those in a good mood
will excel either when the task is complex and past learning can be
used in a heuristic way to more efficiently solve the task or when
creativity and flexibility are required. However, many laboratory
activities provide little or no feedback to participants on how they
are performing on the task, and, thus, the happy person has no clue
in those studies that things are going poorly. In contrast, research
suggests that, in everyday, naturalistic situations, a person in a
happy mood will quit relying on heuristics when he or she sees that
they are not working. In summary, the evidence shows that people
experiencing happy moods have potential deficits when it comes to
problem solving, but they can overcome these deficits if they are
motivated to perform well at the task.
CONCLUSION
To sum up then, we return to our initial question: Does positive
affect promote positive, favorable characteristics? Our review of
the relevant experimental literature reveals compelling evidence
that positive affect fosters the following resources, skills, and
behaviors: sociability and activity (mean r ⫽ .51), altruism (mean
r ⫽ .43), liking of self and others (mean r ⫽ .36), strong bodies
and immune systems (mean r ⫽ .38), and effective conflict resolution skills (mean r ⫽ .33). The evidence is weaker, but still
consistent, that pleasant moods promote original thinking (mean
r ⫽ .25). It is fair to say that the evidence is almost nonexistent
regarding whether individuals induced to experience happy moods
also have superior coping abilities, greater popularity, and healthier behavior. Finally, positive affect sometimes leads to poor
problem solving and sometimes to more efficient solving of complex tasks, depending on the situation. It is intriguing, however,
that despite the presence of some contradictory results, the mean
effect size for performance on complex mental tasks is .25.
Summarizing the Evidence
In this article, we set out to document three classes of evidence
to test our conceptual model, positing that happiness, or the longterm propensity to experience frequent positive emotions, promotes culturally valued success and thriving (see Figure 1). To this
end, we documented the cross-sectional, longitudinal, and experimental literature examining happiness and positive affect and
their associations with successful outcomes, as well as with behaviors paralleling success. Although our review revealed gaps in
the existing research, it also highlighted the robustness and wide
range of the relationships that were observed. First, as indicated by
the consistently strong average effect sizes, we discovered a vast
number of correlational studies showing positive associations between happiness and successful outcomes within all of the major
life domains (i.e., work, love, health). Second, cross-sectional
work indicated copious positive relations of happiness and positive
affect with an array of desirable attributes, propensities, and behaviors (e.g., positive perceptions of self and other, sociability,
prosocial behavior, likability, creativity, and coping, among
others).
Third, although the longitudinal literature was found to be quite
limited— especially when compared with the cross-sectional body
of evidence—it was persuasive in showing that many of the
correlations we had documented were replicated within the temporal sequence predicted by our model. That is, a number of
studies demonstrated that (a) long-term happiness precedes the
successful outcomes with which it correlates and (b) both longterm happiness and short-term positive affect precede the desirable
resources and characteristics with which they are related.
Finally, and perhaps most important, a sizable experimental
literature offered strong evidence that short-term positive affect—
the hallmark of a happy person— causes a range of behaviors
paralleling success. These data suggest that positive affect may
very well be the critical mediator underlying the relationship
between happiness and culturally valued success. In summary,
although many researchers presuppose that happiness follows from
successes and accomplishments in life, our review provides strong,
albeit not conclusive, evidence that happiness may, in many cases,
lead to successful outcomes, rather than merely following from
them.
Questions, Caveats, and Future Research
The evidence presented here highlights the functional benefits
of positive affect and chronic happiness. It would be absurd,
however, to suggest that chronic happiness is necessary for all
forms of success and thriving. Plenty of exceptions are in evidence. The conclusion we draw is much more modest—that positive affect is one strength among several that can help achieve
approach-oriented success. Certainly other resources, such as intelligence, family connections, expert skill, and physical fitness,
can also figure prominently in success. In this section, we discuss
questions arising from our preliminary conceptual framework,
bring up several potential limitations and empirical issues, and
outline the important empirical research that is needed to address
the remaining issues.
Methodological and Generalizability Issues
Experimental and Longitudinal Designs
More experimental and longitudinal research is needed in a
number of areas to fill the gaps in our review and to provide a
stronger test of our conceptual model. For example, although a
substantial amount of experimental research has been conducted in
the areas of creativity and altruism, less experimentation exists on
the effects of positive affect on likability, coping, and health.
Furthermore, few or no longitudinal studies exist in many areas,
including friendship, judgments of others, organizational citizenship, negotiation, and performance of mental tasks. Longitudinal
BENEFITS OF FREQUENT POSITIVE AFFECT
research is also essential to confirm that positive affect predicts
success even after controlling for earlier levels of resources and
success. Cross-sectional studies, in which outcomes are simply
correlated with happiness, might produce spurious findings that are
due to the causality running from the variable to happinessor the
presence of third variables. For this reason, it is important to
consider longitudinal studies that examine the effects of happiness
on outcomes while controlling for happiness at Time 1 or for
potential third variables at Time 1. For example, baseline health
might be controlled in a study of the effects of happiness on
longevity. Although this procedure has not always been followed
in the studies we review, and represents a serious limitation of
some investigations, it should be a high priority for future research.
Finally, the existing evidence for a causal link between positive
affect and behaviors that lead to success currently comes from
short-term laboratory studies (Type C evidence in Figure 1). If
these same behaviors are also increased by long-term interventions
to enhance global happiness and happy moods (e.g., through
self-help, therapy, or drug treatment)—that is, collect evidence of
Type D—the case for happiness being causally related to success
will be strengthened even more.
Reporting Biases
A good portion of the evidence presented in this article involves
self-reports, which are prone to the biasing effects of mood. That
is, an individual in a happy mood is likely to rate everything as
positive, including herself, her health, her job, her coping abilities,
and her marriage. Such potential reporting biases may render some
of the reviewed findings to some extent ambiguous. This is undoubtedly a limitation of the evidence. Fortunately, however,
many of the outcomes we reviewed are not dependent on global
self-reports. Among others, these include mortality data, immune
marker levels, income, job supervisor ratings, peer judgments,
marital status, and laboratory measures of creativity, task performance, and helping. Furthermore, positive mood biases may sometimes not be artifactual, but, instead, may represent the phenomenon in question. Clearly, more non–self-report measures of key
variables are needed in future studies.
Assessing Happiness and Positive Affect
Can we be certain of the validity of the happiness measures used
in the literature reviewed here? Recall that our conceptual model
rests on a definition of happiness as the frequent experience of
positive emotions. In the studies we review, some of the long-term
measures assess happiness, others more directly assess the longterm experience of positive affect, and yet others assess what
Veenhoven (1984) labeled the “hedonic level of affect” and what
Bradburn (1969) called “affect balance”—the experience of positive emotions minus negative emotions. Regarding measures of
happiness, Diener and his colleagues (1991) reported that individuals scoring high on such scales do indeed experience frequent
positive emotions. Studies using hedonic-level-of-affect measures
also provide a test of our model—albeit a less direct one— because
positive affect represents half of such scores. Although negative
affect is also included in affect balance measures, the outcomes we
review (such as sociability) are likely to result from positive affect.
841
What about measures of positive affect such as the PANAS
(Watson et al., 1988), whose items (e.g., excited, active) might be
the ingredients leading to success rather than pleasant emotions per
se? Although an important topic for future research is dissecting
the various types and components of positive emotions, there is
reason to believe that positive emotions, not merely its components
like energy or arousal, play a causal role. First, experimental
manipulations of positive affect produce similar outcomes, and
many of these manipulations (e.g., receiving a small gift or listening to soothing music) are unlikely to produce high levels of
arousal or activation. Second, measures of less activated forms of
positive emotion such as happy or content produce effects that are
consistent with those found with the whole PANAS. Thus, positive
emotions do appear to be an active ingredient leading to successful
outcomes, although researchers need to explore further the augmenting role of arousal/energy and the possibly diverging role of
various specific types of positive emotions. For example, high- and
low-arousal positive emotions may activate different types of goals
and behaviors, such as the goals of influencing versus adjusting to
one’s environment, respectively (Tsai, Knutson, & Fung, 2004).
Alternative measures of positive affect that have been included
in studies reviewed here include facial expressions of positive
emotion and positive emotional language usage. Research using
such measures is not susceptible to self-report biases and is relatively free from the conceptual ambiguities that characterize our
current understanding of the structure of positive emotion. That
studies using these more subtle measures have supported the
relations of positive affect to valued life outcomes (and have
typically done so longitudinally) strengthens the case for the
contribution of positive emotional experience in securing the
goods of life.
Generalizability
A critical question is the degree to which the findings presented
in this article generalize to other cultures. The majority of the
evidence we reviewed comes from Westernized, industrialized
nations, where positive emotions are highly valued (e.g., Eid &
Diener, 2001). Other cultures, by contrast, give less emphasis to
happiness and its pursuit (Lyubomirsky, 1997; Suh, 2000) and
hold different definitions of success. It is possible then that the
characteristics that follow from positive emotions, such as selfconfidence, activity, sociability, and original thought, are more
likely to lead to success in some societies than in others. For
example, cultures centered around the idea of avoiding bad outcomes rather than approaching good ones may be less likely to
reward those who are high in positive affect. Happiness might lead
to outcomes that are considered beneficial only in particular types
of societies that happen to be where most research to date has been
conducted. Alternatively, the relation between positive affect and
success behaviors may also be universal across cultures or may be
nearly universal in resource-rich societies. Furthermore, perhaps
all cultures value the three domains of success we posit—work
life, social relationships, and health— but they prioritize them
differently. Thus, an important objective for future research is to
collect cross-cultural data so that the limiting conditions of our
framework can be understood.
842
LYUBOMIRSKY, KING, AND DIENER
Situational Specificity
Although we found consistent effects for happiness across all
three classes of evidence, there was significant heterogeneity
across studies in a number of areas, suggesting the need for future
research to explore moderators of the effects of happiness and
positive affect. For example, although Diener and colleagues
(2002) found that happier college students earned more income
many years after leaving college, this effect was moderated by
parental wealth, with richer students benefiting more from being
happy. Furthermore, there are times when being flexible, sociable,
and optimistic might not be appropriate, and might distract one
from the task at hand. For example, some clerical or accounting
jobs might require a person who is asocial and quiet as well as very
careful about errors and who strictly follows rules. Lucas and
Diener (2003) discussed the types of jobs that might most profit
from happy workers and those vocations in which happiness might
be less of an advantage.
In summary, perhaps the most important limitation to our conclusions is that being happy is more adaptive in certain situations
than in others. For example, happiness may be most functional
when it occurs in benign life circumstances and may be less
helpful during dangerous times. Nonetheless, the advantages of
happiness reviewed in this article are rather striking, and a major
task for future research will be to determine whether these benefits
always accrue or whether circumstances exist in which a dysphoric
personality leads to greater success.
Causality and Possible Third Variables
We found in our review that experimental studies generate the
same basic conclusions as the cross-sectional and longitudinal
research. Yet, a question nags: Could happy people be successful
simply because they possess more resources in the first place,
which is the reason they are happy? Certainly, some of the effects
we review may be due to some degree to the effects of beneficial
circumstances on happiness (e.g., Headey & Veenhoven, 1989).
The longitudinal research, however, suggests that this is not the
complete explanation because happiness often long precedes the
successful outcomes. For example, happiness in college (long
before the person enters marriage or the workforce) precedes
higher income and a more satisfying marriage many years later,
even when Time 1 factors are controlled. Furthermore, in an
18-month longitudinal study that used causal modeling to test two
competing models—that is, happiness as influencing five of its
correlates versus the reverse—the results supported the happinessas-cause model for 17 out of 18 predictions that differentiated the
models (Stones & Kozma, 1986). Nevertheless, the possibility
remains that individuals with certain personal resources such as
good social skills, high activity levels, self-efficacy, and creativity
are likely to be more successful at an early age, and, hence, to
maintain and reinforce their success and happiness at a later age
because they continue to have more personal resources and, therefore, more successes. Again, however, the laboratory experimental
studies suggest that this is not the entire explanation for happy
people’s success.
Furthermore, it is important to establish that positive affect is the
key variable associated with desirable characteristics and, ultimately, with successful outcomes—not the absence of negative
affect or depression. Some studies are able to address this question
directly, as they include both positive affect and negative affect as
variables or manipulations. For example, in the helping literature,
experimental inductions of positive affect produce increased
prosocial behavior, whereas inductions of negative affect do not
necessarily decrease helping (e.g., Aderman, 1972; Berkowitz,
1987; Isen & Levin, 1972; Rosenhan et al., 1974). Regarding
social interactions (e.g., Cunningham, 1988a, 1988b), creativity
(e.g., Hirt et al., 1996; Richards, 1994), and evaluations of strangers (e.g., Baron, 1987, 1993), it appears that positive mood inductions do not produce symmetrical effects. Experimental laboratory
research—for example, on helping, creativity, and task performance—also often includes neutral mood conditions, which do not
parallel the effects of happy mood (e.g., Berkowitz, 1987; Cunningham, 1988a; Estrada et al., 1994; Isen, 1970, 1993; Isen et al.,
1985; Rosenhan et al., 1974). As another example, some crosssectional and longitudinal studies show significant effects of positive affect, but not negative affect—for example, on mortality risk
in the nun study (Danner et al., 2001), on likelihood of developing
a cold (Cohen et al., 2003), or on organizational citizenship (Credé
et al., 2005). In summary, many of the effects we describe in this
article cannot be attributed simply to the absence of negative affect
in happy people, although it is possible that some of the effects are
due to lack of negative affect. Disentangling the effects of positive
affect from lack of negative affect or depression should be a goal
of future research, as many studies, such as in the areas of immunity and health, still consistently fail to include measures of positive emotion.
Further evidence that the effects reviewed here are not simply
due to unspecified third variables comes from within-person studies, which show that positive moods correlate over time with
desirable outcome variables. On the days or moments when people
are in positive mood states, they are more likely to feel and behave
in certain ways than when they are in negative mood states.
Although studies of within-person patterns are not conclusive
proof of causality, they add yet another type of evidence from
which the effects of positive emotions can be inferred. In summary, taken together, a variety of different sources of evidence
suggest that positive affect leads to certain outcomes rather than
simply being caused by them. Nonetheless, longitudinal and longterm experimental studies, which assess a variety of personality
characteristics, as well as positive emotions and outcomes, would
advance understanding of the intricate relations between personal
attributes and chronic predispositions to positive affect.
Process Issues
Mediation
One conclusion from our review of the empirical evidence is
that most of the effects of being happy are due to the fact that
happy people experience positive moods most of the time and, by
definition, experience them more than unhappy people. However,
happy people might possess certain characteristics and behavioral
propensities that are helpful even in the absence of a positive
mood. Although little is known at present about the genetic predispositions characterizing chronically happy individuals, we cannot discount the possibility that long-term happiness may be directly linked—perhaps through inborn correlates—with particular
BENEFITS OF FREQUENT POSITIVE AFFECT
desirable outcomes or characteristics (e.g., extraversion, optimism,
sociability). As a result, these qualities may be evident and may
produce beneficial results even when chronically happy people are
in neutral or even unpleasant moods.
An alternative and persuasive perspective of the role of positive
affect as mediator of the happiness–success relation comes from
Fredrickson’s (1998, 2001) broaden-and-build model. She suggested that positive emotions broaden our cognitive and behavioral
repertoire and allow for an accrual of resources, the learning of
new skills, and so forth. In our framework, the experience of
positive affect is critical—that is, individual differences in longterm happiness may influence the ease with which a person enters
a “good mood” (cf. Larsen & Ketelaar, 1991), but the affect itself
is the key to the positive outcomes associated with positive moods.
Thus, while happy people overall may be found to enjoy a variety
of positive outcomes, the frequent experience of positive mood (in
the absence of a temperamental disposition toward such moods)
should still convey benefits. Notably, because the key to success is
happy affect and not necessarily a happy genetic predisposition,
we submit that chronically unhappy people are therefore not fated
to failure. Another implication is that future happiness-increasing
interventions should focus on how people can adopt new practices
and habits, and restructure their lives, in ways that allow for a
stream of positive experiences and positive emotions (Lyubomirsky, Sheldon, & Schkade, 2005).
We know from the experimental studies that momentary positive emotions produce many of the outcomes we reviewed. We
also know from cross-sectional and longitudinal studies that happy
people exhibit behaviors that are parallel to the outcomes found in
the experimental studies. What we do not know, because there is
little research on mediation in this area, is the degree to which
people’s current moods mediate the effects of chronic happiness
on behavior. As mentioned previously, Fredrickson’s (1998, 2001)
model suggests that even in the absence of a positive mood—
indeed, even in a negative mood— happy people will generally
perform better on many tasks because of the skills they have
learned and resources they have accumulated because of their
frequent experiences of positive moods in the past (Fredrickson &
Joiner, 2002; Fredrickson et al., 2003). We suspect that this is a
case of partial mediation—namely, that happy people perform
many of the desirable behaviors we review because they are more
often in a pleasant mood, but that being happy in the past might
lead to the accumulation of skills, social support, other resources,
and adaptive habits that the happy person can use even when in a
negative mood. Thus, an individual’s current mood is likely to
produce certain benefits, but current mood might not entirely
explain the successful performance of happy people. It will be
important in future research to separate the effects of happy
temperament, happiness engendered by current life circumstances,
and induced happy moods on the characteristics we reviewed
earlier. Tests of the mediation hypothesis promise to be an exciting
direction for future scientific work.
The search for mediational variables might begin with an examination of the various outcomes we have examined here. In this
review, we have treated a variety of desirable life outcomes as if
they hold equal status in their overall importance in people’s lives.
It may be, of course, that these outcomes are themselves intercorrelated and perhaps even differentially important. For instance, the
social benefits of positive affect may be the central mediator of the
843
effect of positive affect on other life outcomes. Research that
combines a variety of life outcomes will be needed in order to
answer the important question of how these various “goods of life”
relate to and potentially promote each other.
The Varieties of Positive Affect
An important topic of investigation for the future involves
distinguishing the effects of positive affect at a general level versus
the effects of discrete positive emotions such as contentment,
affection, curiosity, elevation, pride, and joy. Specific emotions
may be linked with specific beneficial outcomes—for example,
contentment with originality, affection with sociability, pride with
helping, and curiosity with learning and problem solving—and
these possibilities remain an intriguing direction for future
research.
One important question concerns whether the effects of positive
affect that we review apply to all positive emotions or only to those
high in arousal. In the case of positive emotions, we can ask
whether the outcomes reviewed in this article apply to contentmentor only to elation and joy. The work of Watson (2000)
suggested that feelings of energy and activity are much more likely
to accompany elation than they are to accompany contentment.
However, little more is known about the effects of the two types of
affect, and whether individuals who have chronic tendencies to
contentment will be as successful as those who are prone to joy.
An interesting finding in this regard comes from a study that
predicted work outcomes at age 26 from reports of emotions at age
18 (Roberts et al., 2003). The authors found that occupational
attainment was predicted by both positive affect– communion and
by positive affect–agency, whereas financial independence was
significantly predicted only by positive affect– communion. In the
affect literature, the distinction between moods and emotions is
often seen as pivotal. However, in the literatures that we reviewed,
the two are rarely, if ever, separately measured. Thus, we are
unable to draw conclusions about whether a propensity to positive
moods versus emotions is more conducive to the outcomes we
describe. For example, the possibility exists that the types of
emotions induced in the experimental studies stand out as figure
against ground and are more likely to produce the effects outlined
in this article. On the other hand, moods are relatively longer
lasting and are less likely to be in focal awareness; therefore,
relative to emotions, moods may influence behavior in more subtle
ways. Once again, assessing moods versus emotions and examining their discrete effects on the behaviors we review, and on
various types of success, is an important avenue for future
research.
Future Research Questions
Additional questions for research are needed to extend the
pattern of findings we describe here and to support the unifying
framework we present. Because positive affect has often been
treated as an outcome rather than a predictor of the goods of life,
the potential benefits of positive affect, itself, have remained
largely untested. Hence, research should begin to address the
potential causal role of positive affect in securing positive life
outcomes. In addition, examining positive affect in this way opens
a variety of new questions for research on the positive benefits of
844
LYUBOMIRSKY, KING, AND DIENER
positive affect. For example, what types of success are most
enhanced by positive affect? Are there long-term beneficial outcomes in some areas for unhappy people? Are different outcomes
likely for individuals who are prone to experience different forms
of positive affect, such as joy, affection, or contentment? What are
the control processes that prevent positive affect from amplifying
in a cycle with success and moving ever upward to dysfunctional
levels? At the broadest level, what is the optimal level of positive
affect in different tasks, contexts, and cultures? Our hope is that
our review stimulates research that examines each of these questions in detail.
Is Positive Affect a Magic Elixir?
Readers of our review might conclude that happiness and positive affect are the royal road to the perfect life. Leaving this
impression is not our intent. There are a number of ways that
positive emotions can produce adverse effects. For one thing, in
some situations, positive affect is not the most functional response.
For another thing, happy people might use their creativity, selfconfidence, negotiation ability, and sociability to achieve aims that
are not beneficial to society, such as being the “king” of the local
bar or even to achieve aims that are harmful to society, such as
being an effective confidence man. It follows from our review, for
instance, that a happy member of the Mafia might be more effective than an unhappy one, and a happy scam artist might be more
effective at committing fraud without being caught. Thus, success
must be defined in terms of a cultural and behavioral context, and
positive emotions might not lead every individual to be successful
at goals that the broader culture or the world believes are desirable.
We are aware that many mildly dysphoric individuals function
very well in society. They write newspaper columns, run psychology departments, act in popular movies, argue before the U.S.
Supreme Court, and perform many other jobs with distinction.
Qualities such as intelligence, perseverance, conscientiousness,
and social criticism of the status quo are desirable characteristics in
many situations, and are to some degree separable from positive
affectivity. A happy person with these characteristics might be
very effective in many vocations and roles, but some situations
might exist, as yet undefined, in which mild dysphoria leads to
superior functioning.
It is important to keep in mind that human emotional life is rich,
and that the relations of positive affect and negative affect to
functioning are complex ones. At times, happiness will be most
adaptive and at other times may require a level of misery or at least
discontent. Our framework suggests that positive bias in a flexible
system may well be adaptive, but an exclusively happy life is not
only unrealistic—it is not necessarily the most desirable life.
A commonly expressed claim is that happy people are satisfied
with the status quo and are not motivated to accomplish new goals
or to “change the world.” The data reviewed in this article indicate
that this blanket condemnation of happiness is inaccurate— happy
people perform well in many areas of life, including domains such
as work and income, that require motivation and persistence.
Happy people can have lofty goals and experience positive affect
that is due to the progress they make toward those goals. At the
same time, specific dissatisfactions can also motivate happy people
to work for change and to pursue new directions. Andrews and
Withey (1976) found that people who are happy with their lives are
not inevitably satisfied when they judge the conditions in society;
they found that satisfaction with one’s life and with society and
government were distinct. Furthermore, many of the characteristics observed in happy people— optimism, energy, social engagement, originality, altruism, likability, productivity, good health—
are the very characteristics that could help them improve the
conditions of theirs and others’ lives.
In summary, although happy people are generally more satisfied
people, this does not appear to prevent them from being achievement oriented. Indeed, happy people appear to be relatively more
likely to seek approach goals. The interaction of cognitive judgments about the desire for change with the propensity for positive
affect is a ripe area of inquiry for the future.
Do Happy People Experience Negative Emotions?
If happy people were unable to experience negative emotions
when things go wrong, their responses would likely be dysfunctional because they might not react appropriately to threats, losses,
and other significant negative events. If, on the other hand, happy
people can occasionally experience negative emotions, as we suggest they do, they might be particularly successful because they
can be approach focused most of the time, but not when conditions
become adverse. Thus, happy people can remain in a positive
mood as long as things are positive or neutral, but experience a
negative mood when things are very bad, thus motivating them to
withdraw, conserve resources, or otherwise avoid harm. Furthermore, there may be a resetting point around a person’s current
circumstances so that people are most likely to react with negative
affect when conditions worsen from their current state (Kahneman
& Tversky, 1979).
The negative affect produced by bad events causes a change in
thoughts, feelings, and behaviors. When adverse events occur,
people quit using heuristic processing and switch to vigilant and
careful analytical processing, which does not involve an overreliance on previous solutions to challenges. The person needs to
safeguard resources and focus on solving the immediate problem.
At the same time, it is functional for the person to return to a
positive state when conditions improve. Extending the ideas of
Fleeson (2001), happiness could be considered a “density function” in which people vary in terms of how much they are in the
state of positive experience. Although frequent experience of this
state appears to be functional, an ability to react to significant
negative events is also likely to be beneficial. Thus, even happy
people show substantial variations in their moods over time. Research confirms that the happiest individuals do feel occasionally
unhappy. For example, Diener and Seligman’s (2002) happiest
college students all displayed ups and downs in their moods, but
stayed in the positive zone the majority of the time. However, the
findings showed that they also occasionally descended into the
negative range and experienced unpleasant emotions, indicating
that the happiest individuals are not trapped in a positive mood
regardless of circumstance. We found the same pattern in the
World Value Survey (1994)—most of those responding with a 10
on a 10-point life satisfaction scale (the top 14% of respondents)
reported having experienced a negative mood or emotion during
the past few weeks.
In a laboratory study, chronically happy people reported negative feelings (such as being sad, anxious, and discouraged) in
BENEFITS OF FREQUENT POSITIVE AFFECT
response to negative feedback about their own performance (Lyubomirsky & Ross, 1997). The fact that happy people can and do
respond emotionally to events may provide part of the answer to
why they are likely to succeed in life. Unlike in short-term mood
manipulation studies, in which an induced positive mood often
elicits an inappropriate response to the situation, in everyday life,
happy people can react negatively when it is appropriate to the
context, but later return to a positive state.
Costs and Trade-Offs of Happiness
Despite the many benefits of long-term positive affect described
in this article, happiness can have costs or downsides in some
situations and, in other situations, have trade-offs with other desired values. Happy people are characterized by certain behaviors,
as reviewed previously, and, in some situations, these characteristics may prove detrimental. For example, if a happy individual
uses a heuristic to solve a frequently encountered problem, but the
heuristic now provides the wrong answer and there is no failure
feedback available in the situation, he or she will perform more
poorly than an unhappy person. As discussed earlier, this possibility likely accounts for findings of “depressive realism” in some
studies (Alloy & Abramson, 1979), as well as for the findings that,
under some conditions, happy people show more stereotypical
thinking because they rely on heuristic shortcuts (e.g., Edwards &
Weary, 1993). To the extent that relying on shortcuts leads to
nonoptimal performance, individuals in a positive mood may suffer. Clearly, the social costs of relying on stereotypes to make
decisions may be great.
In addition, because positive moods signal to the individual that
things are going well, less happy individuals may be superior at
critical thinking and error checking (e.g., Mackie & Worth, 1989;
Melton, 1995). Thus, it is unlikely that one particular mood state
leads to superior problem solving or task performance in general—
rather, positive affect and negative affect probably have differing
effects on cognitive processing that may or may not be well suited
to a particular task. Lucas and Diener (2003) suggested that mildly
dysphoric individuals are likely to underperform in leadership and
social tasks, but might excel in jobs such as monitoring a nuclear
power plant where constant vigilance for possible problems is
absolutely essential. Clearly, the relation of moods to decision
making and problem solving is complex and the match between
individual differences and situational requirements may determine
the adaptive significance of any emotional style.
Earlier we suggested that happy people may feel positive emotions more frequently because they are relatively more sensitive to
rewards in their environment. Tying positive emotionality to
Gray’s (1994) “behavioral approach system” makes a good deal of
sense and it also highlights potential pitfalls of happiness. Clearly,
the complexity of human life requires that one avoid some circumstances, and always moving toward evermore tantalizing rewards might lead an individual’s existence to devolve into hedonism or inappropriate risk taking. In addition, the tendency to
recognize and move toward rewards in the environment may make
a happy person susceptible to approach–approach conflicts, caught
between two potentially positive life paths.
In addition to the possibility that happy individuals might be
outperformed by their less happy peers in some situations, it is
worth noting that people make trade-offs in their decisions regard-
845
ing activities and happiness. For example, compared with European Americans, Asians and Asian Americans are more likely to
persist at a task at which they are not performing well in order to
master it and may thus suffer in terms of mood because they
continue working on something at which they are not proficient
(Heine et al., 2001; Oishi & Diener, 2003). Other researchers have
found that placing high importance on goals can heighten happiness when goals are achieved, but can also increase worry about
the goals and amplify greater negative affect when the goals are
not achieved (Diener, Colvin, Pavot, & Allman, 1991; Pomerantz,
Saxon, & Oishi, 2000). Happiness is one of life’s goods, but it
exists in the context of a variety of other goods (Ryff, 1989; Ryff
& Singer, 1998). Thus, individuals might well sacrifice happiness
in the pursuit of other valued ends. Notably, however, it may be the
happy who are particularly willing to sacrifice positive affect for
the sake of other goals, primarily because of the other resources
and capacities that have been afforded to them by the experience
of happiness.
Furthermore, particular circumstances or degrees of positive
affect may lead to decrements in performance. Recent work has
shown that extremely happy individuals perform slightly lower in
some achievement situations compared with very happy persons,
suggesting that the optimum level of happiness might vary depending on the task at hand (Diener, Oishi, & Lucas, 2005).
Extremely happy individuals might be inclined to be too sociable
to perform at the maximum level in some achievement situations
that occur over long periods of time.
Very happy individuals may also be judged harshly for their
apparent satisfaction—for example, as shallow or complacent.
Indeed, research has shown that happiness in the context of a
potentially lazy or meaningless life is judged quite negatively
(Scollon & King, 2004). It may be that the positive social perception of happy individuals depends on the particular situations in
which individuals encounter them. An apparently happy person
may be judged quite favorably in an acquaintanceship situation,
but an incongruously happy person may well be judged more
negatively. The capacity to downregulate positive affect may be a
facet of social skill and effective self-regulation (e.g., M. W. Erber
& Erber, 2001; R. Erber & Erber, 2000).
Although existing evidence indicates that happy individuals
indeed tend to be successful across a number of life domains, we
must be mindful that negative emotions can be functional under
some circumstances. Individuals who are temperamentally prone
to greater levels of negative emotions may help their groups under
some conditions. In addition, happiness in some circumstances
may be sacrificed in order to reach long-term goals. We do not yet
fully understand the limits of the success of happy people, and we
do not know the extent to which the effects of positive affect are
dependent on culture and cultural norms for emotion. The current
findings indicate that happy people are in many ways successful
people. This does not mean, of course, that happy people show
superior performance in every activity and situation.
Final Remarks
We have reviewed extensive evidence demonstrating that happy
people are successful and flourishing people. Part of the explanation for this phenomenon undoubtedly comes from the fact that
success leads to happiness. Our review, however, focuses on the
LYUBOMIRSKY, KING, AND DIENER
846
reverse causal direction—that happiness, in turn, leads to success.
Happy people show more frequent positive affect and specific
adaptive characteristics. Positive affect has been shown, in experimental, longitudinal, and correlational studies, to lead to these
specific adaptive characteristics. Thus, the evidence seems to support our conceptual model that happiness causes many of the
successful outcomes with which it correlates. Furthermore, the
data suggest that the success of happy people may be mediated by
the effects of positive affect and the characteristics that it promotes. It appears that happiness, rooted in personality and in past
successes, leads to approach behaviors that often lead to further
success. At the same time, happy people are able to react with
negative emotions when it is appropriate to do so.
The desire to be happy is prevalent in Western culture (e.g.,
Diener, Suh, Smith, & Shao, 1995; King & Broyles, 1997), and a
happy life is very much the preferred life (King & Napa, 1998). If
subjective well-being feels good but otherwise leaves people impaired, for example, in terms of decision making, social relationships, physical health, or success in life, we might question its net
value for society and for the individual. In this article, we reviewed
cross-sectional, longitudinal, and experimental data showing that
happy individuals are more likely than their less happy peers to
have fulfilling marriages and relationships, high incomes, superior
work performance, community involvement, robust health, and a
long life. The three classes of evidence also indicated that positive
emotions, as well as chronic happiness, are often associated with
resources and characteristics that parallel success and thriving—
that is, desirable behaviors and cognitions such as sociability,
optimism, energy, originality, and altruism. Although our conclusions run counter to the belief that successful outcomes and desirable characteristics are primarily the causes, rather than the consequences, of happiness, a surprisingly large amount of evidence
now appears to challenge this belief.
References
References marked with an asterisk indicate studies included in the
meta-analysis.
*Achat, H., Kawachi, I., Spiro, A., III, DeMolles, D. A., & Sparrow, D.
(2000). Optimism and depression as predictors of physical and mental
health functioning: The Normative Aging Study. Annals of Behavioral
Medicine, 22, 127–130.
Ackermann, R., & DeRubeis, R. J. (1991). Is depressive realism real?
Clinical Psychology Review, 11, 565–584.
*Adaman, J. E., & Blaney, P. H. (1995). The effects of musical mood
induction on creativity. Journal of Creative Behavior, 29, 95–108.
*Aderman, D. (1972). Elation, depression, and helping behavior. Journal
of Personality and Social Psychology, 24, 91–101.
*Alden, A. L., Dale, J. A., & DeGood, D. E. (2001). Interactive effects of
the affect quality and directional focus of mental imagery on pain
analgesia. Applied Psychophysiology and Biofeedback, 26, 117–126.
Alloy, L. B., & Abramson, L. Y. (1979). Judgment of contingency in
depressed and nondepressed students: Sadder but wiser? Journal of
Experimental Psychology: General, 108, 441– 485.
*Ambady, N., & Gray, H. M. (2002). On being sad and mistaken: Mood
effects on the accuracy of thin-slice judgments. Journal of Personality
and Social Psychology, 83, 947–961.
Andrews, F. M., & Withey, S. B. (1976). Social indicators of well-being.
New York: Plenum Press.
Antonovsky, A. (1988). Unraveling the mystery of health. San Francisco:
Jossey-Bass.
Antonovsky, A. (1993). The structure and properties of the sense of
coherence scale. Social Science and Medicine, 36, 725–733.
Argyle, M., & Martin, M. (1991). The psychological causes of happiness.
In F. Strack, M. Argyle, & N. Schwarz (Eds.), Subjective well-being: An
interdisciplinary perspective (pp. 77–100). Elmsford, NY: Pergamon
Press.
Aspinwall, L. G. (1998). Rethinking the role of positive affect in selfregulation. Motivation and Emotion, 22, 1–32.
Aspinwall, L. G., & Brunhart, S. M. (1996). Distinguishing optimism from
denial: Optimistic beliefs predict attention to health threats. Personality
and Social Psychology Bulletin, 22, 993–1003.
*Audrain, J., Schwartz, M., Herrera, J., Golman, P., & Bush, A. (2001).
Physical activity in first degree relatives of breast cancer patients.
Journal of Behavioral Medicine, 24, 587– 603.
*Bahr, H. M., & Harvey, C. D. (1980). Correlates of morale among the
newly widowed. Journal of Social Psychology, 110, 219 –233.
*Baldassare, M., Rosenfield, S., & Rook, K. S. (1984). The types of social
relations predicting elderly well-being. Research on Aging, 6, 549 –559.
*Bardwell, W. A., Berry, C. C., Ancoli-Israel, S., & Dimsdale, J. E. (1999).
Psychological correlates of sleep apnea. Journal of Psychosomatic Research, 47, 583–596.
*Baron, R. A. (1987). Interviewer’s moods and reactions to job applicants:
The influence of affective states on applied social judgments. Journal of
Applied Social Psychology, 17, 911–926.
*Baron, R. A. (1990). Environmentally induced positive affect: Its impact
on self-efficacy, task performance, negotiation, and conflict. Journal of
Applied Social Psychology, 20, 368 –384.
*Baron, R. A. (1993). Interviewers’ moods and evaluations of job applicants: The role of applicant qualifications. Journal of Applied Social
Psychology, 23, 253–271.
*Baron, R. A., & Bronfen, M. I. (1994). A whiff of reality: Empirical
evidence concerning the effects of pleasant fragrances on work-related
behavior. Journal of Applied Social Psychology, 24, 1179 –1203.
*Baron, R. A., Fortin, S. P., Frei, R. L., Hauver, L. A., & Shack, M. L.
(1990). Reducing organizational conflict: The role of socially-induced
positive affect. International Journal of Conflict Management, 1, 133–
152.
*Baron, R. A., Rea, M. S., & Daniels, S. G. (1992). Effects of indoor
lighting (illuminance and spectral distribution) on the performance of
cognitive tasks and interpersonal behaviors: The potential mediating role
of positive affect. Motivation and Emotion, 16, 1–33.
*Barsade, S. G. (2002). The ripple effect: Emotional contagion and its
influence on group behavior. Administrative Science Quarterly, 47,
644 – 675.
*Barsade, S. G., Ward, A. J., Turner, J. D. F., & Sonnenfeld, J. A. (2000).
To your heart’s content: A model of affective diversity in top management teams. Administrative Science Quarterly, 45, 802– 836.
Batson, C. D. (1990). Affect and altruism. In B. S. Moore & A. M. Isen
(Eds.), Affect and social behavior (pp. 89 –125). New York: Cambridge
University Press.
Baum, A., & Poluszny, D. M. (1999). Health psychology: Mapping biobehavioral contributions to health and illness. Annual Review of Psychology, 50, 137–163.
*Bell, P. A. (1978). Affective state, attraction, and affiliation: Misery loves
happy company. Personality and Social Psychology Bulletin, 4, 616 –
619.
*Benyamini, Y., Idler, E. L., Leventhal, H., & Leventhal, E. A. (2000).
Positive affect and function as influences on self-assessments of health:
Expanding our view beyond illness and disability. Journals of Gerontology:Psychological Sciences, 55B, P107–P116.
*Berkowitz, L. (1987). Mood, self-awareness, and willingness to help.
Journal of Personality and Social Psychology, 52, 721–729.
*Berry, D. S., & Hansen, J. S. (1996). Positive affect, negative affect, and
BENEFITS OF FREQUENT POSITIVE AFFECT
social interaction. Journal of Personality and Social Psychology, 71,
796 – 809.
*Berry, D. S., & Willingham, J. K. (1997). Affective traits, responses to
conflict, and satisfaction in romantic relationships. Journal of Research
in Personality, 31, 564 –576.
Berscheid, E. (2003). The human’s greatest strength: Other humans. In
L. G. Aspinwall & U. M. Staudinger (Eds.), A psychology of human
strengths: Fundamental questions and future directions for a positive
psychology (pp. 37– 47). Washington, DC: American Psychological
Association.
Bless, H., Bohner, G., Schwarz, N., & Strack, F. (1990). Mood and
persuasion: A cognitive response analysis. Personality and Social Psychology Bulletin, 16, 331–345.
*Bless, H., Clore, G. L., Schwarz, N., Golisano, V., Rabe, C., & Wolk, M.
(1996). Mood and the use of scripts: Does a happy mood really lead to
mindlessness? Journal of Personality and Social Psychology, 71, 665–
679.
*Bodenhausen, G., Gabriel, S., & Lineberger, M. (2000). Sadness and
susceptibility to judgmental bias: The case of anchoring. Psychological
Science, 11, 320 –323.
*Bodenhausen, G. V., Kramer, G. P., & Süsser, K. (1994). Happiness and
stereotypic thinking in social judgment. Journal of Personality and
Social Psychology, 66, 621– 632.
*Bogner, J. A., Corrigan, J. D., Mysiw, W. J., Clinchot, D., & Fugate, L.
(2001). A comparison of substance abuse and violence in the prediction
of long-term rehabilitation outcomes after traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 82, 571–577.
Booth, R. J., & Pennebaker, J. W. (2000). Emotions and immunity. In M.
Lewis & J. M. Haviland-Jones (Eds.), Handbook of emotions (2nd ed.,
pp. 558 –572). New York: Guilford Press.
Borman, W. C., Penner, L. A., Allen, T. D., & Motowildo, S. J. (2001).
Personality predictors of citizenship performance. International Journal
of Selection and Assessment, 9, 52– 69.
Bradburn, N. M. (1969). The structure of psychological well-being. Chicago: Alpine.
*Brebner, J., Donaldson, J., Kirby, N., & Ward, L. (1995). Relationships
between happiness and personality. Personality and Individual Differences, 19, 251–258.
*Brown, J. (1984). Effects of induced mood on causal attributions for
success and failure. Motivation and Emotion, 8, 343–353.
*Burger, J. M., & Caldwell, D. F. (2000). Personality, social activities,
job-search behavior and interview success: Distinguishing between
PANAS trait positive affect and NEO extraversion. Motivation and
Emotion, 24, 51– 62.
Cacha, F. B. (1976). Figural creativity, personality, and peer nominations
of pre-adolescents. Gifted Child Quarterly, 20, 187–195.
Cameron, P. (1975). Mood as an indicant of happiness: Age, sex, social
class, and situational differences. Journal of Gerontology, 30, 216 –224.
Campbell, A. (1981). The sense of well-being in America. New York:
McGraw-Hill.
Campbell, A., Converse, P. E., & Rogers. W. L. (1976). The quality of
American life. New York: Russell Sage Foundation.
Cantor, N., Norem, J., Langston, C., Zirkel, S., Fleeson, W., & CookFlannagan, C. (1991). Life tasks and daily life experience. Journal of
Personality, 59, 425– 451.
Carlson, M., Charlin, V., & Miller, N. (1988). Positive mood and helping
behavior: A test of six hypotheses. Journal of Personality and Social
Psychology, 55, 211–229.
*Carnevale, P., & Isen, A. M. (1986). The influence of positive affect and
visual access on the discovery of integrative solutions in bilateral negotiation. Organizational Behavior and Human Decision Processes, 37,
1–13.
Carver, C. S. (2003). Pleasure as a sign you can attend to something else:
847
Placing positive feelings within a general model of affect. Cognition and
Emotion, 17, 241–261.
*Carver, C. S., Pozo, C., Harris, S. D., Noriega, V., Scheier, M., Robinson,
D., et al. (1993). How coping mediates the effect of optimism on
distress: A study of women with early stage breast cancer. Journal of
Personality and Social Psychology, 65, 375–390.
Carver, C. S., & Scheier, M. F. (1981). Attention and self-regulation: A
control-theory approach to human behavior. New York: SpringerVerlag.
Carver, C. S., & Scheier, M. F. (1990). Origins and functions of positive
and negative affect: A control-process view. Psychological Review, 97,
19 –35.
Carver, C. S., & Scheier, M. F. (1998). On the self regulation of behavior.
New York: Cambridge University Press.
Carver, C. S., & Scheier, M. F. (2001). Optimism, pessimism, and selfregulation. In E. C. Chang (Ed.), Optimism and pessimism: Implications
for theory, research, and practice (pp. 31–51). Washington, DC: American Psychological Association.
*Chang, E. C., & Farrehi, A. S. (2001). Optimism/pessimism and
information-processing styles: Can their influences be distinguished in
predicting psychological adjustment. Personality and Individual Differences, 31, 555–562.
*Chen, C. C., David, A., Thompson, K., Smith, C., Lea, S., & Fahy, T.
(1996). Coping strategies and psychiatric morbidity in women attending
breast assessment clinics. Journal of Psychosomatic Research, 40, 265–
270.
Chen, S.-M. (1980). A study of sociometric status of Chinese school
children (Chinese). Bulletin of Educational Psychology, 13, 119 –132.
Clark, L. A., & Watson, D. P. (1991). General affective dispositions in
physical and psychological health. In C. R. Snyder & D. R. Forsyth
(Eds.), Handbook of social and clinical psychology: The health perspective (pp. 221–245). Elmsford, NY: Pergamon Press.
Clark, L. A., & Watson, D. P. (1999). Temperament: A new paradigm for
trait psychology. In L. A. Pervin & O. P. John (Eds.), Handbook of
personality: Theory and research (2nd ed., pp. 399 – 423). New York:
Guilford Press.
Clark, L. A., Watson, D. P., & Mineka, S. (1994). Temperament, personality, and the mood and anxiety disorders. Journal of Abnormal Psychology, 103, 103–116.
Clark, M. S., & Isen, A. M. (1982). Toward understanding the relationship
between feeling states and social behavior. In A. H. Hastorf & A. M.
Isen (Eds.), Cognitive social psychology (pp. 71–108). New York:
Elsevier/North-Holland.
*Clark, M. S., & Waddell, B. A. (1983). Effects of moods on thoughts
about helping, attraction and information acquisition. Social Psychology
Quarterly, 46, 31–35.
Clore, G. L., Wyer, R. S., Jr., Dienes, B., Gasper, K., & Isbell, L. M.
(2001). Affective feelings as feedback: Some cognitive consequences. In
L. L. Martin & G. L. Clore (Eds.), Theories of mood and cognition: A
user’s guidebook (pp. 27– 62). Hillsdale, NJ: Erlbaum.
*Cogan, R., Cogan, D., Waltz, W., & McCue, M. (1987). Effects of
laughter and relaxation on discomfort thresholds. Journal of Behavioral
Medicine, 10, 139 –144.
Cohen, S. (1988). Psychosocial models of the role of social support in the
etiology of physical disease. Health Psychology, 7, 269 –297.
*Cohen, S., Doyle, W. J., Turner, R. B., Alper, C. M., & Skoner, D. P.
(2003). Emotional style and susceptibility to the common cold. Psychosomatic Medicine, 65, 652– 657.
*Collins, J. E., Hanson, K., Mulhern, M., & Padberg, R. M. (1992). Sense
of coherence over time in cancer patients: A preliminary report. Medical
Psychotherapy, 5, 73– 82.
Connolly, J. J., & Viswesvaran, C. (2000). The role of affectivity in job
satisfaction: A meta-analysis. Personality and Individual Differences,
29, 265–281.
848
LYUBOMIRSKY, KING, AND DIENER
Cooper, H. (1998). Synthesizing research: A guide for literature reviews
(3rd ed.). Thousand Oaks, CA: Sage.
*Cooper, H., Okamura, L., & Gurka, V. (1992). Social activity and
subjective well-being. Personality and Individual Differences, 13, 573–
583.
*Costa, P. T., & McCrae, R. R. (1980). Influence of extraversion and
neuroticism on subjective well-being: Happy and unhappy people. Journal of Personality and Social Psychology, 38, 668 – 678.
*Costa, P. T., McCrae, R. R., & Norris, A. H. (1981). Personal adjustment
to aging: Longitudinal prediction from neuroticism and extraversion.
Journals of Gerontology, 36, 78 – 85.
Coté, S. (1999). Affect and performance in organizational settings. Current
Directions in Psychological Science, 8, 65– 68.
*Cowan, G., Neighbors, C., DeLaMoreaux, J., & Behnke, C. (1998).
Women’s hostility toward women. Psychology of Women Quarterly, 22,
267–284.
*Credé, M., Chernyshenko, O. S., Stark, S., & Dalal, R. S. (2005). The
relationship of job satisfaction to personological and environmental
antecedents and volitional workplace behavior. Manuscript submitted
for publication.
*Cropanzano, R., & Wright, T. A. (1999). A 5-year study of change in the
relationship between well-being and job performance. Consulting Psychology Journal: Practice and Research, 51, 252–265.
Csikszentmihalyi, M. (1975). Beyond boredom and anxiety. San Francisco:
Jossey-Bass.
Csikszentmihalyi, M. (1997). Finding flow. New York: Basic Books.
Csikszentmihalyi, M. (1999). If we are so rich, why aren’t we happy?
American Psychologist, 54, 821– 827.
Csikszentmihalyi, M., Patton, J. D., & Lucas, M. (1997). Le bonheur,
l’experience optimale et les valeurs spirituelles: Une etude empirique
aupres d’adolescents [Happiness, the optimal experience, and spiritual
values: An empirical study of adolescents]. Revue Quebecoise de Psychologie, 18, 167–190.
Csikszentmihalyi, M., & Wong, M. M. (1991). The situational and personal
correlates of happiness: A cross-national comparison. In F. Strack, M.
Argyle, & N. Schwarz (Eds.), Subjective well-being: An interdisciplinary perspective (pp. 193–212). Elmsford, NY: Pergamon Press.
*Cunningham, M. R. (1988a). Does happiness mean friendliness? Induced
mood and heterosexual self-disclosure. Personality and Social Psychology Bulletin, 14, 283–297.
*Cunningham, M. R. (1988b). What do you do when you’re happy or blue?
Mood, expectancies, and behavioral interest. Motivation and Emotion,
12, 309 –331.
*Cunningham, M. R., Shaffer, D. R., Barbee, A. P., Wolff, P. L., & Kelley,
D. J. (1990). Separate processes in the relation of elation and depression
to helping: Social versus personal concerns. Journal of Experimental
Social Psychology, 26, 13–33.
*Cunningham, M. R., Steinberg, J., & Grev, R. (1980). Wanting to and
having to help: Separate motivations for positive mood and guiltinduced helping. Journal of Personality and Social Psychology, 38,
181–192.
*Danner, D. D., Snowdon, D. A., & Friesen, W. V. (2001). Positive
emotions in early life and longevity: Findings from the nun study.
Journal of Personality and Social Psychology, 80, 804 – 813.
*Deeg, D. J. H., & Van Zonneveld, R. J. (1989). Does happiness lengthen
life? The prediction of longevity in the elderly. In R. Veenhoven (Ed.),
How harmful is happiness? Consequences of enjoying life or not (pp.
29 –34). Rotterdam, the Netherlands: Universitaire Pers Rotterdam.
*DeLuga, R. J., & Mason, S. (2000). Relationship of resident assistant
conscientiousness, extraversion, and positive affect with rated performance. Journal of Research in Personality, 34, 225–235.
DeNeve, K. M., & Cooper, H. (1998). The happy personality: A metaanalysis of 137 personality traits and subjective well-being. Psychological Bulletin, 124, 197–229.
Denollet, J., & Brutsaert, D. L. (1998). Personality, disease severity, and
the risk of long-term cardiac events in patients with a decreased ejection
fraction after myocardial infarction. Circulation, 97, 167–173.
*Devins, G. M., Mann, J., Mandin, H. P., & Leonard, C. (1990). Psychosocial predictors of survival in end-stage renal disease. Journal of
Nervous and Mental Disease, 178, 127–133.
Diener, E. (1994). Assessing subjective well-being: Progress and opportunities. Social Indicators Research, 31, 103–157.
Diener, E., & Biswas-Diener, R. (2002). Will money increase subjective
well-being? Social Indicators Research, 57, 119 –169.
Diener, E., Colvin, C. R., Pavot, W. G., & Allman, A. (1991). The psychic
costs of intense positive affect. Journal of Personality and Social Psychology, 61, 492–503.
*Diener, E., & Fujita, F. (1995). Resources, personal strivings, and subjective well-being: A nomothetic and idiographic approach. Journal of
Personality and Social Psychology, 68, 926 –935.
*Diener, E., Gohm, C. L., Suh, E., & Oishi, S. (2000). Similarity of the
relations between marital status and subjective well-being across cultures. Journal of Cross-Cultural Psychology, 31, 419 – 436.
Diener, E., Larsen, R. J., Levine, S., & Emmons, R. A. (1985). Intensity
and frequency: Dimensions underlying positive and negative affect.
Journal of Personality and Social Psychology, 48, 1253–1265.
Diener, E., Oishi, R., & Lucas, R. (2005). Optimum levels of happiness.
Manuscript in preparation.
*Diener, E., Nickerson, C., Lucas, R. E., & Sandvik, E. (2002). Dispositional affect and job outcomes. Social Indicators Research, 59, 229 –
259.
Diener, E., Sandvik, E., & Pavot, W. (1991). Happiness is the frequency,
not the intensity, of positive versus negative affect. In F. Strack, M.
Argyle, & N. Schwarz (Eds.), Subjective well-being: An interdisciplinary perspective (pp. 119 –139). Oxford, England: Pergamon Press.
*Diener, E., & Seligman, M. E. P. (2002). Very happy people. Psychological Science, 13, 81– 84.
Diener, E., Smith, H. L., & Fujita, F. (1995). The personality structure of
affect. Journal of Personality and Social Psychology, 69, 130 –141.
Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective
well-being: Three decades of progress. Psychological Bulletin, 125,
276 –302.
Diener, E., Suh, E. M., Smith, H. L., & Shao, L. (1995). National differences in reported well-being: Why do they occur? Social Indicators
Research, 34, 7–32.
Diener, E., Wolsic, B., & Fujita, F. (1995). Physical attractiveness and
subjective well-being. Journal of Personality and Social Psychology, 69,
120 –129.
*Dillon, K. M., Minchoff, B., & Baker, K. H. (1985). Positive emotional
states and enhancement of the immune system. International Journal of
Psychiatry in Medicine, 15, 13–18.
*Dillon, K. M., & Totten, M. C. (1989). Psychological factors, immunocompetence, and health of breast-feeding mothers and their infants.
Journal of Genetic Psychology, 150, 155–162.
DiMatteo, M. R., Lepper, H. S., & Croghan, T. W. (2000). Depression is
a risk factor for noncompliance with medical treatment. Archives of
Internal Medicine, 160, 2101–2107.
Dobson, K., & Franche, R. L. (1989). A conceptual and empirical review
of the depressive realism hypothesis. Canadian Journal of Behavioral
Science, 21, 419 – 433.
Dobson, K. S., & Pusch, D. (1995). A test of the depressive realism
hypothesis in clinically depressed subjects. Cognitive Therapy and Research, 19, 179 –194.
*Donovan, M. A. (2000). Cognitive, affective, and satisfaction variables as
predictors of organizational behaviors: A structural equation modeling
examination of alternative models. Dissertation Abstracts International,
60(9-B), 4943. (UMI No. AAI9944835)
*Dovidio, J. F., Gaertner, S. L., Isen, A. M., & Lowrance, R. (1995). Group
BENEFITS OF FREQUENT POSITIVE AFFECT
representations and intergroup bias: Positive affect, similarity, and group
size. Personality and Social Psychology Bulletin, 21, 856 – 865.
Dunning, D., & Story, A. L. (1991). Depression, realism, and the overconfidence effect: Are the sadder wiser when predicting future actions
and events? Journal of Personality and Social Psychology, 61, 521–532.
Edwards, J. A., & Weary, G. (1993). Depression and the impression
formation continuum: Piecemeal processing despite the availability of
category information. Journal of Personality and Social Psychology, 64,
636 – 645.
Eid, M., & Diener, E. (2001). Norms for experiencing emotions in different
cultures: Inter- and intranational differences. Journal of Personality and
Social Psychology, 81, 869 – 885.
*Elliot, A. J., & Thrash, T. M. (2002). Approach–avoidance motivation in
personality: Approach and avoidance temperaments and goals. Journal
of Personality and Social Psychology, 82, 804 – 818.
*Elsbach, K., & Barr, P. (1999). The effects of mood on individuals’ use
of structured decision protocols. Organization Science, 10, 181–198.
*Epping-Jordan, J. E., Compas, B. E., Osowiecki, D. M., Oppedisano, G.,
Gerhardt, C., Primo, K., et al. (1999). Psychological adjustment in breast
cancer: Processes of emotional distress. Health Psychology, 18, 315–
326.
Erber, M. W., & Erber, R. (2001). The role of motivated social cognition
in the regulation of affective states. In J. P. Forgas (Ed.), Handbook of
affect and social cognition (pp. 275–290). Hillsdale, NJ: Erlbaum.
Erber, R., & Erber, M. W. (2000). The self-regulation of moods: Second
thoughts on the importance of happiness in everyday life. Psychological
Inquiry, 11, 142–148.
*Erez, A., & Isen, A. M. (2002). The influence of positive affect on the
components of expectancy motivation. Journal of Applied Psychology,
87, 1055–1067.
*Estrada, C., Isen, A. M., & Young, M. J. (1994). Positive affect influences
creative problem solving and reported source of practice satisfaction in
physicians. Motivation and Emotion, 18, 285–299.
*Estrada, C. A., Isen, A. M., & Young, M. J. (1997). Positive affect
facilitates integration of information and decreases anchoring in reasoning among physicians. Organizational Behavior and Human Decision
Processes, 72, 117–135.
Eysenck, H. J. (1997). Addiction, personality and motivation. Human
Psychopharmacology, 12, 79 – 87.
*Feingold, A. (1983). Happiness, unselfishness, and popularity. Journal of
Psychology, 115, 3–5.
Feist, G. J. (1998). A meta-analysis of personality in scientific and artistic
creativity. Personality and Social Psychology Review, 2, 290 –309.
*Fitzgerald, T. E., Prochaska, J. O., & Pransky, G. S. (2000). Health risk
reduction and functional restoration following coronary revascularization: A prospective investigation using dynamic stage typology clustering. International Journal of Rehabilitation and Health, 5, 99 –116.
Fleeson, W. (2001). Toward a structure- and process-integrated view of
personality: Traits as density distributions of states. Journal of Personality and Social Psychology, 80, 1011–1027.
Folkman, S., & Moskowitz, J. T. (2000). Positive affect and the other side
of coping. American Psychologist, 55, 647– 654.
*Forgas, J. P. (1989). Mood effects on decision making strategies. Australian Journal of Psychology, 41, 197–214.
*Forgas, J. P. (1998). On feeling good and getting your way: Mood effects
on negotiator cognition and bargaining strategies. Journal of Personality
and Social Psychology, 74, 565–577.
*Foster, J. B., Hebl, M. R., West, M., & Dawson, J. (2004, April). Setting
the tone for organizational success: The impact of CEO affect on
organizational climate and firm-level outcomes. Paper presented at the
17th annual meeting of the Society for Industrial and Organizational
Psychology, Toronto, Ontario, Canada.
Fraser, G. E., & Shavlik, D. J. (2001). 10 years of life: Is it a matter of
choice? Archives of Internal Medicine, 161, 1645–1652.
849
Fredrickson, B. L. (1998). What good are positive emotions? Review of
General Psychology, 2, 300 –319.
Fredrickson, B. L. (2001). The role of positive emotions in positive
psychology: The broaden-and-build theory of positive emotions. American Psychologist, 56, 218 –226.
*Fredrickson, B. L., & Joiner, T. (2002). Positive emotions trigger upward
spirals toward emotional well-being. Psychological Science, 13, 172–
175.
*Fredrickson, B. L., & Levenson, R. W. (1998). Positive emotions speed
recovery from the cardiovascular sequelae of negative emotions. Cognition and Emotion, 12, 191–220.
*Fredrickson, B. L., Mancuso, R. A., Branigan, C., & Tugade, M. M.
(2000). The undoing effect of positive emotions. Motivation and Emotion, 24, 237–258.
Fredrickson, B. L., Tugade, M. M., Waugh, C. E., & Larkin, G. R. (2003).
What good are positive emotions in crises?: A prospective study of
resilience and emotions following the terrorist attacks on the United
States on September 11, 2001. Journal of Personality and Social Psychology, 84, 365–376.
*Friedman, H. S., Tucker, J. S., Tomlinson-Keasey, C., Schwartz, J. E.,
Wingard, & Criqui, M. H. (1993). Does childhood personality predict
longevity? Journal of Personality and Social Psychology, 65, 176 –185.
Frijda, N. H., & Mesquita, B. (1994). The social roles and functions of
emotions. In S. Kitayama & H. R. Markus (Eds.), Emotion and culture:
Empirical studies of mutual influence (pp. 51– 87). Washington, DC:
American Psychological Association.
*Frisch, M. B., Clark, M. P., Rouse, S. V., Rudd, M. D., Paweleck, J. K.
Greenstone, A., et al. (2004). Predictive and treatment validity of life
satisfaction and the Quality of Life Inventory. Assessment, 10, 1–13.
*Fromm, E. (1962). The art of loving. New York: Harper & Row.
*Futterman, A. D., Kemeny, M. E., Shapiro, D., & Fahey, J. L. (1994).
Immunological and physiological changes associated with induced positive and negative mood. Psychosomatic Medicine, 56, 499 –511.
*Geier, A. B., Schwartz, M. B., & Brownell, K. D. (2003). “Before and
after” diet advertisements escalate weight stigma. Eating and Weight
Disorders, 8, 282–288.
*George, J. M. (1989). Mood and absence. Journal of Applied Psychology,
74, 317–324.
*George, J. M. (1991). State or trait: Effects of positive mood on prosocial
behaviors at work. Journal of Applied Psychology, 76, 299 –307.
*George, J. M. (1995). Leader positive mood and group performance: The
case of customer service. Journal of Applied Social Psychology, 25,
778 –795.
George, J. M., & Brief, A. P. (1992). Feeling good—Doing good: A
conceptual analysis of the mood at work—Organizational spontaneity.
Psychological Bulletin, 112, 310 –329.
*Gil, K. M., Carson, J. W., Porter, L. S., Scipio, C., Bediako, S. M., &
Orringer, E. (2004). Daily mood and stress predict pain, health care use,
and work activity in African American adults with sickle-cell disease.
Health Psychology, 23, 267–274.
*Gladow, N. W., & Ray, M. P. (1986). The impact of informal support
systems on the well-being of low income single parents. Family Relations: Journal of Applied Family and Child Studies, 35, 113–123.
Gleicher, F., & Weary, G. (1991). Effect of depression on quantity and
quality of social inferences. Journal of Personality and Social Psychology, 61, 105–114.
Glenn, N. D., & Weaver, C. N. (1979). A note on family situation and
global happiness. Social Forces, 57, 960 –967.
*Glenn, N. D., & Weaver, C. N. (1981). The contributions of marital
happiness to global happiness. Journal of Marriage and the Family, 43,
161–168.
*Goldman, S. L., Kraemer, D. T., & Salovey, P. (1996). Beliefs about
mood moderate the relationship of stress to illness and symptom reporting. Journal of Psychosomatic Research, 41, 115–128.
850
LYUBOMIRSKY, KING, AND DIENER
Gottman, J. M., & Levenson, R. W. (1999). What predicts change in
marital interaction over time? A study of alternative medicine. Family
Process, 38, 143–158.
*Graef, R., Csikszentmihalyi, M., & Gianinno, S. M. (1983). Measuring
intrinsic motivation in everyday life. Leisure Studies, 2, 155–168.
Graen, T. (1976). Role-making processes within complex organizations. In
M. D. Dunnette (Ed.), Handbook of organizational and industrial psychology (pp. 1201–1245). Chicago: Rand McNally.
*Graham, C., Eggers, A., & Sukhtankar, S. (in press). Does happiness pay?
An exploration based on panel data from Russia. Journal of Economic
Behaviour and Organization.
Gray, J. A. (1994). Personality dimensions and emotion systems. In P.
Ekman & R. J. Davidson (Eds.), The nature of emotion (pp. 329 –331).
New York: Oxford University Press.
*Griffin, P. W., Mroczek, D. K., & Spiro, A. (in press). Variability in
affective change among aging men: Findings from the VA normative
aging study. Journal of Research in Personality.
*Griffitt, W. B. (1970). Environmental effects of interpersonal affective
behavior: Ambient effective temperature and attraction. Journal of Personality and Social Psychology, 15, 240 –244.
Grob, A., Stetsenko, A., Sabatier, C., Botcheva, L., & Macek, P. (1999). A
cross-national model of subjective well-being in adolescence. In F. D.
Alsaker, A. Flammer, & N. Bodmer (Eds.), The adolescent experience:
European and American adolescents in the 1990s (pp. 115–130). Hillsdale, NJ: Erlbaum.
*Harker, L., & Keltner, D. (2001). Expressions of positive emotions in
women’s college yearbook pictures and their relationship to personality
and life outcomes across adulthood. Journal of Personality and Social
Psychology, 80, 112–124.
Haviland, J. M., & Lelwica, M. (1987). The induced affect response:
Ten-week-old infants’ responses to three emotion expressions. Developmental Psychology, 23, 97–104.
Headey, B., & Veenhoven, R. (1989). Does happiness induce a rosy
outlook? In R. Veenhoven (Ed.), How harmful is happiness? Consequences of enjoying life or not (pp. 106 –127). Rotterdam, the Netherlands: Universitaire Pers Rotterdam.
*Headey, B., Veenhoven, R., & Wearing, A. (1991). Top-down versus
bottom-up theories of subjective well-being. Social Indicators Research,
24, 81–100.
*Headey, B., & Wearing, A. (1989). Personality, life events, and subjective
well-being: Toward a dynamic equilibrium model. Journal of Personality and Social Psychology, 57, 731–739.
Heine, S. J., Kitayama, S., Lehman, D. R., Takata, T., Ide, E., Leung, C.,
et al. (2001). Divergent consequences of success and failure in Japan and
North America: An investigation of self-improving motivations and
malleable selves. Journal of Personality and Social Psychology, 81,
599 – 615.
*Hektner, J. M. (1997). Exploring optimal personality development: A
longitudinal study of adolescents. Dissertation Abstracts International,
57(11B), 7249. (UMI No. AAM9711187)
*Hirt, E. R., Melton, R. J., McDonald, H. E., & Harackiewicz, J. M.
(1996). Processing goals, task interest, and the mood–performance relationship: A mediational analysis. Journal of Personality and Social
Psychology, 71, 245–261.
*Hom, H., & Arbuckle, B. (1988). Mood induction effects upon goal
setting and performance in young children. Motivation and Emotion, 12,
113–122.
House, J. S., Landis, K. R., & Umberson, D. (1988). Social relationships
and health. Science, 241, 540 –545.
*Howell, C. J., Howell, R. T., & Schwabe, K. A. (in press). Does wealth
enhance life satisfaction for people who are materially deprived? Exploring the association among the Orang Asli of Peninsular Malaysia.
Social Indicators Research.
*Irving, L. M., Snyder, C. R., & Crowson, J. J. (1998). Hope and coping
with cancer by college women. Journal of Personality, 66, 195–214.
*Isen, A. M. (1970). Success, failure, attention and reaction to others: The
warm glow of success. Journal of Personality and Social Psychology,
15, 294 –301.
Isen, A. M. (1993). Positive affect and decision making. In M. Lewis &
J. M. Haviland-Jones (Eds.), Handbook of emotions (1st ed., pp. 261–
277). New York: Guilford Press.
Isen, A. M. (1999). Positive affect. In T. Dalgleish & M. J. Power (Eds.),
Handbook of cognition and emotion (pp. 521–539). Chichester, England: Wiley.
Isen, A. M. (2000). Positive affect and decision making. In M. Lewis &
J. M. Haviland-Jones (Eds.), Handbook of emotions (2nd ed., pp. 417–
435). New York: Guilford Press.
*Isen, A. M., & Daubman, K. A. (1984). The influence of affect on
categorization. Journal of Personality and Social Psychology, 47, 1206 –
1217.
Isen, A. M., & Geva, N. (1987). The influence of positive affect on
acceptable level of risk: The person with a large canoe has a large worry.
Organizational Behavior and Human Decision Processes, 39, 145–154.
*Isen, A. M., Johnson, M. M., Mertz, E., & Robinson, G. F. (1985). The
influence of positive affect on the unusualness of word associations.
Journal of Personality and Social Psychology, 48, 1413–1426.
*Isen, A. M., & Levin, P. F. (1972). Effect of feeling good on helping:
Cookies and kindness. Journal of Personality and Social Psychology,
21, 384 –388.
*Isen, A. M., & Means, B. (1983). The influence of positive affect on
decision-making strategy. Social Cognition, 2, 18 –31.
Isen, A. M., & Patrick, R. (1983). The effect of positive feelings on risk
taking: When the chips are down. Organizational Behavior and Human
Performance, 31, 194 –202.
Ito, T. A., & Cacioppo, J. T. (1999). The psychophysiology of utility
appraisals. In D. Kahneman, E. Diener, & N. Schwarz (Eds.), Wellbeing: The foundations of hedonic psychology (pp. 470 – 488). New
York: Russell Sage Foundation.
Jahoda, M. (1958). Current concepts of positive mental health. New York:
Basic Books.
Jamison, K. R. (1990). Manic-depressive illness and accomplishment:
Creativity, leadership, and social class. In F. K. Goodwin & K. R.
Jamison (Eds.), Manic-depressive illness (pp. 332–367). New York:
Oxford University Press.
*Judge, T. A., & Higgins, C. A. (1998). Affective disposition and the letter
of reference. Organizational Behavior and Human Decision Processes,
75, 207–221.
*Jundt, D., & Hinsz, V. B. (2001, May). Are happier workers more
productive workers? The impact of mood on self-set goals, self-efficacy,
and task performance. Paper presented at the annual meeting of the
Midwestern Psychological Association, Chicago.
*Kahana, E., Redmond, C., Hill, G. J., Kahana, B., Johnson, J. R., &
Young, R. F. (1995). The effects of stress, vulnerability, and appraisals
on the psychological well-being of the elderly. Research on Aging, 17,
459 – 489.
*Kahn, B. E., & Isen, A. M. (1993). The influence of positive affect on
variety-seeking among safe, enjoyable products. Journal of Consumer
Research, 20, 257–270.
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of
decisions under risk. Econometrika, 47, 263–291.
Karney, B. R., & Bradbury, T. N. (1995). The longitudinal course of
marital quality and stability: A review of theory, methods, and research.
Psychological Bulletin, 118, 3–34.
*Kashdan, T. B., & Roberts, J. E. (2004). Trait and state curiosity in the
genesis of intimacy: Differentiation from related constructs. Journal of
Social and Clinical Psychology, 23, 792– 816.
*Kashdan, T. B., Rose, P., & Fincham, F. D. (2004). Curiosity and
BENEFITS OF FREQUENT POSITIVE AFFECT
exploration: Facilitating positive subjective experiences and personal
growth opportunities. Journal of Personality Assessment, 82, 291–305.
*Kavanagh, D. J. (1987). Mood, persistence, and success. Australian
Journal of Psychology, 39, 307–318.
*Kehn, D. J. (1995). Predictors of elderly happiness. Activities, Adaptation,
and Aging, 19, 11–30.
*Keltner, D., & Bonanno, G. A. (1997). A study of laughter and dissociation: Distinct correlates of laughter and smiling during bereavement.
Journal of Personality and Social Psychology, 73, 687–702.
Keltner, D., & Kring, A. (1998). Emotion, social function, and psychopathology. Review of General Psychology, 2, 320 –342.
Kidd, R. F., & Marshall, L. (1982). Self-reflection, mood, and helpful
behavior. Journal of Research in Personality, 16, 319 –334.
Kiecolt-Glaser, J. K., McGuire, L., Robles, T. F., & Glaser, R. (2002).
Emotions, morbidity, and mortality: New perspectives from psychoneuroimmunology. Annual Review of Psychology, 53, 83–107.
King, L. A., & Broyles, S. J. (1997). Wishes, gender, personality, and
well-being. Journal of Personality, 65, 49 –76.
*King, L. A., & Napa, C. N. (1998). What makes a life good? Journal of
Personality and Social Psychology, 75, 156 –165.
*Kirkcaldy, B., & Furnham, A. (2000). Positive affectivity, psychological
well-being, accident- and traffic-deaths and suicide: An international
comparison. Studia Psychologica, 42, 97–104.
*Koivumaa-Honkanen, H., Honkanen, R., Koskenvuo, M., Viinamaeki, H.,
& Kaprio, J. (2002). Life satisfaction as a predictor of fatal injury in a
20-year follow-up. Acta Psychiatrica Scandinavica, 105, 444 – 450.
*Koivumaa-Honkanen, H., Honkanen, R., Viinamaeki, H., Heikkilae, K.,
Kaprio, J., & Koskenvuo, M. (2001). Life satisfaction and suicide: A
20-year follow-up study. American Journal of Psychiatry, 158, 433–
439.
*Koivumaa-Honkanen, H., Koskenvuo, M., Honkanen, R. J., Viinamaki,
H., Heikkilae, K., & Kaprio, J. (2004). Life dissatisfaction and subsequent work disability in an 11-year follow-up. Psychological Medicine,
34, 221–228.
Kozma, A., & Stones, M. J. (1978). Some research issues and findings in
the assessment of well-being in the elderly. Canadian Psychological
Review, 19, 241–249.
*Kozma, A., & Stones, M. J. (1983). Predictors of happiness. Journal of
Gerontology, 38, 626 – 628.
*Krause, J. S., Sternberg, M., Lottes, S., & Maides, J. (1997). Mortality
after spinal cord injury: An 11-year prospective study. Archives of
Physical Medicine and Rehabilitation, 78, 815– 821.
*Krueger, R. F., Hicks, B. M., & McGue, M. (2001). Altruism and
antisocial behavior: Independent tendencies, unique personality correlates, distinct etiologies. Psychological Science, 12, 397– 402.
Kubzansky, L. D., & Kawachi, I. (2000). Going to the heart of the matter:
Do negative emotions cause coronary heart disease? Journal of Psychosomatic Research, 48, 323–337.
*Kubzansky, L. D., Sparrow, D., Vokonas, P., & Kawachi, I. (2001). Is the
glass half empty or half full? A prospective study of optimism and
coronary heart disease in the normative aging study. Psychosomatic
Medicine, 63, 910 –916.
*Laidlaw, T. M., Booth, R. J., & Large, R. G. (1996). Reduction in skin
reactions to histamine after a hypnotic procedure. Psychosomatic Medicine, 58, 242–248.
Larsen, R. J., & Ketelaar, T. (1991). Personality and susceptibility to
positive and negative emotional states. Journal of Personality and Social
Psychology, 61, 132–140.
Lebo, D. (1953). Some factors said to make for happiness in old age.
Journal of Clinical Psychology, 9, 385–387.
*Lee, G. R., & Ishii-Kuntz, M. (1987). Social interaction, loneliness, and
emotional well-being among the elderly. Research on Aging, 9, 459 –
482.
Lee, G. R., Seccombe, K., & Shehan, C. L. (1991). Marital status and
851
personal happiness: An analysis of trend data. Journal of Marriage and
the Family, 53, 839 – 844.
*Lefcourt, H. M., Davidson-Katz, K., & Kuenemen, K. (1990). Humor and
immune system functioning. Humor, 3, 305–321.
Lehr, U. M. (1982). Depression und Lebensqualität im Alter–Korrelate
negativer und positiver Gestimmtheit [Depression or “quality of life” in
old age: Correlates of negative and positive morale-findings from the
Bonn Longitudinal Study of Aging (BLSA)]. Zeitschrift für Gerontologie, 15, 241–249.
Leith, K. P., & Baumeister, R. (1996). Why do bad moods increase
self-defeating behavior? Emotion, risk-taking, and self-regulation. Journal of Personality and Social Psychology, 71, 1250 –1267.
*Levy, B. R., Slade, M. D., Kunkel, S. R., & Kasl, S. V. (2002). Longevity
increased by positive self-perceptions of aging. Journal of Personality
and Social Psychology, 83, 261–270.
*Levy, S. M., Lee, J., Bagley, C., & Lippman, M. (1988). Survival hazard
analysis in first recurrent breast cancer patients: Seven-year follow-up.
Psychosomatic Medicine, 50, 520 –528.
*Lobel, M., DeVincent, C. J., Kaminer, A., & Meyer, B. A. (2000). The
impact of prenatal maternal stress and optimistic disposition on birth
outcomes in medically high-risk women. Health Psychology, 19, 544 –
553.
Locke, E. A. (1975). Personnel attitudes and motivation. Annual Review of
Psychology, 26, 457– 480.
*Lox, C. L., Burns, S. P., Treasure, D. C., & Wasley, D. A. (1999).
Physical and psychological predictors of exercise dosage in healthy
adults. Medicine and Science in Sports and Exercise, 31, 1060 –1064.
*Lu, L., & Argyle, M. (1991). Happiness and cooperation. Personality and
Individual Differences, 12, 1019 –1030.
*Lu, L., & Shih, J. B. (1997). Personality and happiness: Is mental health
a mediator? Personality and Individual Differences, 22, 249 –256.
*Lucas, R. E. (2001). Pleasant affect and sociability: Towards a comprehensive model of extraverted feelings and behaviors. Dissertation Abstracts International, 61 (10-B), 5610. (UMI No. AAI9990068)
*Lucas, R. E., Clark, A. E., Georgellis, Y., & Diener, E. (2003). Reexamining adaptation and the set point model of happiness: Reactions to
changes in marital status. Journal of Personality and Social Psychology,
84, 527–539.
*Lucas, R. E., Clark, A. E., Georgellis, Y., & Diener, E. (2004). Unemployment alters the set point for life satisfaction. Psychological Science,
15, 8 –13.
Lucas, R. E., & Diener, E. (2003). The happy worker: Hypotheses about
the role of positive affect in worker productivity. In M. Burrick & A. M.
Ryan (Eds.), Personality and work (pp. 30 –59). San Francisco: JosseyBass.
*Lucas, R. E., Diener, E., Grob, A., Suh, E. M., & Shao, L. (2000).
Cross-cultural evidence for the fundamental features of extraversion.
Journal of Personality and Social Psychology, 79, 452– 468.
*Lucas, R. E., Diener, E., & Suh, E. M. (1996). Discriminant validity of
well-being measures. Journal of Personality and Social Psychology, 71,
616 – 628.
*Lutgendorf, S. K., Vitaliano, P. P., Tripp-Reimer, T., Harvey, J. H., &
Lubaroff, D. M. (1999). Sense of coherence moderates the relationship
between life stress and natural killer cell activity in health older adults.
Psychology and Aging, 14, 552–563.
*Lyons, A., & Chamberlain, K. (1994). The effects of minor events,
optimism and self-esteem on health. British Journal of Clinical Psychology, 33, 559 –570.
Lyubomirsky, S. (1997, May). The meaning and expression of happiness:
Comparing the United States and Russia. Paper presented at the ninth
conference of the American Psychological Society, Washington, DC.
Lyubomirsky, S. (2001). Why are some people happier than others?: The
role of cognitive and motivational processes in well-being. American
Psychologist, 56, 239 –249.
852
LYUBOMIRSKY, KING, AND DIENER
Lyubomirsky, S., Kasri, F., & Zehm, K., & Dickerhoof, R. (2005). The
cognitive and hedonic costs of excessive self-reflection. Manuscript
submitted for publication.
Lyubomirsky, S., & Ross, L. (1997). Hedonic consequences of social
comparison: A contrast of happy and unhappy people. Journal of Personality and Social Psychology, 73, 1141–1157.
Lyubomirsky, S., Sheldon, K. M., & Schkade, D. (2005). Pursuing happiness: The architecture of sustainable change. Review of General Psychology, 9, 111–131.
*Lyubomirsky, S., Tkach, C., DiMatteo, M. R., & Lepper, H. S. (in press).
What are the differences between happiness and self-esteem? Social
Indicators Research.
*Lyubomirsky, S., & Tucker, K. L. (1998). Implications of individual
differences in subjective happiness for perceiving, interpreting, and
thinking about life events. Motivation and Emotion, 22, 155–186.
*Mackie, D. M., & Worth, L. T. (1989). Processing deficits and the
mediation of positive affect in persuasion. Journal of Personality and
Social Psychology, 57, 27– 40.
Maddi, S. R., & Kobasa, S. C. (1991). The development of hardiness. In A.
Monat & R. S. Lazarus (Eds.), Stress and coping: An anthology (3rd ed.,
pp. 245–257). New York: Columbia University Press.
*Magen, Z., & Aharoni, R. (1991). Adolescents’ contributing toward
others: Relationship to positive experiences and transpersonal commitment. Journal of Humanistic Psychology, 31, 126 –143.
*Maier, H., & Smith, J. (1999). Psychological predictors of mortality in old
age. Journal of Gerontology, 54B, 44 –54.
Manucia, G. K., Baumann, D. J., & Cialdini, R. B. (1984). Mood influences on helping: Direct effects or side effects? Journal of Personality
and Social Psychology, 46, 357–364.
*Marks, G. N., & Fleming, N. (1999). Influences and consequences of
well-being among Australian young people: 1980 –1995. Social Indicators Research, 46, 301–323.
Martin, R. A. (2002). Is laughter the best medicine? Humor, laughter, and
physical health. Current Directions in Psychological Science, 11, 216 –
220.
Maruta, T., Colligan, R. C., Malinchoc, M., & Offord, K. P. (2000).
Optimists vs. pessimists: Survival rate among medical patients over a
30-year period. Mayo Clinic Proceedings, 75, 140 –143.
*Mastekaasa, A. (1994). Marital status, distress, and well-being: An international comparison. Journal of Comparative Family Studies, 25, 183–
205.
*Mathes, E. W., & Kahn, A. (1975). Physical attractiveness, happiness,
neuroticism, and self-esteem. Journal of Psychology, 90, 27–30.
*Matikka, L. M., & Ojanen, M. (in press). Happiness in persons with
intellectual disabilities. European Journal of Mental Disability.
*Mayer, J. D., Mamberg, M. H., & Volanth, A. J. (1988). Cognitive
domains of the mood system. Journal of Personality, 56, 453– 486.
*McClelland, D. C., & Cheriff, A. D. (1997). The immunoenhancing
effects of humor on secretory IgA and resistance to respiratory infection.
Psychology and Health, 12, 329 –344.
*McCrae, R. R., & Costa, P. T. (1986). Personality, coping, and coping
effectiveness in an adult sample. Journal of Personality, 54, 385– 405.
McCrae, R. R., & Costa, P. T. (1991). Adding Liebe un Arabeit: The fully
five-factor model and well-being. Personality and Social Psychology
Bulletin, 17, 227–232.
McGuire, L., Kiecolt-Glaser, J. K., & Glaser, R. (2002). Depressive symptoms and lymphocyte proliferation in older adults. Journal of Abnormal
Psychology, 111, 192–197.
*McMillen, D. L., Sanders, D. Y., & Solomon, G. S. (1977). Self-esteem,
attentiveness, and helping behavior. Personality and Social Psychology
Bulletin, 3, 257–261.
*Melton, R. J. (1995). The role of positive affect in syllogism performance.
Personality and Social Psychology Bulletin, 21, 788 –794.
Meng, X., Rosenthal, R., & Rubin, D. B. (1992). Comparing correlated
correlation coefficients. Psychological Bulletin, 111, 172–175.
*Miles, D. E., Borman, W. E., Spector, P. E., & Fox, S. (2002). Building
an integrative model of extra role work behaviors: A comparison of
counterproductive work behavior with organizational citizenship behavior. International Journal of Selection and Assessment, 10, 51–57.
Miller, S. M., & Schnoll, R. A. (2000). When seeing is feeling: A
cognitive– emotional approach to coping with health stress. In M. Lewis
& J. M. Haviland-Jones (Eds.), Handbook of emotions (2nd ed., pp.
538 –557). New York: Guilford Press.
*Mishra, S. (1992). Leisure activities and life satisfaction in old age: A
case study of retired government employees living in urban areas.
Activities, Adaptation and Aging, 16, 7–26.
*Mongrain, M., & Zuroff, D. C. (1995). Motivational and affective correlates of dependency and self-criticism. Personality and Individual Differences, 18, 347–354.
*Mroczek, D. K., & Spiro, A. (2005). Change in life satisfaction during
adulthood: Findings from the Veterans Affairs Normative Aging Study.
Journal of Personality and Social Psychology, 88, 189 –202.
*Murray, N., Sujan, H., Hirt, E. R., & Sujan, M. (1990). The influence of
mood on categorization: A cognitive flexibility interpretation. Journal of
Personality and Social Psychology, 59, 411– 425.
Myers, D. G. (1992). The pursuit of happiness: Who is happy and why.
New York: William Morrow.
Myers, D. G. (1999). Close relationships and quality of life. In D. Kahneman, E. Diener, & N. Schwarz (Eds.), Well-being: The foundations of
hedonic psychology (pp. 374 –391). New York: Russell Sage
Foundation.
Myers, D. G. (2000). The funds, friends, and faith of happy people.
American Psychologist, 55, 56 – 67.
Naughton, M. J., Herndon, J. E., II, Shumaker, S. A., Miller, A. A.,
Kornblith, A. B., Chao, D., et al. (2002). The health-related quality of
life and survival of small-cell lung cancer patients: Results of a companion study to CALGB 9033. Quality of Life Research, 11, 235–248.
*Neyer, F. J., & Asendorpf, J. B. (2001). Personality–relationship transaction in young adulthood. Journal of Personality and Social Psychology, 81, 1190 –1204.
*O’Malley, M. N., & Andrews, L. (1983). The effect of mood and
incentives on helping: Are there some things money can’t buy? Motivation and Emotion, 7, 179 –189.
Oishi, S., & Diener, E. (2003). Culture and well-being: The cycle of action,
evaluation, and decision. Personality and Social Psychology Bulletin,
29, 939 –949.
Okun, M. A., Stock, W. A., Haring, M. J., & Witter, R. A. (1984). The
social activity/subjective well-being relation: A quantitative synthesis.
Research on Aging, 6, 45– 65.
Organ, D. (1988). Organizational citizenship behavior: The good soldier
syndrome. Lexington, MA: Lexington Books.
Ortony, A., Clore, G. L., & Collins, A. (1988). The cognitive structure of
emotions. Cambridge, England: Cambridge University Press.
*Ostir, G. V., Markides, K. S., Black, S. A., & Goodwin, J. S. (2000).
Emotional well-being predicts subsequent functional independence and
survival. Journal of the American Geriatrics Society, 48, 473– 478.
*Ostir, G. V., Markides, K. S., Peek, M. K., & Goodwin, J. S. (2001). The
association between emotional well-being and the incidence of stroke in
older adults. Psychosomatic Medicine, 63, 210 –215.
Pacini, R., Muir, F., & Epstein, S. (1998). Depressive realism from the
perspective of cognitive– experiential self-theory. Journal of Personality
and Social Psychology, 74, 1056 –1068.
*Palmore, E. B. (1969). Predicting longevity: A follow-up controlling for
age. Gerontologist, 9, 247–250.
*Pelled, L. H., & Xin, K. R. (1999). Down and out: An investigation of the
relationship between mood and employee withdrawal behavior. Journal
of Management, 25, 875– 895.
BENEFITS OF FREQUENT POSITIVE AFFECT
Pennebaker, J. W. (1993). Putting stress into words: Health, linguistic, and
therapeutic implications. Behaviour Research and Therapy, 31, 539 –
548.
Pennebaker, J. W., & Francis, M. E. (1996). Cognitive, emotional, and
language processes in disclosure. Cognition and Emotion, 10, 601– 626.
Pennebaker, J. W., Mayne, T. J., & Francis, M. E. (1997). Linguistic
predictors of adaptive bereavement. Journal of Personality and Social
Psychology, 72, 863– 871.
Peplau, L. A., & Perlman, D. (Eds.). (1982). Loneliness. New York: Wiley.
*Perry, L. C., Perry, D. G., & Weiss, R. J. (1986). Age differences in
children’s beliefs about whether altruism makes the actor feel good.
Social Cognition, 4, 263–269.
*Peterson, C., Seligman, M. E. P., Yurko, K. H., Martin, L. R., &
Friedman, H. S. (1998). Catastrophizing and untimely death. Psychological Science, 9, 127–130.
*Pettit, J. W., Kline, J. P., Gencoz, T., Gencoz, F., & Joiner, T. E. (2001).
Are happy people healthier: The specific role of positive affect in
predicting self-reported health symptoms. Journal of Research in Personality, 35, 521–536.
*Pfeiffer, S. M., & Wong, P. T. (1989). Multidimensional jealousy. Journal of Social and Personal Relationships, 6, 181–196.
*Phillips, D. L. (1967). Mental health status, social participation, and
happiness. Journal of Health and Social Behavior, 8, 285–291.
Piko, B. F., Gibbons, F. X., Luszcynska, A., & Teközel, M. (2002). Does
culture matter? Cross-cultural comparison of smoking patterns among
adolescents. In I. Leal, T. Botelho, & J. P. Ribeiro (Eds.), Proceedings
of the 16th Conference of the Health Psychology Society (pp. 9 –12).
Lisbon, Portugal: Institute for the Application of Psychology.
Pinquart, M., & Sörensen, S. (2000). Influences of socioeconomic status,
social network, and competence on subjective well-being in later life: A
meta-analysis. Psychology and Aging, 15, 187–224.
*Pitkala, K. H., Laatkonen, M. L., Strandberg, T. E., & Tilvis, R. S. (2004).
Positive life orientation as a predictor of 10-year outcome in an aged
population. Journal of Clinical Epidemiology, 57, 409 – 414.
Pomerantz, E. M., Saxon, J. L., & Oishi, S. (2000). The psychological
trade-offs of goal investment. Journal of Personality and Social Psychology, 79, 617– 630.
Porter, L. W., & Steers, R. M. (1973). Organizational, work, and personal
factors in employee turnover and absenteeism. Psychological Bulletin,
80, 151–176.
Pressman, S. D., & Cohen, S. (2005). Does positive affect influence health?
Psychological Bulletin, 131, 925–971.
Pritzker, M. A. (2002). The relationship among CEO dispositional attributes, transformational leadership behaviors and performance effectiveness. Dissertation Abstracts International, 62(12-B), 6008. (UMI
No. AAI3035464)
*Reed, M. B., & Aspinwall, L. G. (1998). Self-affirmation reduces biased
processing of health-risk information. Motivation and Emotion, 22,
99 –132.
*Requena, F. (1995). Friendship and subjective well-being in Spain: A
cross-national comparison with the United States. Social Indicators
Research, 35, 271–288.
*Reynolds, D. K., & Nelson, F. L. (1981). Personality, life situation and
life expectancy. Suicide and Life Threatening Behavior, 11, 99 –110.
Richards, R. (1994). Creativity and bipolar mood swings: Why the association? In M. P. Shaw & M. A. Runco (Eds.), Creativity and affect (pp.
44 –72). Stamford, CT: Ablex.
*Richards, R., & Kinney, D. K. (1990). Mood swings and creativity.
Creativity Research Journal, 3, 202–217.
*Riddick, C. C. (1985). Life satisfaction determinants of older males and
females. Leisure Sciences, 7, 47– 63.
*Rigby, K., & Slee, P. T. (1993). Dimensions of interpersonal relation
among Australian children and implications for psychological wellbeing. Journal of Social Psychology, 133, 33– 42.
853
*Rimland, B. (1982). The altruism paradox. Psychological Reports, 51,
521–522.
*Roberts, B. W., Caspi, A., & Moffitt, T. E. (2003). Work experiences and
personality development in young adulthood. Journal of Personality and
Social Psychology, 84, 582–593.
*Rosenhan, D. L., Salovey, P., & Hargis, K. (1981). The joys of helping:
Focus of attention mediates the impact of positive affect on altruism.
Journal of Personality and Social Psychology, 40, 899 –905.
*Rosenhan, D. L., Underwood, B., & Moore, B. (1974). Affect moderates
self-gratification and altruism. Journal of Personality and Social Psychology, 30, 546 –552.
Rosenstock, I. M., & Kirscht, J. P. (1979). Why people seek healthcare. In
G. C. Stone, N. G. Cohen, & N. E. Adler (Eds.), Health psychology—A
handbook (pp. 161–188). San Francisco: Jossey-Bass.
Rosenthal, R. (1991). Meta-analytic procedures for social research (2nd
ed.). Thousand Oaks, CA: Sage.
Rosenthal, R., & Rubin, D. B. (2003). r-sub(equivalent): A simple effect
size indicator. Psychological Methods, 8, 492– 496.
*Røysamb, E., Tambs, K., Reichborn-Kjennerud, T., Neale, M. C., &
Harris, J. R. (2003). Happiness and health: Environmental and genetic
contributions to the relationship between subjective well-being, perceived health, and somatic illness. Journal of Personality and Social
Psychology, 85, 1136 –1146.
Ruch, W. (1993). Exhilaration and humor. In M. Lewis & J. M. Haviland
(Eds.), Handbook of emotions (pp. 605– 616). New York: Guilford
Press.
Rusting, C. L., & Larsen, R. J. (1997). Extraversion, neuroticism, and
susceptibility to positive and negative affect: A test of two theoretical
models. Personality and Individual Differences, 22, 607– 612.
*Ruvolo, A. P. (1998). Marital well-being and general happiness of newlywed couples: Relationships across time. Journal of Social and Personal Relationships, 15, 470 – 489.
*Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the
meaning of psychological well-being. Journal of Personality and Social
Psychology, 57, 1069 –1081.
Ryff, C. D., & Singer, B. (1998). The contours of positive human health.
Psychological Inquiry, 9, 1–28.
Salovey, P., Mayer, J. D., & Rosenhan, D. L. (1991). Mood and helping:
Mood as a motivator of helping and helping as a regulator of mood. In
M. S. Clark (Ed.), Prosocial behavior (pp. 215–237). Newbury Park,
CA: Sage.
Salovey, P., & Rosenhan, D. L. (1989). Mood states and prosocial behavior. In H. Wagner & A. Manstead (Eds.), Handbook of social psychophysiology (pp. 371–391). Chichester, England: Wiley.
Salovey, P., Rothman, A. J., Detweiler, J. B., & Steward, W. T. (2000).
Emotional states and physical health. American Psychologist, 55, 110 –121.
*Samson, D., & Rachman, S. (1989). The effect of induced mood on fear
reduction. British Journal of Clinical Psychology, 28, 227–238.
Sandvik, E., Diener, E., & Seidlitz, L. (1993). Subjective well-being: The
convergence and stability of self-report and non-self-report measures.
Journal of Personality, 61, 317–342.
*Sarason, I. G., Potter, E. H., & Sarason, B. R. (1986). Recording and
recall of personal events: Effects on cognitions and behavior. Journal of
Personality and Social Psychology, 51, 347–356.
Schaller, M., & Cialdini, R. B. (1990). Happiness, sadness, and helping: A
motivational integration. In E. T. Higgins & R. M. Sorrentino (Eds.),
Handbook of motivation and cognition: Foundations of social behavior
(Vol. 2, pp. 265–296). New York: Guilford Press.
*Scheier, M. F., Matthews, K. A., Owens, J. F., Magovern, G. J., Lefebvre,
R. C., Abbott, R., A., et al. (1989). Dispositional optimism and recovery
from coronary artery bypass surgery: The beneficial effects on physical
and psychological well-being. Journal of Personality and Social Psychology, 57, 1024 –1040.
*Scheufele, D. A., & Shah, D. V. (2000). Personality strength and social
854
LYUBOMIRSKY, KING, AND DIENER
capital: The role of dispositional and informational variables in the production of civic participation. Communication Research, 27, 107–131.
*Schimmack, U., Oishi, S., Furr, R. M., & Funder, D. C. (2004). Personality and life satisfaction: A facet-level analysis. Personality and Social
Psychology Bulletin, 30, 1062–1075.
Schroeder, D. A., Penner, L. A., Dovidio, J. F., & Piliavin, J. A. (1995).
The psychology of helping and altruism: Problems and puzzles. New
York: McGraw-Hill.
*Schuettler, D., & Kiviniemi, M. T. (in press). Does how I feel about it
matter?: The role of affect in cognitive and behavioral reactions to a
chronic illness diagnosis. Journal of Applied Social Psychology.
*Schuldberg, D. (1990). Schizotypal and hypomanic traits, creativity, and
psychological health. Creativity Research Journal, 3, 218 –230.
*Schwartz, B., Ward, A. H., Monterosso, J., Lyubomirsky, S., White, K., &
Lehman, D. (2002). Maximizing versus satisficing: Happiness is a matter of
choice. Journal of Personality and Social Psychology, 83, 1178 –1197.
Schwarz, N. (1990). Feelings as information: Informational and motivational functions of affective states. In R. M. Sorrentino & E. T. Higgins
(Eds.), Handbook of motivation and cognition: Cognitive foundations of
social psychology (Vol. 2, pp. 527–561). New York: Guilford Press.
Scollon, C. N., & King, L. A. (2004). Is the good life the easy life? Social
Indicators Research, 68, 127–162.
Segerstrom, S. C. (2000). Personality and the immune system: Models,
methods, & mechanisms. Annals of Behavioral Medicine, 22, 180 –190.
Seligman, M. E. P. (1991). Learned optimism. New York: A. A. Knopf.
*Seligman, M. E. P., & Schulman, P. (1986). Explanatory style as a
predictor of productivity and quitting among life insurance agents.
Journal of Personality and Social Psychology, 50, 832– 838.
*Shapiro, P. J., & Weisberg, R. W. (1999). Creativity and bipolar diathesis:
Common behavioral and cognitive components. Cognition and Emotion,
13, 741–762.
*Sheldon, K. M., & Lyubomirsky, S. (in press). Achieving sustainable
increases in happiness: Change your actions, not your circumstances.
Journal of Happiness Studies.
Shephard, R. J. (1993). Exercise in the prevention and treatment of cancer:
An update. Sports Medicine, 15, 258 –280.
Shrauger, J. S., Mariano, E., & Walter, T. J. (1998). Depressive symptoms
and accuracy in the prediction of future events. Personality and Social
Psychology Bulletin, 24, 880 – 892.
*Sinclair, R. C., & Mark, M. M. (1995). The effects of mood state on
judgmental accuracy: Processing strategy as a mechanism. Cognition
and Emotion, 9, 417– 438.
*Smith, A. M., Stuart, M. J., Wiese-Bjornstal, D. M., & Gunnon, C. (1997).
Predictors of injury in ice hockey players: A multivariate, multidisciplinary approach. American Journal of Sports Medicine, 25, 500 –507.
*Smith, T. W., Ruiz, J. M., & Uchino, B. N. (2004). Mental activation of
supportive ties, hostility, and cardiovascular reactivity to laboratory
stress in young men and women. Health Psychology, 23, 476 – 485.
Snyder, C. R. (2000). The past and possible futures of hope. Journal of
Social and Clinical Psychology, 19, 11–28.
Solomon, G. F., Segerstrom, S. C., Grohr, P., Kemeny, M., & Fahey, J.
(1997). Shaking up immunity: Psychological and immunologic changes
after a natural disaster. Psychosomatic Medicine, 59, 114 –127.
*Spanier, G. B., & Furstenberg, F. F. (1982). Remarriage after divorce: A
longitudinal analysis of well-being. Journal of Marriage and the Family,
44, 709 –720.
*Stack, S., & Eshleman, J. R. (1998). Marital status and happiness: A
17-nation study. Journal of Marriage and the Family, 60, 527–536.
*Staw, B. M., & Barsade, S. G. (1993). Affect and managerial performance: A test of the sadder-but-wiser vs. happier-and-smarter hypothesis. Administrative Science Quarterly, 38, 304 –331.
*Staw, B. M., Sutton, R. I., & Pelled, L. H. (1994). Employee positive
emotion and favorable outcomes at the workplace. Organization Science, 5, 51–71.
*Stone, A. A., Cox, D. S., Valdimarsdottir, H., Jandorf, L., & Neale, J. M.
(1987). Evidence that secretory IgA antibody is associated with daily
mood. Journal of Personality and Social Psychology, 52, 988 –993.
*Stone, A. A., Neale, J. M., Cox, D. S., Napoli, A., Valdimarsdottir, V., &
Kennedy-Moore, E. (1994). Daily events are associated with a secretory
immune response to an oral antigen in men. Health Psychology, 13,
440 – 446.
*Stones, M. J., & Kozma, A. (1986). “Happy are they who are happy . . .”
A test between two causal models of relationships between happiness
and its correlates. Experimental Aging Research, 12, 23–29.
*Strayer, J. (1980). A naturalistic study of empathic behaviors and their
relation to affective states and perspective-taking skills in preschool
children. Child Development, 51, 815– 822.
Suh, E. M. (2000). Self, the hyphen between culture and subjective
well-being. In E. Diener & E. M. Suh (Eds.), Culture and subjective
well-being (pp. 63– 86). Cambridge, MA: MIT Press.
*Sullivan, D., LaCroix, A. Z., Russo, J. E., & Walker, E. A. (2001).
Depression and self-reported physical health in patients with coronary
disease. Psychosomatic Medicine, 63, 248 –256.
Tait, M., Padgett, M. Y., & Baldwin, T. (1989). Job and life satisfaction:
A reevaluation of the strength of the relationship and gender effects as
a function of the date of the study. Journal of Applied Psychology, 74,
502–507.
*Tarlow, E. M., & Haaga, D. A. F. (1996). Negative self-concept: Specificity to depressive symptoms and relation to positive and negative
affectivity. Journal of Research in Personality, 30, 120 –127.
Taylor, S. E., & Brown, J. D. (1988). Illusion and well-being: A social
psychological perspective on mental health. Psychological Bulletin, 103,
193–210.
*Taylor, S. E., Lerner, J. S., Sherman, D. K., Sage, R. M., & McDowell,
N. K. (2003). Portrait of the self-enhancer: Well-adjusted and well-liked
or maladjusted and friendless? Journal of Personality and Social Psychology, 84, 165–176.
*Thoits, P. A., & Hewitt, L. N. (2001). Volunteer work and well-being.
Journal of Health and Social Behavior, 42, 115–131.
Thoresen, C. J., Kaplan, S. A., Barsky, A. P., Warren, C. R., & de
Chermont, K. (2003). The affective underpinnings of job perceptions
and attitudes: A meta-analytic review and integration. Psychological
Bulletin, 129, 914 –945.
Tice, D. M., & Wallace, H. (2000). Mood and emotion control: Some
thoughts on the state of the field. Psychological Inquiry, 11, 214 –217.
Tomkins, S. S. (1962). Affect, imagery, and consciousness: Vol. I. The
positive affects. New York: Springer.
*Totterdell, P. (2000). Catching moods and hitting runs: Mood linkage and
subjective performance in professional sports teams. Journal of Applied
Psychology, 83, 848 – 859.
*Trope, Y., & Pomerantz, E. M. (1998). Resolving conflicts among selfevaluative motives: Positive experiences as a resources for overcoming
defensiveness. Motivation and Emotion, 22, 53–72.
Tsai, J. L., Knutson, B., & Fung, H. H. (2004). Cultural variation in affect
valuation. Manuscript submitted for publication.
*Urada, D., & Miller, N. (2000). The impact of positive mood and category
importance on crossed categorization effects. Journal of Personality and
Social Psychology, 78, 417– 433.
*Valdimarsdottir, H. B., & Bovbjerg, D. H. (1997). Positive and negative
mood: Association with natural killer cell activity. Psychology and
Health, 12, 319 –327.
*Van Katwyk, P. T., Fox, S., Spector, P. E., & Kelloway, E. K. (2000).
Using the Job-Related Affective Well-being Scale (JAWS) to investigate
affective responses to work stressors. Journal of Occupational Health
Psychology, 52, 219 –230.
Veenhoven, R. (1984). Conditions of happiness. Dordrecht, The Netherlands: Reidel.
BENEFITS OF FREQUENT POSITIVE AFFECT
Veenhoven, R. (1988). The utility of happiness. Social Indicators Research, 20, 333–354.
Veenhoven, R. (1994). World database of happiness: Correlates of happiness: 7837 findings from 603 studies in 69 nations 1911–1994 (Vols.
1–3). Rotterdam, The Netherlands: Erasmus University.
Veenhoven, R. (1997). Progrès dans la compréhension du bonheur
[Progress in understanding happiness]. Revue Quebecoise de Psychologie, 18, 29 –74.
Verkley, H., & Stolk, J. (1989). Does happiness lead into idleness? In R.
Veenhoven (Ed.), How harmful is happiness? (pp. 79 –93). Rotterdam,
Amsterdam: University of Rotterdam.
*Vitaliano, P. P., Scanlan, J. M., Ochs, H. D., Syrjala, K., Siegler, I. C., &
Snyder, E. A. (1998). Psychosocial stress moderates the relationship of
cancer history with natural killer cell activity. Annals of Behavioral
Medicine, 20, 199 –208.
*Watson, D. (1988). Intraindividual and interindividual analyses of positive and negative affect: Their relation to health complaints, perceived
stress, and daily activities. Journal of Personality and Social Psychology, 54, 1020 –1030.
*Watson, D. (2000). Mood and temperament. New York: Guilford Press.
Watson, D., & Clark, L. A. (1995). Depression and the melancholic
temperament. European Journal of Personality, 9, 351–366.
*Watson, D., Clark, L. A., McIntyre, C. W., & Hamaker, S. (1992). Affect,
personality, and social activity. Journal of Personality and Social Psychology, 63, 1011–1025.
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: The PANAS
scales. Journal of Personality and Social Psychology, 54, 1063–1070.
Watson, D., & Pennebaker, J. W. (1989). Health complaints, stress, and
distress: Exploring the central role of negative affectivity. Psychological
Review, 96, 234 –251.
*Waugh, C. E., & Fredrickson, B. L. (2003). Feeling good and feeling
close: The effect of positive emotion on self– other overlap. Manuscript
submitted for publication.
*Weinglert, L., & Rosen, A.-S. (1995). Optimism, self-esteem, mood, and
subjective health. Personality and Individual Differences, 18, 653– 661.
*Weiss, H. M., Nicholas, J. P., & Daus, C. S. (1999). An examination of
the joint effects of affective experiences and job beliefs on job satisfaction and variations in affective experiences over time. Organizational
Behavior and Human Decision Processes, 78, 1–24.
855
*Willi, J. (1997). The significance of romantic love for marriage. Family
Process, 36, 171–182.
*Williams, S., & Shiaw, W. T. (1999). Mood and organizational citizenship behavior: The effects of positive affect on employee organizational
citizenship behavior intentions. Journal of Psychology, 133, 656 – 668.
Wills, T. A., Sandy, J. M., Shinar, O., & Yaeger, A. (1999). Contributions
of positive and negative affect to adolescent substance use: Test of a
bidimensional model in a longitudinal study. Psychology of Addictive
Behaviors, 13, 327–338.
Wilson, W. (1967). Correlates of avowed happiness. Psychological Bulletin, 67, 294 –306.
*Windle, M. (2000). A latent growth curve model of delinquent activity
among adolescents. Applied Developmental Science, 4, 193–207.
World Value Survey Group. (1994). World Values Survey, 1981–1984 and
1990 –1993. Ann Arbor, MI: Institute for Social Research.
*Wright, J., & Mischel, W. (1982). Influence of affect on cognitive social
learning person variables. Journal of Personality and Social Psychology,
43, 901–914.
*Wright, T. A., & Cropanzano, R. (1998). Emotional exhaustion as a
predictor of job performance and voluntary turnover. Journal of Applied
Psychology, 83, 486 – 493.
*Wright, T. A., & Cropanzano, R. (2000). Psychological well-being and
job satisfaction as predictors of job performance. Journal of Occupational Health Psychology, 5, 84 –94.
*Wright, T. A., & Staw, B. M. (1999). Affect and favorable work outcomes: Two longitudinal tests of the happy—Productive worker thesis.
Journal of Organizational Behavior, 20, 1–23.
*Zinser, M. C., Baker, T. B., Sherman, J. E., & Cannon, D. S. (1992).
Relation between self-reported affect and drug urges and cravings in
continuing and withdrawing smokers. Journal of Abnormal Psychology,
101, 617– 629.
*Zuckerman, D. M., Kasl, S. V., & Ostfeld, A. M. (1984). Psychosocial
predictors of mortality among the elderly poor. The role of religion,
well-being, and social contacts. American Journal of Epidemiology, 119,
410 – 423.
Received March 5, 2004
Revision received March 11, 2005
Accepted April 12, 2005 䡲
New Editor Appointed, 2007–2012
The Publications and Communications (P&C) Board of the American Psychological Association
announces the appointment of a new editor for a 6-year term beginning in 2007. As of January 1,
2006, manuscripts should be directed as follows:
• Emotion (www.apa.org/journals/emo.html), Elizabeth A. Phelps, PhD, Department of Psychology, New York University, 6 Washington Place, Room 863, New York, NY 10003.
Electronic manuscript submission. As of January 1, 2006, manuscripts should be submitted
electronically via the journal’s Manuscript Submission Portal (see the Web site listed above).
Authors who are unable to do so should correspond with the editor’s office about alternatives.
Manuscript submission patterns make the precise date of completion of the 2006 volumes uncertain.
The current editors, Richard J. Davidson, PhD, and Klaus R. Scherer, PhD, will receive and consider
manuscripts through December 31, 2005. Should 2006 volumes be completed before that date,
manuscripts will be redirected to the new editor for consideration in 2007 volume.
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/282349589
B ine leader
orien a ion
per onal al e , organi a ional c l
re and marke
A c e in Journal of Strategic Marketing · September 2015
DOI: 10.1080/0965254X.2015.1076879
CITATIONS
READS
23
1,535
1a
:
Yuhui Gao
Dublin City University
39 PUBLICATIONS 326 CITATIONS
SEE PROFILE
S
e f
ea
f
b ca
a ea
g
e e e a ed
ec :
Designing Emotional Customer Experience for Value Co-creation: From a Service-dominant Logic Perspective View project
All content following this page was uploaded by Yuhui Gao on 06 October 2016.
The user has requested enhancement of the downloaded file.
!” ## $ !
%&’ %’(()))*
+ *&( (,-&
.- – +-/’- 0 -1
+&
-
2%3
4%-
! ” # $% & ” '()*+,-. /0* *1.+14 %- ,,2* * ,*+,-. /0* *1.+1-
34 +% *
%4! 5 6
7 8
98
98: ! ”
;<!=: $
4$
,,888* $ * !, ,6 )$ ! >6 : ?6!
5) +67@’4: 5A 5B
5 .( 4 . 7 C
JOURNAL OF STRATEGIC MARKETING, 2015
http://dx.doi.org/10.1080/0965254X.2015.1076879
Business leaders’ personal values, organisational culture and
market orientation
Yuhui Gao
DCU Business School, Dublin City Univeristy, Dublin, Ireland
ARTICLE HISTORY
ABSTRACT
In a world where competitive advantages based on technology,
physical assets and large advertising budgets are fungible, business
leaders’ personal values as an alternative or complementary
influence on decision-making and market orientation have an
intuitive appeal. Research findings based on data collected from
370 business leaders of independent indigenous companies in
China suggest that business leaders with different sets of personal
values create and develop different types of organisational culture.
Leaders with openness to change values form an adhocracy culture,
while leaders expressing conservation values promote a hierarchy
culture. Different organisational cultures have different influences
on market orientation. The hypothesised relationships between
self-enhancement leaders and market culture and between selftranscendence leaders and clan culture were not supported. Finally,
the article discusses the theoretical contribution of the study,
managerial implications and suggestions for future research.
Received 13 February 2015
Accepted 30 March 2015
KEYWORDS
Personal values;
organisational culture; market
orientation; China
Introduction
A review of the literature shows that scholars have studied the linkages between personality
and organisational culture (Chatman & Barsade, 1995), leadership style and organisational
culture (Ogbonna & Harris, 2000; Schein, 2010), and business leaders’ personal values and
market orientation (Gao & Bradley, 2007). However, researchers make very little attempt
to jointly examine the association between the three concepts, business leaders’ personal
values, organisational culture and market orientation.
Market orientation is the cornerstone of marketing management (Kohli & Jaworski, 1990).
Researchers have richly explored the market orientation field since the publication of the
seminal works of Kohli and Jaworski (1990) and Narver and Slater (1990). Since market orientation provides organisations with a better understanding of their customers, competitors
and environments, it becomes a significant antecedent of performance and is presumed to
contribute to long-term success.
Organisations have recognised the need to become more market orientated (Deshpande,
Farley, & Webster, 1993; Harris & Ogbonna, 2001). However, as Shapiro (1988, p. 123) notes,
CONTACT Yuhui Gao
© 2015 Taylor & Francis
yuhui.gao@dcu.i.e.
2
Y. GAO
‘slogans and glossy programs don’t give a company a market orientation. It takes a philosophy and a culture that go deep in the organisation. Deshpande and Webster (1989)
propose a research agenda calling for the integration of organisational culture with the
study of marketing management. They suggest a specific research question for future study:
What kind of organisational culture encourages and rewards market orientation behaviours? Despite the continuous contributions from Deshpande and his colleagues on the
combined studies of organisational culture, market orientation, innovativeness and firm
performance (e.g., Deshpande & Farley, 2004), research on how to create, implement and
develop a market-oriented organisational culture remains limited (Carrillat, Jaramillo, &
Locander, 2004; Gebhardt, Carpenter, & Sherry, 2006; Homburg & Pflesser, 2000).
People and their values are great differentiators and endure sources of competitive advantage for a firm (Pfeffer, 2002). Organisational cultures start with leaders who impose their
own personal values and assumptions on a group (Schein, 1992). In the discussion of the
process involved in creating and implementing a market-oriented organisational culture,
Carrillat et al. (2004) highlight the role of human factors in such a process. They stress that a
transformational leadership style is the initiating step towards creating a market-oriented
organisational culture and implanting market-oriented strategies. Leaders with articulated
sets of personal values make choices more easily and tend to build lasting results. In contrast, leaders lacking a clear set of personal values constantly shift from goal to goal (Ulrich,
Zenger, & Smallwood, 1999). Organisational strategies and effectiveness are reflections of
the personal values of powerful leaders in the organisation (Hambrick & Mason, 1984).
Despite the significant role that business leaders’ personal values play in the organisation, the marketing literature largely overlooks their impact. The authors argue that a better
understanding of business leaders’ personal values can help us to better understand the
nature of a market-oriented organisational culture. The objective of this research is, therefore, to extend the current literature by exploring two specific questions: (1) What is the role
of personal values in creating and developing organisational culture? and (2) What impact
does organisational culture have on market orientation?
The remainder of the article is structured as follows: Firstly, it provides an overview of
the literature on personal values, organisational culture and market orientation. Secondly,
the article discusses the relationships among the three constructs, which lead to a series
of hypotheses. Thirdly, it provides the empirical analysis based on data collected from 370
leaders of indigenous companies in China. Finally, the article discusses the findings, the
research limitations and suggestions for future research.
Conceptual background
Personal values
Personal values are desirable goals, varying in importance, that serve as guiding principles
in people’s lives (Kluckhohn, 1951; Rokeach, 1973; Schwartz, 1992). People use personal
values as criteria or standards to predict various kinds of behaviour (Kluckhohn, 1951). The
priorities that individuals attribute to different values reflect their temperaments, personalities, socialisation experiences, unique life experiences and surrounding culture (Rokeach,
1973; Smith & Schwartz, 1997).
JOURNAL OF STRATEGIC MARKETING
3
Building upon Rokeach’s (1973) work, Schwartz (1992) derives 10 motivationally discerning types of values based on 3 universal human requirements to which all individuals and
societies must be responsive: the needs of individuals as biological organisms, the requisites
of coordinated social interaction and the requirements for the smooth functioning and
survival of groups. Schwartz (1992) identifies 57 personal values which he then represents
as 10 value types (self-direction, stimulation, conformity, tradition, security, universalism,
benevolence, achievement, power and hedonism). Schwartz (1992) further presents the 10
value types in the two bipolar dimensions: openness to change (self-direction and stimulation) vs. conservation (conformity, tradition and security); self-transcendence (universalism
and benevolence) vs. self-enhancement (achievement and power).
Hedonism relates to openness to change and self-enhancement. The openness to change
values, stressing one’s own independent thought and action, oppose conservation values
which emphasise the preservation of established arrangements. The self-transcendence
values, focusing on the understanding and acceptance of others and concern for the welfare of all human beings, oppose self-enhancement values which emphasise the interests
of oneself and attaining social superiority (Schwartz, 1992).
Organisational culture
Deshpande and Webster (1989, p. 4) define organisational culture as ‘the pattern of shared
values and beliefs that help members of an organisation understand why things happen and
thus teach them the behavioural norms in the organisation. This notion of organisational
culture is consistent with Schein’s (1992) view, where he relates organisational culture to the
values that lie beneath the organisation’s routines. Douglas, Davidson, and Schwartz (2001,
p. 103) share a similar view by stating that ‘organisational culture is, at its core, a system of
common values’.
A number of typologies of organisational culture exist (Leisen, Lilly, & Winsor, 2002).
Drawing on the work of Quinn (1988) and Cameron and Freeman (1991), Deshpande et al.
(1993) adopt the model of four organisational culture types. The shared beliefs in an organisation concern dominant organisational attributes, leadership styles, organisational bonding
mechanisms and overall strategic emphases. This conceptualisation results in four culture
types, namely market, adhocracy, clan and hierarchy. According to Deshpande et al. (1993),
several types of culture can coexist in the organisation. However, as one type of culture
becomes dominant over time, one uses the dominating type to label the organisation’s
culture.
Market orientation
Market orientation includes activities involved in the implementation of the marketing
concept (Kohli & Jaworski, 1990), that is, the firm’s willingness to recognise and understand
consumers’ needs and wants, and a willingness to adjust any of the marketing mix elements
to satisfy those needs and wants (Houston, 1986). Scholars have produced a significant
amount of research on market orientation; in fact, a number of meta-analysis studies in this
field have been developed (e.g., Doyle & Armenakyan, 2014; Ellis, 2006; Kirca, Jayachandran,
& Bearden, 2005). Market orientation is mainly conceptualised from two perspectives in the
literature: a behavioural (Kohli & Jaworski, 1990) and a cultural perspective (Narver & Slater,
4
Y. GAO
1990). Kohli and Jaworski (1990) define a market orientation as composed of three sets of
activities: generating, disseminating and responding to market intelligence. This behavioural
view of market orientation focuses on specific behaviours and therefore facilitates operationalising the market orientation construct. Narver and Slater (1990), however, perceive
market orientation as consisting of three components (customer orientation, competitor
orientation and inter-functional coordination) and two decision-making criteria (a long-term
focus and a profit focus). The two conceptualisations share something in common: they generally mean ‘learning about market developments, sharing this information with appropriate
personnel, and adapting offerings to a changing market’ (Jaworski, Kohli, & Sahay, 2000,
p. 45). In addition, Deshpande and Farley (1998) offer a conceptualisation that includes
both perspectives and emphasises a behavioural approach that defines market orientation
as the set of cross-functional processes and activities directed at creating superior value for
customers through continuous needs assessments. However, Deshpande’s conceptualisation
focuses mainly on customer-related activities (Voss & Voss, 2000).
Hypotheses development and conceptual framework
Linking personal values to organisational culture
According to Schein (2010), organisational culture basically starts from three sources: (1) the
beliefs, values and assumptions of founders of organisations; (2) the learning experiences of
group members as their organisation evolves; and (3) new beliefs, values and assumptions
brought in by new members and leaders. Schein (2010, p. 3) further suggests that ‘these
dynamic processes of culture creation and management are the essence of leadership and
make one realize that leadership and (organisational) culture are two sides of the same coin’.
Leaders of the organisation, consciously or unconsciously, put their personal imprint on the
organisation. As organisations grow over time, the entrepreneurs tend to have their ideals
re-coded, communicated and lived throughout the company (French, 2002). Organisational
values, the core of organisational culture (Douglas et al., 2001), are values of the leaders
(French, 2002). England and Lee (1974) identify several aspects of management affected by
managers’ personal values: perceptions of situations; problem solutions; interpersonal relationships; perceptions of individual and organisational success; the extent to which leaders
accept or reject organisational pressures; and goals and managerial performance.
Every organisation is driven by its leaders’ individual and collective values, whether those
values are ‘consciously understood or unconsciously influential, spoken or unspoken, written
or unrecorded’ (Bean, 1993, p. 95). Leaders’ personal values are likely to have an impact on
the formation and development of organisational culture.
Hypothesis 1: Leaders with different sets of personal values tend to create and develop different
types of organisational culture.
People with dominant openness to change values, for example, which include self-direction,
stimulation and hedonism value types, tend to have independent thought and action and
choose excitement, novelty and creation in their lives (Schwartz, 1992). Leaders with such
value sets are more likely to foster an adhocracy culture, which shows creativity, innovation
and risk-taking. In contrast, people holding dominant conservation values, which consist
of security, conformity and tradition value types, try to seek safety and stability and try to
restrain actions (Schwartz, 1992). Leaders with such value sets are more likely to develop
JOURNAL OF STRATEGIC MARKETING
5
a hierarchy culture that includes regulations and formal structures. People with dominant
self-enhancement values, which include hedonism, achievement and power value types, will
be inclined to control people and resources and to seek personal success through demonstrating competence according to social standards (Schwartz, 1992). Thus, leaders with such
values are more likely to develop a market culture, which emphasises competitive advantage
and market superiority. Finally, people with dominant self-transcendence values, which consist of universalism and benevolence value types, tend to emphasise acceptance of others
as equals and concern for their welfare. Leaders with such values are more likely to foster a
clan culture, which focuses on loyalty, tradition, cohesiveness, teamwork and sense of family.
Hypothesis 1a: Leaders with dominant Openness to change values create and develop an adhocracy culture.
Hypothesis 1b: Leaders with dominant conservation values create and develop a hierarchy
culture.
Hypothesis 1c: Leaders with dominant self-enhancement values create and develop a market
culture.
Hypothesis 1d: Leaders with dominant self-transcendence values create and develop a clan
culture.
Linking organisational culture to market orientation
A firm’s organisational culture affects market information acquisition, transmission and
utilisation processes (Moorman, 1995). Homburg and Pflesser (2000) suggest that certain
organisation-wide-shared basic values are more likely to support market orientation than
others. For example, organisations with the value of open internal communications are more
market oriented because the marketing managers do not keep market information within
themselves but instead share the information across the organisation. Wei and Morgan (2004)
find that organisations with a strong support climate are more likely to establish strong
connections and communication flows among different functional areas, which in turn,
facilitates market orientation development.
Hypothesis 2: Different organisational cultures have a different impact on market orientation.
An adhocracy culture, focusing on entrepreneurship, creativity and risk-taking, tends to
seek business objectives such as new market, new directions for growth and innovation
(Deshpande et al., 1993). Such a culture facilitates the creation of market-driving strategies
(Carrillat et al., 2004); therefore, an adhocracy culture tends to encourage market orientation
(Appiah-Adu & Blankson, 1998). A hierarchy culture, emphasising rules, stability, predictability
and smooth operation (Deshpande et al., 1993), may result in an inward looking bureaucratic
firm which is not customer or market focused (Appiah-Adu & Blankson, 1998). Such a culture
may discourage market orientation. A market culture focusing on productivity, competitiveness, goal achievement and market superiority (Cameron & Freeman, 1991; Deshpande
et al., 1993) tends to place higher importance on customer issues, which in turn leads to sustainable superior customer value (Appiah-Adu & Blankson, 1998). Because a market culture
allows for successful communication of innovations, it is the best culture type to implement
market-driving strategies (Carrillat et al., 2004). Thus, such a culture encourages market orientation development in the firm. Lastly, a clan culture, with its focus on loyalty, tradition
6
Y. GAO
and interpersonal cohesiveness (Deshpande et al., 1993; Ouchi, 1980), could result in a lack
of attention to changing market needs, which is less likely to encourage market orientation
(Appiah-Adu & Blankson, 1998).
Hypothesis 2a: A strong adhocracy organisational culture has a positive impact on market
orientation.
Hypothesis 2b: A strong hierarchy organisational culture has a negative impact on market
orientation.
Hypothesis 2c: A strong market organisational culture has a positive impact on market
orientation.
Hypothesis 2d: A strong clan organisational culture has a negative impact on market orientation.
Research design and methodology
Data collection
A structured survey was administered to 870 senior managers attending part-time EMBA
programmes in prestigious business schools in China. A total of 370 completed questionnaires were returned, representing a response rate of 43%. Among the subjects, 55% were
male and 45% were female. Most of the respondents were in the 25–34 (47%) and 35–44
(36%) age ranges. The majority of respondents either had undergraduate degrees (51%) or
master’s degrees (43%). The results also showed that the respondents, on average, had more
than 12 years of total work experience, with approximately 7 years of experience working
with their current organisation. Among the 370 respondents, 27% of them were CEOs, 19%
general managers and 10% owners. The remaining respondents were marketing managers
(18%), finance managers (3%) and other department managers (33%).
Measures
Personal values
The Schwartz Value Survey (SVS) instrument was used to assess business leaders’ personal
values. The SVS was selected because Schwartz’s theory was extensively tested using samples
collected from 67 countries, including China (Schwartz, 2004). The standard Chinese version
of the SVS was obtained from the Centre for Cross Cultural Comparisons (2004). Following
Steenkamp, Hofstede and Wedel (1999), the instructions and scoring procedure developed
by Schwartz (Schwartz & Sagiv 1995) were used in this study. Respondents were asked how
important a particular value was ‘as a guiding principle in my life’. Each value was rated on a
nine-point scale: −1 opposed to my values, 0 not important, 3 important and 7 of supreme
importance. The SVS consists of 58 values (two values, namely preserving my public image
and observing social norms, were specifically selected to suit the Chinese context); however,
44 values were found to have cross-cultural equivalent meanings. Therefore, data collected
for a total of 46 values (including the two Chinese specific values) were used for further
analysis in the study.
The score for each value domain (e.g., openness to change) was obtained by computing
the mean score for each value type first (e.g., the mean score for self-direction and stimulation
was calculated, respectively), then averaging the scores attributed to the value types within
JOURNAL OF STRATEGIC MARKETING
7
each domain (e.g., the score for openness to change dimension was calculated by averaging
the mean scores of self-direction and stimulation).This procedure ensures equal weighting
of all value types in the construction of a particular value domain (Schwartz, 1992).
Organisational culture
Deshpande et al.’s (1993) organisational culture instrument is widely used in the field of
management (Ogbonna & Harris, 2000) and in marketing research (Appiah-Adu & Blankson,
1998; Deshpande & Farley, 2004). The instrument consists of 16 items, 4 different organisational variables (dominant organisational attributes, leadership style, organisational bonding
mechanisms and overall strategic emphases) for each culture classification. Respondents
were asked to divide 100 points among the 4 culture archetypes depending upon how they
perceived the statement to be reflective of their business. This measurement is viewed as
theoretically superior to other measures (e.g., Cooke & Rousseau, 1988) and practically easy
to administer (Ogbonna & Harris, 2000). The Deshpande et al. (1993) instrument was used,
therefore.
Market orientation
Narver and Slater’s (1990) measurement method was adopted because previous Chinese
market orientation research (Gao, Zhou, & Yim, 2007) demonstrates its reliability and validity.
Six items measured customer orientation, four items measured competitor orientation and
five items measured inter-functional coordination. All items were scored on a seven-point
rating scale ranging from 1 not at all to 7 to an extreme extent.
Control variables
Leaders’ age, level of education and work experience were included as control variables to
reduce the possibility of alternative explanations and model misspecifications (Carbonell &
Rodriguez, 2006). Age was measured using a five-point scale ranging from 1 under 25 to 5
above 55. Level of education was also measured based on a five-point scale ranging from 1
Junior high school to 5 PhD. Work experience refers to the number of years the respondent
had been working.
Analysis and results
To derive meaningful indices for the different dimensions of the constructs, exploratory factor
analyses were conducted through principal component analysis with varimax rotation. Given
the large number of items used to measure the various constructs, each was factor analysed
separately to remove problematic items. This method is well established in the literature
(Ogbonna & Harris, 2000; Slater, Hult, & Olson, 2007). Factors that were conceptually clear
and interpretable, and with eigenvalues greater than one, were retained (Churchill, 1999).
Table 1 presents the principal components analysis of measures of the market orientation
construct. The 15 items were distinctly loaded on 3 factors, which cumulatively explained
approximately 63% of the total variance. The three factors were clearly identified as: customer
orientation, inter-functional coordination and competitor orientation. No market orientation
items appeared to be problematic. Table 2 presents the principal components analysis of the
organisational culture measures. The 16 value items were factor analysed, and 4 factors with
eigenvalues greater than one were extracted (this explained over 65% of the total variance).
8
Y. GAO
Table 1. Exploratory factor analysis of the market orientation measurements.
Factor loading
Item (15 items)
Our business objectives are driven primarily by customer
satisfaction.
We closely monitor and assess our level of commitment in
serving customers’ needs.
Our strategy for competitive advantage is based on our
understanding of customers’ needs.
Our business strategies are driven by our beliefs about how
we can create greater value for customers.
We measure customer satisfaction systematically and
frequently.
We pay close attention to after-sales service.
Our sales people regularly share competitors’ information.
Respond rapidly to competitive actions that threaten us.
Top management regularly discuss competitors’ strengths
and weaknesses.
We target customers where we have an opportunity for
competitive advantage.
Our top managers from each business function regularly
visit our customers.
We freely communicate information about our customer
experiences across all business function.
All of our business functions are integrated in serving the
needs of our target markets.
Our managers understand how each staff can contribute
to creating customer value.
All of our business functions are responsive to each other’s
needs and requests.
Eigenvalues
% of Variance explained
Cumulative %
Customer
orientation
Interfunctional
coordination
Competitor
orientation
.77
.79
.69
.68
.73
.31
.60
.33
.40
.65
.39
.44
.74
.69
.69
.64
.76
.34
.71
.38
.79
.31
.68
6.88
45.85
45.85
1.54
10.29
56.13
1.02
6.81
62.94
Note: rotation converted in 6 iterations; all loadings less than .3 were suppressed. The bold values are factor loadings.
The four factors were identified as follows: clan culture, hierarchy culture, adhocracy culture
and market culture. During this data reduction process, six organisational culture items were
dropped due to cross-loadings (see Table 2). It should be noted that, as recommended by
Schwartz (Schwartz & Boehnke, 2004), an exploratory factor analysis procedure was not
applied to the personal values construct.
Measure assessment
Reliability of the measures was examined through the calculation of Cronbach’s alpha coefficients (Cronbach, 1951). The alpha coefficients ranged from .63 (hierarchy culture) to .86
(customer orientation). Though two alpha coefficients (hierarchy culture .63 and market
culture .65) fall just below Nunnally’s (1978) .70 criterion, they are deemed to be acceptable
according to the .60 ‘criterion-in-use’ suggested by Peterson (1994).
Following the recommendations of Hair, Anderson, Tatham, and Black (1998), construct
validity was assessed through content, convergent and discriminant validity. Content validity
was achieved through an extensive literature review, by consulting academic experts and
JOURNAL OF STRATEGIC MARKETING
9
Table 2. Exploratory factor analysis of the organisational culture measurements.
Factor loading
Item (10 items)
Clan
Our company is a very personal place.
The glue that holds our company together is
loyalty and tradition.
Our company emphasised human resources.
The leader is considered to be a coordinator, an
organizer or an administrator.
Our company is very formalised and structural
place.
Our company emphasises performance and
stability.
Our company is a very dynamic and entrepreneurial place.
The leader is considered to be entrepreneur,
innovator or a risk-taker.
Our company emphasises competitive actions
and achievement.
The glue that holds our company together is the
emphasis on task and goal accomplishment.
Eigenvalues
% of Variance explained
Cumulative %
.67
.57
.61
Hierarchy
Adhocracy
.64
.51
Market
.53
−.45
.63
.61
−.38
.53
.31
−.40
.73
.61
.46
2.12
21.19
21.19
1.72
17.24
35.48
1.40
14.01
52.44
1.25
12.54
64.98
Note: rotation converted in 5 iterations; all loadings less than .3 were suppressed. The bold values are factor loadings.
Items dropped: our company is very production oriented; the leader is considered t o be a producer, a technician or a harddrive; the leader is considered to be mentor, sage or a father or mother figure; the glue that holds our company together
is formal rules and policies; the glue that holds our company together is a commitment or innovation and development;
and our company emphasises growth and acquiring new resources.
Table 3. Reliability and convergent validity of measures.
Inter-item
correlations
Construct
Clan culture
Hierarchy culture
Adhocracy culture
Market culture
Customer orientation
Competitor orientation
Inter-functional coordination
Openness to change
Conservation
Self-enhancement
Self-transcendence
Number of items
3
2
3
2
6
4
5
2
3
3
2
Cronbach alpha coefficient
.78
.63
.77
.65
.86
.80
.85
.70
.81
.70
.77
Lowest
.49
.46
.49
.48
.39
.27
.34
.56
.51
.35
.63
Highest
.61
.46
.60
.48
.66
.70
.68
.56
.70
.59
.63
by pre-testing the questionnaire. Modifications were made to minimise question ambiguity
and to improve content validity. Following Hair et al. (1998), convergent validity was used
to assess the degree to which two or more measures of the same construct are correlated.
The inter-item correlation results show that there were significant bivariate relationships,
indicating convergent validity (Table 3). In addition, the inter-item correlation scores all
exceeded the .30 benchmark recommended by Hair et al. (1998). Finally, discriminant validity
was assessed by applying Gaski’s (1986) test, which was used previously (e.g. Ogbonna &
Harris, 2000). The analysis indicated that no correlation coefficients of the measures exceeded
the alpha coefficient of the constructs, suggesting that the measures show discrimination
10
Y. GAO
Table 4. Discriminant validity of the measures.
Hierarchy
culture
Adhocracy culture
Market culture
.63
−.46
−.03
.77
.28
.65
Customer orientation
.86
.54
.61
Competitor
orientation
Inter-functional coordination
.80
.64
.85
Openness to
change
.70
−.59
.63
−.61
Conservation
Self-enhancement
Self-transcendence
.81
−.63
.69
.70
−.54
.77
Clan culture
.78
−.40
−.12
−.40
Clan culture
Hierarchy culture
Adhocracy culture
Market culture
Customer orientation
Competitor orientation
Inter-functional coordination
Openness to change
Conservation
Self-enhancement
Self-transcendence
Note: diagonal is the Cronbach’s alpha coefficients; off diagonal is the correlation coefficients. The bold values are factor
loadings.
Table 5. Results of analysis of variance: personal values and organisational culture types.
Organisational culture type (mean, standard
deviation)
Hypotheses
(H1a–H1d)
Adhocracy
culture
Openness to
change (H1a)
4.30 (.96)
Univariate F
3.40
Significance
.02*
4.17 (1.05)
4.36 (1.08)
3.32
.08†
4.22 (1.14)
4.39 (.88)
.25
.86
Paired
comparisons (t
tests)
A > H***;
A > M***;
A > C*
H>A;
H>C***;
H>M ***
–
4.56 (1.11)
4.83 (.92)
.82
.48
–
Market
culture
4.21 (1.06)
Clan culture
4.54 (.87)
Hierarchy
culture
4.10 (1.10)
Conservation
(H1b)
4.077 (1.02)
4.45 (.89)
Self-enhancement (H1c)
Self-transcendence
(H1d)
4.31 (.88)
4.301
(1.09)
4.66 (1.20)
4.60 (.95)
Notes: std. deviation in parentheses.
A: adhocracy culture; H: hierarchy culture; M: market culture; and C: clan culture.
Multivariate tests of significance: Pillai’s Trace = .14, df = 16, F = .00; Hotelling’s Trace = .13, df = 16, F = .00; and Wilks’
Lambda = .89, df = 16, F = .00.
*
p < .05; ***p < .001; †p < .10.
(Table 4). Overall, these results showed that the measures in this study possessed satisfactory
reliability and construct validity.
Hypotheses testing and results
To test the first set of hypotheses (H1, H1a–H1d), a MANOVA was performed to compare
the scores on each value dimension (i.e. openness to change, conservation, self-enhancement and self-transcendence) across four organisational types. Table 5 presents the results
of the MANOVA analysis with personal values dimensions as the dependent variables and
JOURNAL OF STRATEGIC MARKETING
11
Table 6. The hierarchical regressions (dependent variable = market orientation).
Independent variables
Constant
Control variables
Age group
Level of Education
Work Experience
Adhocracy culture
(H2a)
Hierarchy culture
(H2b)
Market culture (H2c)
Clan culture (H2d)
R2
Adjusted R2
∆R2
∆F
Multicollinearity
diagnostics (VIF)
Model 1
–
(12.71)
.02 (.22)
.13 (2.33)*
.05 (.44)
3.69
1.04
3.75
.02
.01
Multicollinearity
diagnostics (VIF)
Model 2
–
(11.68)
.05 (.58)
.07 (1.33)
.03 (.26)
.15 (2.21)*
3.72
1.07
3.77
2.11
−.19 (−2.58)**
2.27
.32 (4.83)***
−.10 (−1.38)
1.85
2.14
.20
.18
.18
18.91 (df = 4)***
1. Standardised coefficients are reported.
2. t values are in parentheses.
*
p < .05; **p < .01; ***p < .00, two-tailed tests.
organisational culture types as the grouping variables. The significant values of Pillai’s Trace
(p < .00), Hotelling’s Trace (p < .00) and Wilks’lambda (p < .00) suggest that there were significant differences between the types of personal values and the types of organisational culture
leaders emphasise. Thus, H1 was supported. As Table 5 shows, the MANOVA F-statistic was
significant for openness to change (p < .05), indicating there were significant differences in
openness to change values among the four organisational culture types. Paired comparison t tests were performed (Song, Di Benedetto, & Mason, 2007), showing that adhocracy
culture exhibited the highest level of openness to change, and three pairwise comparisons
are significant (the mean score of the openness to change value for an adhocracy culture is
higher than for a hierarchy culture, a market culture or a clan culture, i.e. A > H, A > M, A > C,
see the last column in Table 5). Therefore, H1a, which states that leaders with dominant
openness to change values create and develop an adhocracy culture, was supported. The
MANOVA F-statistic was close to significant for conservation (p < .10), indicating there were
weak significant differences in conservation among the four organisational culture types. The
Table 7. Descriptive statistics: means, standard deviations and correlations.
Constructs
1. Market orientation
2. Age group
3. Level of education
4. Work experience
5. Adhocracy culture
6. Hierarchy culture
7. Market culture
8. Clan culture
Mean
Std. deviation
N = 354–368
1
1.00
.04
.11*
.04
.34***
−.22***
.33***
.10*
5.3
.9
p < .05; **p < .01;***p < .00 (two tailed).
*
2
3
4
5
6
7
8
1.00
−.16***
.85***
−.12**
.04
.03
.09*
2.5
.8
1.00
−.20***
.13**
−.09*
.08*
.03
3.4
.6
1.00
−.11*
.06
.05
.06
12.4
7.7
1.00
−.47***
.29***
−.08
25.1
18.2
1.00
−.02
−.39***
31.8
18.6
1.00
−.40***
17.8
14.7
1.00
27.1
19.5
12
Y. GAO
t test results showed that the hierarchy culture had the highest level of conservation values,
and the three pairwise comparisons were significant, thus supporting H1b. However, H1c
and H1d were not supported, as the F-statistics were not significant for self-enhancement
and self-transcendence. Therefore, no further t tests were performed.
To test the second set of hypotheses, namely the impacts of four types of organisational
cultures on market orientation, hierarchical regressions were performed. In the first model,
only the constant and the control variables (leaders’ age, level of education and work experience) were entered. In the second model, the independent variable consisted of the control
variables and the four types of organisational cultures (Table 6). As H2a predicted, there was
a significant and positive relationship between adhocracy culture and market orientation
(b = .15, p < .05). H2b states that a hierarchy culture is negatively related to market orientation;
the hypothesis was also strongly supported as the hierarchy culture coefficient was negative
and significant (b = −.19, p < .01). Furthermore, a significant and positive relationship was
found between the market culture and market orientation (b = .32, p < .00), thus H2c was
strongly supported. Finally, H2d states that a clan culture has a negative impact on market
orientation; however, this hypothesis was not supported as the coefficient of the clan culture
was not significant (although negative, b = −.10, p > .05). In the two estimated regression
equations, the largest variance inflation factor, the multicollinearity indicator, is 3.77 for
work experience, in Model 2. This is well below the recommended threshold of 10 (Hair
et al. 1998; Neter, Wasserman, & Kutner, 1985). Multicollinearity, therefore, does not appear
to be a concern in this research (see Table 6 for a multicollinearity diagnostics report).
Table 7 provides the descriptive statistics.
The effect of controls
Leaders’ age and work experience had no significant effects on market orientation in any of
the models. A significant and positive relationship between leaders’ level of education and
market orientation was found in the first model only.
Discussion
A market-oriented culture remains a source of competitive advantage for organisations.
To better understand the role of personal values in creating organisational culture and the
impact of organisational culture on market orientation, the present study examines the three
constructs and their interrelationships.
Business leaders’ personal values have an impact on the formation and development of
organisational culture (Bean, 1993; Siehl, 1985). To explore this issue, H1 was advanced, suggesting that leaders with different sets of personal values create and develop different types
of organisational culture. The results provide support for this hypothesis. Research findings
also confirm that (a) with openness to change leaders form an adhocracy culture (H1a) and
(b) conservation leaders promote a hierarchy culture (H1b). These findings suggest that
leaders of the organisation, consciously or unconsciously, influence the development of their
organisation through their personal values. On the other hand, the relationships between
self-enhancement and market culture and similarly between self-transcendence and clan
JOURNAL OF STRATEGIC MARKETING
13
culture were not established in this research (H1c, d). This finding is explainable by the fact
that China is undergoing the transformation from a centrally planned economy towards a
market-oriented system (Deshpande & Farley, 2000). Such a transformation results in organisations that are still at an immature stage, too early to form a clearly defined market culture.
The second hypothesis, H2, suggested that different organisational cultures have
different impacts on market orientation. The findings statistically support this hypothesis. Adhocracy culture was found to be positively related to market orientation (H2a),
a finding in agreement with previous empirical studies (Appiah-Adu & Blankson, 1998).
Organisations with a strong adhocracy culture constantly seek new markets, new directions for growth and innovation, and thus encourage market orientation (Deshpande &
Farley, 2004). Hierarchy and clan cultures were both found to be negatively related to
market orientation (H2b, H2d), as already shown in the literature (Appiah-Adu & Blankson,
1998). However, the relationship between clan culture and market orientation was not
statistically significant.
This study contributes to the literature in three ways. Firstly, though both the marketing
and management literatures suggest that organisational culture is a potentially important firm resource, scholars make limited attempts to examine the relationship between
organisational culture and market orientation. This study seeks to extend the literature by
responding to Deshpande and Webster ’s (1989) call for an integrated research of organisational culture and marketing. Secondly, the paper includes the key role of personal values
and integrates them into the study of market orientation. The impact of personal values
on market orientation is largely ignored in recent marketing literature. The inclusion of
personal values into the study of marketing phenomena helps us to better understand
the existence of different types of organisational culture and their influence on market
orientation. Thirdly, this study takes a multidisciplinary approach which covers psychology,
management and marketing, an approach that provides a new perspective for market
orientation studies.
Besides its theoretical contributions, this research also offers some important insights
for leaders. As organisations are driving to become more market oriented, leaders need to
understand why certain organisational cultures exist and their impact on market orientation
practices. In this context, a crucial neglected antecedent variable is the influence of business
leaders’ personal values in the creation of the firm’s organisational culture. Leaders may have
largely neglected the intangible role that personal values have played in their organisations.
In order to understand their organisations better, leaders need to first understand themselves, hence, to understand the sets of personal values they hold. This research indicates
that leaders with openness to change values have the inclination to form an adhocracy
culture, which encourages a market orientation. On the other hand, leaders holding conservation values tend to create hierarchy culture, which may discourage market orientation.
Organisational leaders need to recognise that the soft variables, the personal values they
hold, can have a profound impact on the formation of the organisational culture, and hence
how organisational culture might influence market orientation. If leaders can do this, they
might be able to create a more balanced market-oriented organisational culture, and hence
create a competitive advantage for the firm.
14
Y. GAO
Limitations and further research
Although this research provides interesting insights on the understanding of marketoriented organisational culture, it is important to recognise the limitations of the research.
The first limitation is the research sample. The findings of this research are based upon convenience samples, from participants attending the Executive MBA programmes in China. As
Woodside, Sullivan, and Trappey (1999) point out, the motivations and responses of these
participants are likely to be different than those found in other studies. The generalisation
of the findings of this research is subject to further investigation using more representative
samples. In addition, culture is a complex system of norms and values that develops over
time and influences organisational processes and behaviours (Hurley & Hult, 1998). On the
other hand, time affects market orientation in a number of ways, such as lagged or cumulative effects during the implementation of a market-oriented strategy (Gauzente, 2001). The
inclusion of time effects is likely to lead to a more fruitful direction for market orientation
research. Finally, China’s transformation from a centralised economy to a market economy
results in significant changes within the market environment in China. To fully explain the
phenomena between organisational culture and market orientation in China, an inclusion of
the economic environment into the analysis can also provide a more comprehensive picture.
Disclosure statement
No potential conflict of interest was reported by the author.
Funding
This work was supported by Dublin City University under the scheme of Research Early Career.
References
Appiah-Adu, K., & Blankson, C. (1998). Business strategy, organizational culture, and market orientation.
Thunderbird International Business Review, 40, 235–256.
Bean, W. C. (1993). Strategic planning that makes things happen: Getting from where you are to where you
want to be. Amherst, MA: Human Resource Development Press.
Cameron, K. S., & Freeman, S. J. (1991). Cultural congruence, strength and type: Relationships to
effectiveness. In R. W. Woodman & W. A. Passmore (Eds.), Research in organizational change and
development (pp. 23–58). Greenwich: JAI Press, Inc.
Carbonell, P., & Rodriguez, A. I. (2006). The impact of market characteristics and innovation speed on
perceptions of positional advantage and new product performance. International Journal of Research
in Marketing, 23(1), 1–12.
Carrillat, F. A., Jaramillo, F., & Locander, W. B. (2004). Market-driving organizations: A framework. Academy
of Marketing Science Review, 5, 1–14.
Centre for Cross Cultural Comparisons. (2004). Retrieved June 3, 2004, from http://www.
crossculturalcentre.homestead.com
Chatman, J. A., & Barsade, S. G. (1995). Personality, organizational culture, and cooperation: Evidence
from a business simulation. Administrative Science Quarterly, 40, 423–443.
Churchill, G. A. (1999). Marketing research: Methodological foundations (7th ed.). Forth Worth, TX: The
Dryden Press.
Cooke, R. A., & Rousseau, D. M. (1988). Behavioral norms and expectations: A quantitative approach to
the assessment of organizational culture. Group & Organization Management, 13, 245–273.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16, 297–334.
JOURNAL OF STRATEGIC MARKETING
15
Deshpandé, R., & Farley, J. U. (1998). Measuring market orientation: Generalization and synthesis. Journal
of Market-focused Management, 2, 213–232.
Deshpandé, R., & Farley, J. U. (2000). Market-focused organizational transformation in China. Journal
of Global Marketing, 14, 7–35.
Deshpandé, R., & Farley, J. U. (2004). Organizational culture, market orientation, innovativeness, and
firm performance: An international research odyssey. International Journal of Research in Marketing,
21, 3–22.
Deshpande, R., & Webster, F. E., Jr. (1989). Organizational culture and marketing: Defining the research
agenda. Journal of Marketing, 53, 3–15.
Deshpande, R., Farley, J. U., & Webster, F. E. (1993, January). Corporate culture, customer orientation,
and innovativeness in Japanese firms: A quadrad analysis. Journal of Marketing, 57, 23–37.
Douglas, P. C., Davidson, R. A., & Schwartz, B. N. (2001). The effect of organizational culture and ethical
orientation on accountants’ ethical judgments. Journal of Business Ethics, 34, 101–121.
Doyle, J. D., & Armenakyan, A. (2014). Value-creating mechanisms within the market orientationperformance relationship: A meta-analysis. Journal of Strategic Marketing, 22, 193–205.
Ellis, P. D. (2006). Market orientation and performance: A meta-analysis and cross-national comparisons.
Journal of Management Studies, 43, 1089–1107.
England, G. W., & Lee, R. (1974). The relationship between managerial values and managerial success
in the United States. Japan, India, and Australia, Journal of Applied Psychology, 59, 411–419.
French, S. (2002). CEO values replace corporate values. Canadian HR Reporter, 15, 5.
Gao, Y., & Bradley, F. (2007). Engendering a market orientation: Exploring the invisible role of leaders’
personal values. Journal of Strategic Marketing, 15, 79–89.
Gao, G. Y., Zhou, K. Z., & Yim, C. K. (2007). On what should firms focus in transitional economies? A
study of the contingent value of strategic orientations in China. International Journal of Research in
Marketing, 24, 3–15.
Gaski, J. F. (1986). Interrelations among a channel entity’s power sources: Impact of the exercise of
reward and coercion on expert, referent, and legitimate power sources. Journal of Marketing Research,
23, 62–77.
Gauzente, C. (2001). Why should time be considered in market orientation research. Academy of
Marketing Science Review, 1. Retrieved from http://www.amsreview.org/articles/gauzente01-2001.pdf
Gebhardt, G. F., Carpenter, G. S., & Sherry, J. J. F. (2006, October). Creating a market orientation: A
longitudinal, multifirm, grounded analysis of cultural transformation. Journal of Marketing, 70, 37–55.
Hair, J. F., Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.).
London: Prentice Hall International.
Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its top
managers. Academy of Management Journal, 9, 193–206.
Harris, L. C., & Ogbonna, E. (2001). Strategic human resource management, market orientation, and
organizational performance. Journal of Business Research, 51, 157–66.
Homburg, C., & Pflesser, C. (2000). A multiple-layer model of market-oriented organizational culture:
Measurement issues and performance outcomes. Journal of Marketing Research, 37, 449–462.
Houston, F. S. (1986, April). The marketing concept: What it is and what is not. Journal of Marketing,
50, 81–87.
Hurley, R. F., & Hult, G. T. M. (1998). Innovation, market orientation, and organizational learning: An
integration and empirical examination. Journal of Marketing, 62, 42–54.
Jaworski, B., Kohli, A. K., & Sahay, A. (2000). Market-driven versus driving markets. Journal of the Academy
of Marketing Science, 28, 45–54.
Kirca, A. H., Jayachandran, S., & Bearden, W. O. (2005). Market orientation: A meta-analytic review and
assessment of its antecedents and impact on performance. Journal of Marketing, 69, 24–41.
Kluckhohn, C. (1951). Values and value orientations in the theory of action. In T. Parsons & E. A. Shils
(Eds.), Toward a general theory of action (pp. 388–433). Cambridge: Harvard University Press.
Kohli, A. K., & Jaworski, B. J. (1990). Market orientation: The construct, research propositions, and
managerial implications. Journal of Marketing, 54(2), 1–18.
Leisen, B., Lilly, B., & Winsor, R. D. (2002). The effects of organizational culture and market orientation
on the effectiveness of strategic marketing alliances. Journal of Services Marketing, 16, 201–222.
16
Y. GAO
Moorman, C. (1995). Organizational market information processes: Cultural antecedents and new
product outcomes. Journal of Marketing Research, 32, 318–335.
Narver, J. C., & Slater, S. F. (1990). The effect of a market orientation on business profitability. Journal
of Marketing, 54, 20–35.
Neter, J., Wasserman, W., & Kutner, M. (1985). Applied linear statistical models: Regression, analysis of
variance, and experimental design. Homewood, IL: Richard D. Irwin.
Nunnally, J. (1978). Psychometric theory. New York, NY: McGraw-Hill.
Ogbonna, E., & Harris, L. C. (2000). Leadership style, organizational culture and performance: Empirical
evidence from UK companies. The International Journal of Human Resource Management, 11, 766–788.
Ouchi, W. G. (1980). Markets, Bureaucracies, and Clans. Administrative Science Quarterly, 25, 129–141.
Peterson, R. (1994). A meta-analysis of Cronbach’s coefficient alpha. Journal of Consumer Research, 21,
381–391.
Pfeffer, J. (2002). Competitive advantage through people. In J. Henry & D. London (Eds.), Managing
innovation and change (pp. 61–73). London: Sage.
Quinn, R. E. (1988). Beyond rational management. San Francisco, CA: Jossey-Bass Inc.
Rokeach, M. (1973). The nature of human values. New York, NY: Free Press.
Schein, E. H. (1992). Organizational Culture and Leadership (2nd ed.). San Francisco, CA: Jossey-Bass.
Schein, E. H. (2010). Organizational culture and leadership (6th ed.). San Francisco, CA: Wiley.
Schwartz, S. H. (1992). Universals in the content and structure of values: Theoretical advances and
empirical tests in 20 countries. In M. P. Zanna Orlando (Ed.), Advances in experimental social psychology
(Vol. 25, pp. 1–65). San Diego, CA: Academic Press.
Schwartz, S. H. (2004). Basic human values: Their content and structure across cultures. In A. Tamayo &
J. Porto (Eds.), Valores e Trabalho [Values and work]. Brasilia: Editora universidade de Brasilia.
Schwartz, S. H., & Boehnke, K. (2004). Evaluating the structure of human values with confirmatory factor
analysis. Journal of Research in Personality, 38, 230–255.
Schwartz, S. H., & Sagiv, L. (1995). Identifying culture-specifics in the content and structure of values.
Journal of Cross-Cultural Psychology, 26, 92–116.
Shapiro, B. P. (1988, November–December). What the hell is ‘Market-Oriented’? Harvard Business Review,
66, 119–125.
Siehl, C. (1985). After the founder: An opportunity to manager culture. In P. J. Frost, L. F. Moore,
M. R. Louis, C. C. Lundberg, & J. Martin (Eds.), Organizational culture (pp. 125–140). Beverly Hills, CA:
Sage.
Slater, S. F., Hult, G. T. M., & Olson, E. M. (2007). On the importance of matching strategic behavior
and target market selection to business strategy in high-tech markets. Journal of the Academy of
Marketing Science, 35, 5–17.
Smith, P. B., & Schwartz, S. H. (1997). Values. In J. W. Berry, M. H. Segall, & C. Kagitcibasi (Eds.), Handbook
of cross-cultural psychology (Vol. 3, pp. 77–118). Boston, MA: Allyn and Bacon.
Song, M., Di Benedetto, C. A., & Nason, R. W. (2007). Capabilities and financial performance: The
moderating effect of strategic type. Journal of the Academy of Marketing Science, 35, 18–34.
Steenkamp, J.-B. E. M., ter Hofstede, F. T., & Wedel, M. (1999, April). A cross-national investigation into
the individual and national cultural antecedents of consumer innovativeness. Journal of Marketing,
63, 55–69.
Ulrich, D., Zenger, J., & Smallwood, N. (1999). Results-based leadership. Boston, MA: Harvard Business
School Press.
Voss, G. B., & Voss, Z. G. (2000). Strategic orientation and firm performance in an artistic environment.
Journal of Marketing, 64, 67–83.
Wei, Y. S., & Morgan, N. A. (2004). Supportiveness of organizational climate, market orientation, and
new product performance in Chinese firms. Journal of Product Innovation Management, 21, 375–388.
Woodside, A. G., Sullivan, D. P., & Trappey, R. J., III. (1999). Assessing relationships among strategic
types, distinctive marketing competencies, and organizational performance. Journal of Business
Research, 45, 135–146.
View publication stats
International Journal of
Environmental Research
and Public Health
Review
Happy-Productive Teams and Work Units: A
Systematic Review of the ‘Happy-Productive
Worker Thesis’
M. Esther García-Buades 1, * , José M. Peiró 2,3, * , María Isabel Montañez-Juan 1 ,
Malgorzata W. Kozusznik 4 and Silvia Ortiz-Bonnín 1
1
2
3
4
*
Department of Psychology, University of the Balearic Islands, 07122 Palma de Mallorca, Spain;
m.montanez@uib.es (M.I.M.-J.); silvia.ortiz@uib.es (S.O.-B.)
IDOCAL (Institut d’Investigació en Psicologia del RRHH, del Desenvolupament Organitzacional i de la
Qualitat de Vida Laboral), University of Valencia, 46010 Valencia, Spain
IVIE (Instituto Valenciano de Investigaciones Económicas), 46020 Valencia, Spain
Work, Organizational and Personnel Psychology Research Group (WOPP), KU Leuven, 3000 Leuven,
Belgium; gosia.kozusznik@kuleuven.be
Correspondence: esther.garcia@uib.es (M.E.G.-B.); jose.m.peiro@uv.es (J.M.P.);
Tel.: +34-971-172-751 (M.E.G.-B.); +34-963-864-689 (J.M.P.)
Received: 27 November 2019; Accepted: 17 December 2019; Published: 20 December 2019
!”#!$%&'(!
!”#$%&’
Abstract: The happy-productive worker thesis (HPWT) assumes that happy employees perform better.
Given the relevance of teams and work-units in organizations, our aim is to analyze the state of the art on
happy-productive work-units (HPWU) through a systematic review and integrate existing research on
di↵erent collective well-being constructs and collective performance. Research on HPWU (30 studies,
2001–2018) has developed through di↵erent constructs of well-being (hedonic: team satisfaction,
group a↵ect; and eudaimonic: team engagement) and diverse operationalizations of performance
(self-rated team performance, leader-rated team performance, customers’ satisfaction, and objective
indicators), thus creating a disintegrated body of knowledge about HPWU. The theoretical frameworks
to explain the HPWU relationship are attitude–behavior models, broaden-and-build theory, and the
job-demands-resources model. Research models include a variety of antecedents, mediators, and
moderating third variables. Most studies are cross-sectional, all propose a causal happy–productive
relationship (not the reverse), and generally find positive significant relationships. Scarce but
interesting time-lagged evidence supports a causal chain in which collective well-being leads to team
performance (organizational citizenship behavior or team creativity), which then leads to objective
work-unit performance. To conclude, we identify common issues and challenges across the studies
on HPWU, and set out an agenda for future research.
Keywords: happy; productive; performance; satisfaction; a↵ect; engagement; team; work-unit
1. Introduction
The happy-productive worker thesis (HPWT) has a long tradition in work and organizational
psychology since the human relations movement (Hawthorne studies in the 1930s). This movement
showed the importance of groups in a↵ecting the behavior of individuals at work and strongly
contributed to the generalized belief that a happy worker is more productive. Years later, an influential
review expanded the widespread belief that the relationship between satisfaction and job performance
was just an ‘illusory correlation’ (r = 0.17) [1]. However, re-calculations of those results [2] and
more recent meta-analyses highlighted the job attitudes–job performance relationship as a relevant
topic worth further research and applied interest (r = 0.30) [3,4]. More recently, research on the
Int. J. Environ. Res. Public Health 2020, 17, 69; doi:10.3390/ijerph17010069
www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2020, 17, 69
2 of 39
relationship between well-being and performance has expanded to other constructs such as a↵ect [5]
and engagement [6,7]. Some scholars view the happy–performance relationship as weak, spurious, or
questionable [2,8], and many consider well-being and performance as unrelated variables [2,9]. On the
other hand, di↵erent meta-analyses have demonstrated a positive significant relationship between
individual well-being and task performance [4,7].
Most research on HPWT has taken place at the individual level. However, the changes and
transformation in the world of work and organizations has led to a growing relevance of work teams
and work-units in current organizations. More than half of all employees in the 28 member states of
the European Union work in a team that has common tasks and can plan its work [10]. Despite the
importance of teams in organizational life, studies on the HPWT at the team and work-unit level is still
scant. Moreover, research on this issue has often relied on single constructs of collective well-being
such as ‘group a↵ect’ [11] or ‘work-unit satisfaction’ [12]. Over the last decades, several quantitative
studies have investigated happy-productive teams. Yet, to date, there has been no systematic review
bringing together and synthesizing existing research on this topic. To fill this research gap, our aim is
to analyze the state of the art on happy–productive work-units (HPWU) through a systematic review
and integrate existing research on di↵erent collective well-being constructs and collective performance.
A systematic review would provide a comprehensive picture on the current knowledge on HPWU,
a better understanding of the strengths, commonalities and di↵erences across constructs, and provide
implications for team management and future research.
To achieve our main objective, we undertake a systematic review of peer-reviewed research on
HPWU from 2001 to 2018. Considering the limitations of HPWT research at the individual level [9,13,14],
we explore research on eudaimonic constructs of well-being/happiness as well as hedonic constructs,
and consider multiple aspects of collective performance and sources of evaluation. Furthermore, we
review the literature on HPWU by placing the focus on answering three research questions: (1) Which
are the main features of the conceptualization and measurement of collective well-being? (2) Which
theoretical frameworks are used to explain the collective HPWU relationship and which third variables
are included in HPWU research models? (3) What is the evidence for causal or reciprocal relationships
between collective wellbeing and collective performance?
In this review, we first describe the conceptualization of the two key constructs in the HPWT
(happiness and productivity). Second, we explain the methodological approach adopted for the
systematic review. In the results section, we present a brief description of the studies identified,
and then proceed to report the main findings structured around the research questions. Finally, we
discuss the state of the art of research on HPWU, limitations, and challenges for future research.
1.1. Happiness and Well-Being at Work
Scholars have treated happiness as well-being and have studied it through di↵erent constructs
that overlap with the broad concept of happiness (e.g., psychological well-being, subjective well-being,
satisfaction with life). There are two main perspectives about happiness or well-being: hedonic and
eudaimonic [15]. The “hedonic approach focuses on happiness and defines well-being in terms of
pleasure attainment and pain avoidance; and the eudaimonic approach focuses on meaning and
self-realization and defines well-being in terms of the degree to which a person is fully functioning” [16]
(p. 141). Following Sonnentag [17], well-being refers to a person’s hedonic experience of feeling good
and to the eudaimonic experience of fulfilment and purpose.
So far, research on the HPWT has focused mainly on hedonic constructs (i.e., job satisfaction,
a↵ect, and emotions). However, the last decades have seen a growth on research on individual-level
eudaimonic constructs such as engagement or flow [6], thriving at work [18–20], flourishing at work [21],
meaning at work [22], and purpose in life or personal growth [23]. In her review about happiness
at work, Fisher [15] identified some research on collective job satisfaction, group task satisfaction,
group a↵ective tone, group mood, unit-level engagement. We present the hedonic and eudaimonic
perspectives on individual and collective wellbeing at work identified by Fisher in Table 1. In our
Int. J. Environ. Res. Public Health 2020, 17, 69
3 of 39
review of HPWU, we aim to broaden the scope of research on collective well-being beyond a hedonic
perspective by also exploring whether research on eudaimonic constructs has taken place at the
team/work-unit level.
Table 1. Hedonic and eudaimonic perspectives on individual and collective well-being at work
Happiness
Individual Happiness at Work
Collective Happiness at Work
Hedonic
A↵ect
Emotions
Mood
Job satisfaction
Group a↵ect
Group mood
Collective satisfaction
Group task satisfaction
Eudaimonic
Work engagement
Flow
Meaning at work
Flourishing
Personal growth
Unit-level engagement
Recognizing the social dimension of work, well-being may be studied at the collective level as
research on a↵ective and emotional climates has shown [24]. Collective happiness or well-being refers to
an emotional or a↵ective climate that emerges in work-units and becomes a work context for employees
a↵ecting their work experience, behaviors, and performance [25]. Emotional or a↵ective climates
emerge in teams as a sharedness of a↵ective reactions or emotional responses [25]. Teams develop
shared climates through both top-down and bottom-up processes [26]. Top-down processes stem from
team members sharing their work environment, team manager, most of their tasks, and from their
exposure to similar job conditions. Shared a↵ective climates also emerge from bottom up processes
including social interactions and communication, emotional contagion, role modelling, and advice
giving [26].
Measuring collective well-being presents important methodological issues. Most measures of
collective well-being arise from evaluations provided by individuals (i.e., team members), which
are statistically aggregated to the collective level. A majority of researchers interested in group
or team processes have adopted either a direct consensus or a referent-shift consensus model to
aggregate individual responses [27,28]. In the direct consensus model, team members evaluate their
individual well-being with items using an ‘individual referent’ (e.g., “I am enthusiastic about my job”).
Referent-shift models require individual team members to respond to survey items, which refer directly
to the team (e.g., “My team is enthusiastic about the task”). Items worded with a ‘team referent’ shift
the respondents’ attention to the team level. The second step in both direct consensus and referent-shift
models is to average individual responses to obtain a group-level measure (e.g., group’s statistical
mean) after assuming and testing for some minimal level of within-group interrater agreement (IRA)
and interrater reliability (IRR) consensus [29,30].
1.2. Collective Performance
The approach taken to define and measure performance di↵ers depending on the level at which
performance is assessed (i.e., individual, team/work-unit, or organizational). At the team level,
it is important to make a conceptual distinction between team performance and team e↵ectiveness.
Following Salas et al. [31]:
“Team performance accounts for the outcomes of the team’s actions regardless of how the team
may have accomplished the task. Conversely, team e↵ectiveness takes a more holistic perspective in
considering not only whether the team performed (e.g., completed the team task) but also how the
team interacted (i.e., team processes, teamwork) to achieve the team outcome. This is an important
di↵erentiation because many factors external to the team may contribute to the success (or failure) of
the team, and therefore in some cases team performance measures may be deficient in understanding
the team” (p. 557).
(managers or supervisors) are also frequent evaluators of the team’s performance (i.e., leader-rated
team performance). Managers’ evaluations of their work-unit’s performance are widespread and
taken for valid as they are in the position to observe their team’s work and give a global evaluation
of how much or how well the team works and accomplishes the set objectives. Managers typically
provide
a global
about
the69 work-unit. In our review, we call this measure of team’s
Int. J. Environ.
Res.measure
Public Health
2020, 17,
4 of 39
effectiveness team performance and we will distinguish between self-rated team performance and
leader-rated team performance, and whenever possible we will specify whether task performance,
Although team e↵ectiveness is the appropriate term, to keep in line with the expressions used
OCB, or creative performance are taken into account.
in the HPWT literature we will also use the expressions ‘collective performance’ and ‘productive
Customers’ evaluations constitute another relevant source to assess team’s effectiveness. It is
teams’ to refer to measures of both the team’s achievements and actions for the remainder of the
externally rated, and it usually reflects a combined evaluation of both processes and outcomes (i.e.,
article. Building on previous research, we contend that a comprehensive evaluation of a team’s
how fast a team responds to customers’ requests or to which extent the solution to a problem is
e↵ectiveness needs to include measures of di↵erent aspects of the team’s interaction (processes) and
satisfactory). Customers’ evaluations typically include facets such as service quality and customer
performance (outcomes) [31], as well as di↵erent facets of the work content (e.g., task, organizational
satisfaction.
citizenship behavior (OCB), creativity) [9]; and multiple sources of evaluation (group members,
Another performance category includes work-unit objective/financial indicators. In this case,
supervisors, customers, and objective data) [32]. Figure 1 reflects these core aspects of work-unit
team productivity refers to a combination of efficiency and effectiveness and encompasses a number
e↵ectiveness. Based on these aspects, we proceed to describe categories of collective performance
of results-oriented outcomes such as profit, return-on-investment, and sales [12]. These objective
commonly used in research [12,33]: team performance, customers’ evaluations, and work-unit
assessments of performance are usually recorded for groups rather than for individuals [14] and
objective/financial indicators.
therefore refer to the work-unit as a whole.
Figure 1. Work-unit e↵ectiveness: facets and sources of evaluation.
Figure 1. Work-unit effectiveness: facets and sources of evaluation.
Team performance may refer to di↵erent aspects of the work content (e.g., task performance,
contextual performance, and creativity performance) [9]; may refer to team members’ outcomes
(i.e., do the team members achieve their objectives?) or processes (i.e., what do team members do
when at work?); and may be provided by di↵erent agents, the team-members themselves (self-rated
performance) or their supervisors. Typically, group/team members provide subjective ratings on
their e↵ectiveness based on their own perceptions (i.e., self-rated team performance). Team leaders
(managers or supervisors) are also frequent evaluators of the team’s performance (i.e., leader-rated
team performance). Managers’ evaluations of their work-unit’s performance are widespread and taken
for valid as they are in the position to observe their team’s work and give a global evaluation of how
much or how well the team works and accomplishes the set objectives. Managers typically provide
a global measure about the work-unit. In our review, we call this measure of team’s e↵ectiveness
team performance and we will distinguish between self-rated team performance and leader-rated
team performance, and whenever possible we will specify whether task performance, OCB, or creative
performance are taken into account.
Customers’ evaluations constitute another relevant source to assess team’s e↵ectiveness. It is
externally rated, and it usually reflects a combined evaluation of both processes and outcomes (i.e., how
fast a team responds to customers’ requests or to which extent the solution to a problem is satisfactory).
Customers’ evaluations typically include facets such as service quality and customer satisfaction.
Another performance category includes work-unit objective/financial indicators. In this case,
team productivity refers to a combination of efficiency and e↵ectiveness and encompasses a number
of results-oriented outcomes such as profit, return-on-investment, and sales [12]. These objective
Int. J. Environ. Res. Public Health 2020, 17, 69
5 of 39
assessments of performance are usually recorded for groups rather than for individuals [14] and
therefore refer to the work-unit as a whole.
The association between well-being and performance may vary with the type of performance
considered [34]. The diversity in operationalizations of team performance provides a rich combination
of criteria, thus increasing the interest in the evaluation of how collective well-being relates to di↵erent
collective performance criteria. Overall, a more comprehensive consideration of collective well-being
and collective performance allows for a richer picture of HPWU relationships. Therefore, in our
systematic review, we aim to explore HPWU research considering both hedonic and eudaimonic
constructs of well-being, and performance indicators based on multiple aspects of collective performance
and multiple sources of evaluation.
2. Materials and Method: Study Search and Collection
To address our research questions, we conducted a systematic literature review searching the
PsycINFO and PsycARTICLES databases for empirical studies in peer-reviewed journal articles that
addressed the HPWT in groups/teams/work-units between 2001 and 2018 published in English or
Spanish. This search took place in June 2019. For a comprehensive inclusion of all potential terms
referring to happy teams and productive teams, we used the following keywords (and combinations
thereof): happy (well-being, satisfaction, a↵ect, emotions, mood, engagement, flourishing, flow,
purpose, meaning, hedonic, eudaimonic, morale); productive (performance, productivity, efficiency,
e↵ectiveness, customer satisfaction, OCB, innovation, creativity); and team (work-unit, work group).
We included all studies about groups, teams, work-units, and branches because all represent the
same meso-level of analysis as opposed to individual and organizational levels. We broadly define
team or work-unit as a group of three or more employees who meet on a regular basis, are jointly
responsible for one or more tasks, and are nested in a larger social system (e.g., organization) [35].
In this vein, we use the terms group and team interchangeably as is common in organizational
psychology literature [32]. Although we recognize that some di↵erences may exist, we focus on their
communalities [33]. This exploratory systematic search yielded 356 abstracts. A first screening of
all abstracts showed research to concentrate on three collective well-being constructs: satisfaction,
group a↵ect (emotions and mood), and engagement. We did not find studies analyzing eudaimonic
constructs at the team level (e.g., meaning of work or flourishing). Consequently, we conducted
three specific searches on satisfaction, group a↵ect, and engagement, which we complemented with
cross-references found in di↵erent meta-analyses and through a snowball system. The entire search
phrases are presented in Supplementary Materials.
In each case, two independent evaluators analyzed all abstracts to check if they met two
inclusion criteria: (1) the study reported collective level measurements of well-being and performance;
(2) it presented empirical research undertaken with work samples (e.g. we excluded students and
athletes). Agreement between evaluators reached 96%. After solving discrepancies, evaluators selected
87 abstracts.
In the next stage, we proceeded with full-text analysis. We searched and found 87 manuscripts.
We discarded the studies that while studying team phenomena, analyzed the data at the individual
or organizational level, or did not report correlations between well-being and performance. We also
discarded nine studies on collective satisfaction and one on group a↵ect, which did not propose a
happy-productive or the reversed productive-happy research model. These 10 studies presented
models akin to input-processes-outcomes models of team e↵ectiveness and considered both collective
well-being and collective performance as dependent variables.
The final sample of empirical studies with this systematic literature review yielded 30 studies
relating happy work-units and performance strictly at the collective level of analysis. A PRISMA
(Preferred Reporting Items for Systematic reviews and Meta-Analyses) flowchart (Figure 2) summarizes
the process of search, analysis, and selection of research papers.
happy–productive; PH: productive–happy), definition and operationalization of collective wellbeing and performance, study design (cross-sectional or time-lagged), reported correlations, and
Int. J. Environ. Res. Public Health 2020, 17, 69
6 of 39
sample. Next, we proceeded to analyze the manuscripts in order to answer our main research
questions and summarize the findings in the results sections.
Search for
Well-being and Performance
Database Search (PsycINFO, PsycARTICLES): 172
SAT (n = 118) AFF (n = 29) ENG (n = 25)
Records after duplicates removed: 162
SAT (n = 108) AFF (n = 29) ENG (n = 25)
Potentially eligible articles based on title and abstract: 73
SAT (n = 42) AFF (n = 17) ENG (n = 14)
Additional articles
from cross-references:
Full-text articles assessed for eligibility: 87
14
SAT (n = 46) AFF (n = 25) ENG (n = 16)
SAT (n = 4)
*Elimination
based on full-text:
57
SAT (n = 39)
AFF (n = 11)
AFF (n = 8)
ENG (n = 2)
Empirical articles included: 30
SAT (n = 7) AFF (n = 14) ENG (n = 9)
Figure 2.of
Process
of analysis
and selection
research papers
onon
happy–productive
teams and
work-and
Figure 2. Process
analysis
and selection
ofofresearch
papers
happy–productive
teams
units.
work-units. Notes. SAT = satisfaction; AFF = group a↵ect; ENG = engagement; *Exclusion criteria:
sample Notes.
(no work
quality
of theaffect;
study
(meta-analyses,
review),criteria:
analyses
(individual
data
SAT =sample),
satisfaction;
AFF = group
ENG
= engagement; *Exclusion
sample
(no work sample),
analyses,
no correlation
measures
(no satisfaction
measures,
no performance
measures),
and
quality
of the study data),
(meta-analyses,
review),
analyses (individual
data analyses,
no correlation
data), measures
(no satisfaction
measures, (happy
no performance
measures),
and happy–productive
happy–productive
relationship
and productive
as dependent
variables). relationship (happy and
productive as dependent variables).
Data Analysis
3. Results
First, we read the 30 manuscripts and extracted relevant information which we report in the
Appendix A3.1.
(Table
A1 for
Table A2 for group a↵ect, and Table A3 for team engagement)
Description
of satisfaction,
the Studies
about their study
goal,
theoretical
background,
direction proposed between happiness and productivity
3.1.1. Collective Satisfaction
(HP: happy–productive; PH: productive–happy), definition and operationalization of collective
well-being and performance, study design (cross-sectional or time-lagged), reported correlations, and
sample. Next, we proceeded to analyze the manuscripts in order to answer our main research questions
and summarize the findings in the results sections.
Int. J. Environ. Res. Public Health 2020, 17, 69
7 of 39
3. Results
3.1. Description of the Studies
3.1.1. Collective Satisfaction
We identified seven empirical studies relating collective satisfaction and collective performance in
work-units or teams. Samples were drawn from di↵erent sectors (sales, manufacturing, social care,
local governments, health care, banks), and countries (USA, Netherlands, United Kingdom, Taiwan,
China, and Australia) with representations from four continents. Samples sizes ranged from 28 to 171
work-units. Most studies used a cross-sectional design, with three using time-lagged performance
indicators [33,36,37].
3.1.2. Group A↵ect
We identified 14 empirical studies relating group a↵ect and collective performance in work-units
or teams. Samples were drawn from sectors such as electronic industry, service organizations, sales,
banks, orchestras, etc., and di↵erent countries (Germany, Spain, Brazil, Taiwan, South Korea) with
representations from three continents. Samples sizes ranged from 22 to 417 work-units. Most studies
used a cross-sectional design, with two using time-lagged performance indicators [38,39].
3.1.3. Team Engagement
We identified nine empirical studies relating team engagement and collective performance.
Empirical research exploring the collective engagement-performance relationship varies considerably
in terms of sample size (54 to 242 teams), types of company/sector (health services, hospitality, call
centres, research teams, and teachers). All studies have taken place in European countries (Spain,
Finland, UK, and The Netherlands) and one in Vietnam. All studies used a cross-sectional design.
3.2. Main Findings
3.2.1. Research Question 1. Which Are the Main Features of the Conceptualization and
Operationalization of Collective Well-Being?
In this section, we review the main features of the conceptualization and operationalization of
collective well-being. We review the definitions, instruments, informants and referents used within the
literature identified in the systematic review.
Definition of Collective Satisfaction. An important theoretical contribution in defining
satisfaction at the unit-level as a di↵erent phenomenon to individual job satisfaction is the work by
Whitman et al. [12] (p. 46). They defined “unit-level job satisfaction” as “a work unit’s shared internal
state that is expressed by a↵ectively and cognitively evaluating shared job experiences with some
degree of favour or disfavour”. They stressed the relevance of sharedness as a critical precondition to
forming collective job satisfaction. The antecedents to this sharedness are both situational (e.g., similar
work environments and conditions) and dispositional (i.e., processes of attraction–selection–attrition).
These antecedents lead to a common interpretation, understanding, and attitudinal evaluation of the
job experience [12].
Within the reviewed literature, four studies omit a definition of collective satisfaction and three
studies adopt the ”group task satisfaction” definition, which refers to “the group’s shared attitude
toward its tasks and work environment” [12] (p. 1). Mason & Griffin [35] di↵erentiate ”group task
satisfaction” from ”individual job satisfaction” in that group-level attitudes will focus on the task
for which the whole group is responsible and common aspects of the work environment rather than
developing a shared attitude toward any one individual’s job.
Int. J. Environ. Res. Public Health 2020, 17, 69
8 of 39
Operationalization of Collective Satisfaction. Operationalizations of collective satisfaction
appear in diverse formats across studies: global vs. facets satisfaction, individual vs. team referents,
and di↵erent instruments.
Global vs. Facets Satisfaction. Six studies reported global measures of job satisfaction, in which
a few items capture an overall feeling about satisfaction with the team or work-unit (e.g., ”we are
satisfied with each other’s contribution to our team”). Global satisfaction refers to a general attitude
towards the team, and is distinct from satisfaction with facets or various features of the job. One study
reported measures of satisfaction with facets such as tasks, rewards, supervision [35]. Both global
and facets satisfaction scales are valid measures and preference for either one of them depends on the
diagnostic vs. general purpose of the evaluation [40,41].
Informants and Referents. Team or work-unit members were the informants of job satisfaction
in all studies and their responses were aggregated at the unit level. Six studies reported the use of
individual referents (i.e., I am satisfied with . . . ), and Mason & Griffin [35] used both individual and
team referents (i.e., My team is satisfied with . . . ) to measure aggregated “individual task satisfaction”
and “group task performance” respectively. Regarding the debate about using individual or group
referenced measures, Mason & Griffin [35] advocate the use of group referenced measures in preference
to the individual referenced measures. In their empirical study, the group referenced ”group task
satisfaction” measure explained variance in sportsmanship behavior and group absenteeism norms
beyond aggregated “group members’ individual job satisfaction ratings”. Whitman et al. [12] in their
meta-analysis compared the use of organization vs. job referent, finding unit-level organizational
satisfaction more strongly related to unit-level performance (rho = 0.39) than unit-level job satisfaction
(rho = 0.33). These results, although restricted to a limited amount of studies, suggest that the
referent used does a↵ect the satisfaction–performance relationship and the authors advocate the use of
collective referents.
Collective Satisfaction Measures. We found two validated instruments of satisfaction used at
the collective level to grasp the extent to which members are satisfied with their teamwork. The “group
task satisfaction scale” [35] consists of 10 items to tap into three dimensions: satisfaction with the
task itself (e.g., work stimulating, fulfilling), satisfaction with the group’s internal work environment
(e.g., the way they work together, conflict among team members), and satisfaction with the group’s
external work environment (e.g., senior managers, support, resources, policies, rewards). This scale
uses a group referent, i.e., “our team finds its work stimulating”. Furthermore, one study reported
using the Minnesota Satisfaction Questionnaire [42] (20 items) to measure “aggregate individual job
satisfactions” [35], and each one of the remaining studies used a di↵erent scale to the rest (two used
2-item scales, two used 3-item scales, one a 4-item scale, and one a 10-item scale).
Summary Collective Satisfaction. Group or team satisfaction has been defined as “a shared
positive attitude towards a work-related object (i.e., the job, the team’s task, and the team’s
environment)”. However, many studies have used individual referents and relied on a measure
of “aggregated individual job satisfactions”. As an attitude, definitions incorporate both cognitive
and a↵ective evaluations of shared job experiences, but the evaluations of work-unit satisfaction are
predominantly cognitive and stable [43] and “the a↵ective property of job attitudes lay relatively
inert” [43] (p. 362).
Overall, the lack of homogeneity in the use of instruments, number and content of items, and scale
origin is remarkable. The widespread heterogeneity in operationalizations of team satisfaction is likely
to a↵ect the comparability of studies and results. We believe using validated team satisfaction scales
(e.g., “group task satisfaction”), and combining global and team-facets satisfaction measures would
strongly contribute to a more appropriate operationalization and understanding of team satisfaction
and of its connection with team performance.
Definition of Group A↵ect. Group a↵ect refers to the homogeneous a↵ective states within the
group [44] (p. 781). More specifically, it relates to the mood states team members experience or feel
while on the job or in team meetings [45]. Research on group a↵ect involves the study of a↵ect, moods,
Int. J. Environ. Res. Public Health 2020, 17, 69
9 of 39
and emotions at a collective level [5]. Most authors provide definitions of group positive a↵ect with
two components: “shared or homogeneous or consistent” and “a↵ective states, feelings, a↵ective
reactions, emotions or moods”. They use the terms within each component as almost synonymous
in their definitions of group a↵ect, notwithstanding recognition of some di↵erences among concepts
(for instance, between emotions and moods) [46]. All these terms refer to how people feel, whether
positive or negative (i.e., valence), and more or less activated (i.e., activation) [46].
Group a↵ect, as a collectively shared pattern of a↵ective states among group members, is a
meaningful construct at the team level of analysis and an important factor that shapes group processes
and outcomes [5]. Following Barsade & Gibson [47], group a↵ect can be characterized through two
approaches. A top-down approach in which group a↵ect as a whole acts upon the emotions of the
individuals within it, and a bottom-up approach in which group a↵ect emerges as the result of the
aggregate of individual group members’ a↵ective states and traits. The group a↵ect literature reviewed
emphasizes the bottom-up approach and emotional contagion as the main mechanism explaining
the emergence of group a↵ect as a group level phenomenon. This view is complemented with the
top-down influence of transformational leadership, which appears as a relevant antecedent of group
a↵ect within this literature.
Operationalization of Group A↵ect. Seven studies used validated measures of positive group
a↵ect, namely six studies used PANAS (Positive and Negative A↵ective Scale) [48], and one used the
A↵ective Well-being Scale [49]. The rest used a variety of scales ranging from 3–10 moods or emotions.
PANAS has been criticized for its focus on high activation moods, and some researchers advocate
complementing it with low activation moods [46].
The periods and statements accompanying the items are also diverse. One study measured group
mood felt “at the very particular moment”, four studies have referred to “the past week”, one “in
the last weeks”, one “in the past two weeks”, one “in the past six months”, two “in the past year”,
two “in general”, and two do not specify time frames. There is a debate about the advantages and
disadvantages of di↵erent time frames to measure group a↵ect. Although “current mood states may
be more accurately and reliably reported than recalled moods” [46] (p. 345), other authors suggest that
group mood or emotion is a group’s temporally stable, basic temperament, with an overall positive or
negative cast [50].
Additionally, operationalizations refer to how the team members have felt at work/job/at the
store (five studies), at team meetings (three studies), or do not refer a particular situation (six
studies). Regarding informants, team-members reported their positive a↵ect in 13 studies, and only
Rego et al. [38] had the store manager as an informant of team-members’ positive a↵ect. They argue
that “the store supervisor is, to a certain degree, an observer of the stores’ a↵ective tone and behaves
toward the store according to this perception/observation” (p. 69).
Summary Group A↵ect. Group positive a↵ect refers to how the team members have felt for a
certain period of time (i.e., past week, or during a team meeting). Similar to collective satisfaction,
group a↵ect focuses on the a↵ective component of working in a team or work-unit. As opposed to
team satisfaction (with a↵ective-cognitive components), there only appears an a↵ective component,
and there is no reference to specific aspects of the job/work, just a↵ect (e.g., such as pleasure) while
working or at work or at team meetings.
Definition of Team Work Engagement. The concept of personal engagement was introduced by
Kahn [51] as “the behaviors by which people . . . employ and express themselves physically, cognitively,
and emotionally during role performances” (p. 694). Macey & Schneider [52] built on Kahn’s view to
develop a theoretical framework that describes how some distal antecedents (i.e., job characteristics or
leadership) influence engagement levels, which in turn a↵ect performance outcomes. Furthermore,
Schneider et al. [53] defined engagement as having two major components: the feelings of engagement
or the heightened state of energy and enthusiasm associated with work and the organization, and
engagement behaviors such as persistence of tasks, being proactive and taking on responsibilities
when the need arises, all in the service of accomplishing organizational goals. This conceptualization
Int. J. Environ. Res. Public Health 2020, 17, 69
10 of 39
of engagement has been applied to the organizational level [53,54] but to our knowledge not to the
team level.
A second conceptualization with a business engagement perspective refers to engagement as
“the individual’s involvement and satisfaction with as well as enthusiasm for work” (The Gallup
Organization). This definition has been criticized for evaluating satisfaction together with, or instead
of, engagement [52]; and the associated instrument (Gallup Q12, or Gallup Workplace Audit) for
lacking face or construct validity [6,12]. Still, a meta-analysis with Q12 found a true score correlation
of r = 0.42 between collective “satisfaction-engagement” and composite business-unit performance
outcomes (e.g., customer satisfaction, productivity, profit, employee turnover, and accidents) in
American for-profit companies [55]. A third stream of engagement research developed in Europe has
become dominant [6] to a great extent due to the development of the Utrecht Work Engagement Scale
(UWES) [56]. Within this perspective, engagement has been examined as a team-level construct [57].
Team engagement refers to “a positive, fulfilling, work-related and shared psychological state
characterized by team work vigor, dedication and absorption which emerges from the interaction
and shared experiences of the members of a work team” [58] (p. 107). Thus, engaged team members
have high levels of energy and work hard (vigor), are enthusiastic about their work (dedicated), and
are often fully immersed (absorbed) in their job so that time flies [59]. Emergence of team work
engagement is attributed to the interaction and shared experiences of team members through two types
of processes: implicit (i.e., emotional contagion) and explicit (i.e., team members sharing workplace
experiences) [60]. A second definition of team engagement refers to it as “a shared, positive and
fulfilling, motivational emergent state of work-related well-being” [61] (p. 35). Although Costa et al. [61]
referred to engagement as a motivational state in their definition, they also contend that “Team work
engagement seems to be a promising construct for future research on the a↵ective and motivational
emergent states of work teams” (p. 43).
Sonnentag [17] attempts to clarify conceptual boundaries and reflects on whether work engagement
is a motivation or a well-being construct; she concludes that “work engagement and thriving as positive
well-being concepts seem to be closely related to motivational and behavioral processes. Conceptually,
however, they emphasize the experience of energy, dedication, absorption, and growth—as opposed to
actual behaviors” (p. 264).
Operationalization of Team Work Engagement. We identified two measures of team work
engagement: UWES and Team Work Engagement construct. In all cases, team members were the
informants about the team’s work engagement and their responses were aggregated at the team level.
Seven studies measured team engagement through di↵erent versions of the UWES scale: one used the
18-item version, one used the 17-item version, four used the 9-item version, and two used the 3-item
version. Five studies used a team referent (i.e., “My team . . . ”), three used an individual referent (i.e., “I
am enthusiastic about my job”), and one study used both individual and team referents [62]. A second
instrument, the team work engagement construct [61], has been validated to measure team work
engagement and di↵erentiate it from individual work engagement. It consists of nine items, measuring
it as a team property with a team referent (i.e., “we are proud of the work we do”). Results show the
nine items to converge in a single-factor structure. Two studies from our literature search used this
instrument (4 and 9 items).
Summary Team Work Engagement. Although di↵erent conceptualizations of engagement exist,
when it comes to research of collective work engagement at the team level within our literature review,
all authors have defined it following the Utrecht perspective: “a positive, fulfilling, work-related and
shared psychological state characterized by team work vigor, dedication and absorption which emerges
from the interaction and shared experiences of the members of a work team” [63]. Some authors have
distinguished work engagement from job satisfaction in aspects such as level of activation (engagement
high activation vs. satisfaction low activation), and work engagement from motivation [17]. Team work
engagement is more related to an eudaimonic perspective of well-being, i.e., closer to feeling authentic
and meaningful in one’s life [17], than a hedonic perspective emphasizing pleasure and absence of
Int. J. Environ. Res. Public Health 2020, 17, 69
11 of 39
pain. Feeling engaged may be accompanied by positive and/or negative emotions. Thus, the main
emotion in engagement is not pleasure like in hedonic constructs, but interest in order to pursue
gratification [64]. Thus, engagement would explain team e↵orts in unpleasant conditions such as when
team members ignore physical or mental exhaustion and continue working to achieve their objective.
Unfortunately, operationalizations of collective engagement following the North American
perspective based on the work by Kahn, and Macey and Schneider [52] have been applied to the
organizational level [54,65] and to our knowledge not to the team level. All studies within our
systematic review have followed the European perspective on work engagement and used the two
validated measures of the construct at the team level: UWES and Team Work Engagement scale.
These scales o↵er the benefits of consisting of a manageable amount of items, using team referents,
o↵ering adequate psychometric properties, and allowing for comparability among studies.
3.2.2. Research Question 2: Which Theoretical Frameworks Are Used to Explain the Collective
Happy-Productive Work-Unit Thesis? Which Third Variables A↵ect the Relationship between
Well-Being and Performance in the Empirical Research Models (Mediators, Moderators, Antecedents)?
In this section, we describe the main theoretical frameworks underpinning the relationship
between collective well-being and collective performance (see Table 2). We structure the findings
around each of the collective well-being constructs. The relationship between collective well-being and
performance is usually embedded in wider research models including third variables. Depending on
the theoretical models and specific hypotheses, third variables may have a role as antecedents of the
main variables, mediators between well-being and performance, or moderators that explain when or
how the main HP relationship is stronger or weaker. Thus, we also describe third variables found in
the research models.
The Collective Satisfaction Literature: Theoretical Frameworks. The seven studies identified
in the systematic review considered collective satisfaction as an antecedent of collective performance.
The main theoretical framework supporting the research models is the HPWT applied to the
team level. In the early 1990s, Ostro↵ [66] applied the happy–productive thesis to the collective
(organizational) level. She argued that satisfaction and the happiness of personnel would heighten
organizational e↵ectiveness through employees’ behaviors and responses at work. Building on
the arguments from the sociotechnical and human relations schools, she proposed that positive
attitudes trigger productivity-related behaviors, which in turn lead to organizational e↵ectiveness.
These productivity-related behaviors relevant to organizational e↵ectiveness encompass attachment
behaviors (i.e., attending to and staying in the organization), performance behaviors (i.e., job-related
tasks) and citizenship behaviors (cooperation and collaborative e↵orts) [67]. A central mechanism is
collaborative e↵ort, in her words “satisfied employees will be more likely to engage in collaborative
e↵ort and accept organizational goals that can increase productivity, whereas dissatisfied employees
. . . may fail to work collaboratively (p. 964)”.
At the unit-level, Koys [33] proposed that “shared values or attitudes” are the key to the relationship
between unit-level employee job satisfaction and organizational e↵ectiveness. These shared attitudes
lead to appropriate behaviors, which lead to organizational e↵ectiveness. He also referred to
collaboration as a key process between shared attitudes and productivity: “If a unit’s employees
share positive attitudes, they should have norms of cooperation and collaboration, which in turn
enhance unit productivity (p. 102)”. These first studies suggest the general idea that a shared
attitude leads to collaborative behaviors among team members and subsequent improved work-unit
performance. Following a similar reasoning, Whitman [12] proposed that OCB (e.g., a measure of team
contextual performance) mediated the e↵ects of work-unit satisfaction on performance (a composite of
three criteria—productivity, withdrawal, and customer satisfaction). Testing this mediation through
meta-analytical correlations, they found a small but significant mediator e↵ect of OCB between
satisfaction and performance.
Collective Well-Being
A shared attitude (or shared
positive emotional state)
towards the team task
and environment
Defined as
Broaden-and-build theory
Mood-as-input model
Happy productive thesis
Human relations school
Social exchange theory
Linkage research
Service-profit chain
Theoretical Frameworks
Motivational process triggered by job
resources and demands
Improves specific team processes:
cognitive, motivational,
attitudinal, behavioral
Attitude–behavior link:
Facilitates collaborative e↵ort,
acceptance of goals, interactions
and dependencies
Mechanisms Linking Well-Being
and Work Performance
UWES: Utrecht Work
Engagement Scale (for teams)
Team Work Engagement Scale
Positive A↵ect
(PANAS)
Emotion scales
Aggregated Job Satisfaction
Group task satisfaction
Most Popular Measures
12 of 39
Team Satisfaction
Positive a↵ect while on the job
or during team meetings
(transient mood)
Job-demands-resources model
of work engagement
Broaden-and-build theory
Int. J. Environ. Res. Public Health 2020, 17, 69
Group A↵ect
Positive, fulfilling, work-related
shared state of vigor, dedication,
and absorption
Table 2. Theoretical frameworks linking collective well-being and collective performance.
Team Work Engagement
Int. J. Environ. Res. Public Health 2020, 17, 69
13 of 39
One study within the reviewed literature [36] found empirical support for a partial mediation
of OCB between high performance work systems and departmental performance (e.g., overall
departmental performance score based upon the percentage of success on each of the performance
metrics tracked by the Welsh government) in a sample of 119 local government departments.
A related and complementary argument why happy work-units would be productive work-units
refers to social exchange theory [68]. Thus, three studies propose that when (work-unit) employees
are satisfied with their job or work-unit [33,69] or with high performance work systems provided by
their companies [36], they would reciprocate with positive behaviors such as OCB to benefit the unit
or organization. An additional theoretical background is applied to explaining the relationship
between collective satisfaction and a specific type of performance (i.e., customer satisfaction).
Three studies [33,37,70] refer to the service climate framework or the linkage research model [71,72] and
the service-profit-chain model [73]. The service climate framework posits that a unit’s service climate
(positive and strong-shared perception of service as a focus) leads to service behaviors, such as in-role
behavior and customer-focused OCB as a mediator, which subsequently leads to positive customer
experiences (quality, satisfaction, and loyalty). The service-profit-chain model posits that employees’
capability, satisfaction, and loyalty, would lead to satisfied and loyal customers, who tend to purchase
more and increase organizational revenue and profits [33]. Two studies report positive and significant
correlations between collective satisfaction and customer satisfaction [33,70].
Regarding empirical support, 15 out 22 correlations reported in cross-sectional studies proposing
a happy–productive relationship are statistically significant and positive (range 0.17 to 0.63); seven
with team task performance (range 0.27 to 0.63), three with team contextual performance (range 0.36 to
0.61), two with customer satisfaction (range 0.49 to 0.57) and four with objective financial criteria (range
0.19 to 0.43). Non-significant results are obtained between collective satisfaction and one measure of
supervisor-rated performance [35], one with customer satisfaction [33], and three measures of financial
profit [33,37].
Collective Satisfaction:
Third Variables Included in HP Research Models.
Antecedents a↵ecting work-unit satisfaction (and collective performance) are related to transformational
leadership and leader empowering behaviors, team task characteristics, high-performance work
systems, and work-unit climate. In one study, leaders’ positive moods led to both transformational
leadership and positive group a↵ective tone, which then led to team processes such as team
satisfaction, and in turn enhanced team sales performance [45]. A second study in a restaurant
chain found that leader empowering behaviors increased work-units’ employees psychological
empowerment, which in turn enhanced work-unit employee satisfaction, which consequently
improved customer satisfaction [70]. Team task characteristics (task autonomy and feedback) were
relevant antecedents of team member satisfaction, which together with task meaningfulness enhanced
team performance [69]. In another study, high-performance work systems (HPWS) was an antecedent
of departmental job satisfaction, which subsequently improved department performance [36]. Finally,
Van De Voorde et al. [37] found that two work-unit climates (service orientation and goals orientation)
increased work satisfaction.
Furthermore, Whitman et al. [12] analyzed in their meta-analysis the moderating role of several
variables that need to be taken into account to understand when and under which conditions collective
satisfaction and collective performance are related. Results showed that the satisfaction-performance
relationship was moderated by the strength of unit consensus (rho = 0.32 for high consensus vs.
rho = 0.22 for low consensus), industry type (stronger in the education vs. business sector); stronger for
government units vs. for-profit sector. They concluded that “the strength of the relationship – though
always positive-depended a great deal on how criteria were conceptualized, aligned, and constructed”
(p. 72). In a meta-analysis on situational strength as a moderator of the relationship between job
satisfaction and job performance [3], satisfied employees were more likely to be productive employees
in those situations in which employees have a fair amount of discretion in deciding how to perform
Int. J. Environ. Res. Public Health 2020, 17, 69
14 of 39
their work. We did not find similar studies at the work-unit level, but a similar moderator e↵ect of
discretionary behavior may exist for groups and work-units.
In summary, the theoretical arguments within the collective satisfaction literature refer to the
HPWT, the general attitude-behavior link, social exchange theory, and linkage research model or
service-profit chain. Both theory and empirical evidence suggests that contextual performance (e.g.,
OCB) is a mediator between collective satisfaction and objective performance, i.e., attitudes lead to
collaborative behaviors. The HPWU relationship seems stronger for higher degrees of sharedness of
collective satisfaction [12]. Work-unit satisfaction may be increased by antecedents such as leadership
behaviors, team task design, HPWS, and work-unit climate.
Group A↵ect Literature: Theoretical Frameworks. All fourteen studies on group a↵ect consider
group a↵ect as the antecedent of performance. The dominant theoretical framework in the group
a↵ect–performance literature is the “broaden-and-build” theory [74], which has been applied both at
the individual and team level. This model has been complemented with the mood-as-input theory [75],
recently applied to the team level. The rationale behind the broaden-and-build theory is that in a
isomorphic way as it happens at the individual level, “positive group emotions may broaden the
group’s range of attention, cognition, and action and build social resources such as friendship among
the members” [76] (p. 74). In addition, positive emotions build long-term physical resources (e.g.,
better health), intellectual resources (e.g., knowledge), social resources (e.g., help and cooperation),
and psychological resources (e.g., resilience) among individuals and team-members.
Rhee [76] explored the role of group-member interactions as the underlying mechanism of the
relationship between group emotions and group outcomes. She proposed three main interaction
processes as mediators between positive group emotions and group outcomes: building on each other’s
ideas, morale-building communication, and affirmation. Building on each other’s ideas among the
group members (e.g., being attentive to others’ ideas and expanding the original idea to improve idea
quality) is the manifestation of cognitive broadening and social spontaneity at the group level. On the
other hand, morale-building (e.g., encouraging the group’s achievements and successful outcomes)
and affirmation of each other’s ideas (e.g., accepting and supporting others’ opinions) manifest social
spontaneity and building social resources. Rhee contends that these positive interaction processes
have an e↵ect on outcomes such as creativity, team-member learning, satisfaction with the group, and
the quality of group decision making.
The literature reviewed on group a↵ect has proposed and tested cognitive, motivational, attitudinal,
and behavioral team processes as mediators between group a↵ective tone and team performance.
For example, transformational leadership and positive a↵ective tone enhanced team performance
(perceived and objective) through team goal commitment (i.e., motivated team members pursue
team goals), team satisfaction (i.e., satisfied members in terms of their team tasks and environments),
and team helping behavior (i.e., team members exhibit more helping behaviors) in a sample of 85 sales
teams in Taiwan [45]. In another study, positive emotions were positively related to team resilience
(i.e., the process to face o↵, persevere and respond positively in the face of adversity), and team
resilience was positively related to team in-role (i.e., task) and extra-role performance as reported by
the supervisor in a sample of 216 teams [77].
Seong & Choi [78] reported a significant role of group positive a↵ect in predicting group
performance through group-level fit (i.e., the presence of shared goals among members and the
collective pursuit of congruent goals) and group conflict in a sample of 96 Korean teams in the defence
industry. Another study found support for the mediating role of team reflexivity (i.e., the extent to which
team members collectively reflect on and communicate about the team’s objectives, strategies, and
processes) and team promotion focus (i.e., team level motivational state that regulates and coordinates
the team’s e↵orts toward approaching positive outcomes) between group positive a↵ect and team
creativity [79]. Moreover, Kim & Shin [80] found that cooperative group norms and group positive
a↵ect were significant predictors of team creativity, and that this relationship was fully mediated by
collective efficacy (i.e., a sense of collective competence shared among team members with respect to
Int. J. Environ. Res. Public Health 2020, 17, 69
15 of 39
responding to specific situational demands and allocating, coordinating, and integrating their resources).
Peñalver et al. [81] found full-mediation e↵ect of group social resources (i.e., teamwork, coordination,
supportive team climate) between group positive a↵ect and in- and extra-role performance.
As mentioned earlier, a second relevant theoretical framework to explain the relationship between
group a↵ect and collective performance refers to the mood-as-input theory [75]. This model states
that people use their current mood as an information, and the interpreted meaning and consequences
of their mood on their behavior depend on the organizational context in which the mood was
formed [82,83]. The model also focuses on the relationship and potential interaction between negative
and positive a↵ect to predict creativity. Negative a↵ective tone informs work-unit members that the
situation is problematic and leads them to feel the need of carrying actions to remedy the situation [38].
Group negative a↵ect adopts a moderator role (see next section).
Regarding empirical support, 16 out 24 correlations reported in group a↵ect cross-sectional studies
proposing a happy–productive relationship are statistically significant and positive (range 0.13 to 0.58);
two with member-rated task performance (0.35, and 0.56), four with leader-rated task performance
(range 0.13 to 0.58), one with member-rated contextual performance (0.40), two with leader-rated
contextual performance (0.14, and 0.20), one with member-rated creativity (0.34), four with leader-rated
creativity (range 0.40 to 0.47), and two with objective financial criteria (range 0.19 to 0.43).
Group A↵ect: Third Variables Included in HP Research Models. Antecedents of group a↵ect
found in the literature are related to organizational support climate and leadership. For instance,
team climate of support from the organization (i.e., the extent to which team members believe the
team is supported by the organization and their managers) was shown to be positively related to
positive team mood, which in turn was relating to team performance in a sample of bank branches [39].
Regarding leadership, di↵erent studies propose that the leader is a relevant initiator of a particular tone
of group a↵ect, which disseminates among members through a contagion process. Leader positive
moods led to transformational leadership [45] and positive group a↵ective tone [45,78]. Finally,
transformational leadership positively predicts positive group a↵ective tone through team learning
goal orientation (i.e., team members’ shared tendencies to develop competence by acquiring new skills
and learning from experience) [84].
Moderators. A meta-analysis showed that positive group a↵ect has consistent positive e↵ects
on task performance regardless of contextual factors such as group a↵ect source (exogenous or
endogenous to the group) and group life span [11]. However, other contextual factors such as group
identification, team trust, or the presence of negative a↵ect have proved their influence on the positive
group a↵ect–performance relationship. For example, positive group a↵ective tone had a stronger
positive influence on willingness to engage in OCB and on perceived team performance when group
identification (i.e., the extent to which people define themselves in terms of their group membership)
was high [46]. In a second study, positive group a↵ective tone was beneficial for team creativity when
team trust was low, and detrimental for team creativity when team trust was high [85]. As seen earlier,
negative group a↵ect is an additional boundary condition with the potential to enhance the e↵ect of
positive a↵ect on team creativity [38,82]. For example, Tu [83] found that negative a↵ect might be
positively related to employee creativity, when contextual factors are supportive (i.e., organizational
support is high and organizational control is low) in a sample of 106 new product development
(NPD) teams working for high-technology Taiwanese firms. In another study in a Brazilian retail
chain, negative a↵ective tone made the relationship between positive a↵ective tone and creativity
stronger [38]. The authors contend that negative a↵ective tone may help employees to broaden their
modes of creative thinking to identify and solve problems/difficulties. Similarly, Tsai et al. [85] found
that positive group a↵ect enhanced creativity when team trust was low and negative group a↵ect
was high.
In summary, the theoretical frameworks underpinning the HPWU literature on group a↵ect are
the broaden-and-build theory and the mood-as-input theory. Following these theories, positive group
a↵ect broadens and activates the teams’ (cognitive, motivational, attitudinal, and behavioral) processes
Int. J. Environ. Res. Public Health 2020, 17, 69
16 of 39
and interactions over a specific period of time leading to improved team performance. Moreover,
this literature is starting to take into account the potential interaction of positive and negative group
a↵ect and the influence of contextual conditions (e.g., trust, group identification, organizational support,
or control) on the HPWU relationship.
Team Work Engagement Literature: Theoretical Frameworks. Team work engagement is
considered a predictor of collective performance in the nine studies we found in the systematic review.
The job demands-resources model of work engagement (JDR-WE model) is the main theoretical
framework used to explain why higher levels of engagement lead to increased performance [86].
The JDR-WE model is a model of employee motivation [87]. Its main proposition is that job resources
(e.g., social support, autonomy) and personal resources (e.g., self-efficacy, optimism) have a positive
impact on engagement, particularly when job demands (e.g., workload, emotional demands) are high.
Specifically, challenging job demands (vs. hindering job demands) have the potential to promote
employees’ growth and achievement together with their motivation toward the task. In turn, work
engagement has a positive impact on job performance.
The mechanisms operating between team engagement and performance replicate the arguments
given at the individual level on how vigor, dedication, and absorption may lead to increased
performance. For example, Mäkikangas [88] stated that: “As work engagement is a motivational
state characterized by an employee’s will and drive to perform well at work [89], it is reasonable to
use it as a predecessor of team job performance” (p. 773). A more detailed explanation was o↵ered
by Costa [87] who proposed that engaged teams are energetic when working, display active and
productive behaviors, are willing to help each other and build on each other’s ideas, and consider
their task meaningful and relevant. García-Buades et al. [90] contend that shared team engagement
additionally contributes to teams’ performance due to emergent phenomena such as the team members’
alignment towards common goals, increased synergies among members, and better cooperation and
interaction processes. The studies identified in the systematic search provide similar arguments about
the mechanisms explaining the collective engagement–performance link. However, little research has
been conducted on these mechanisms.
Furthermore, it is worth mentioning some multilevel e↵orts in the team work
engagement–collective performance literature, which contribute to clarify the relationship between
team-level constructs and individual level constructs. For instance, individual and team work
engagement were associated with high levels of perceived team performance in 102 Finnish teams
from the educational sector [88]. Another study found that team work engagement was significantly
related to team performance, but it also predicted individual performance through individual work
engagement (vigor) [62].
Regarding mediators, only one study proposed and found support for service climate and
employee performance to mediate an indirect relationship between team engagement and customer
loyalty in 114 service units in the hospitality industry [91].
The nine cross-sectional studies proposing a happy–productive relationship based on team work
engagement reported 8 out of 11 correlations to be statistically significant and positive (range 0.24
to 0.54); four with member-rated task performance (range 0.30 to 0.54), three with leader-rated task
performance (range 0.24 to 0.30), one with member-rated contextual performance (0.38). Although two
correlations between team work engagement and customer satisfaction were not significant, results
with path analysis found an indirect relationship with customer satisfaction [91] and results with
multilevel analyses found a significant e↵ect of team engagement on service performance when climate
for innovation was high [90].
Team Work Engagement: Third Variables included in HP Research Models
Regarding antecedents, a meta-analysis by Christian et al. [7] found that job resources are the
most relevant predictor of work engagement. Within the studies identified in the systematic search,
team resources arise as relevant antecedents of team work engagement. For example, team resources
(supportive team climate, coordination, and teamwork) predicted team work engagement, which
Int. J. Environ. Res. Public Health 2020, 17, 69
17 of 39
in turn predicted performance [58]. Other team resources a↵ecting team work engagement are
performance feedback, social support from co-workers, support from supervisor, and information
available [87]. In the same study, a direct negative e↵ect of task conflict was found on team work
engagement [87]. In another study, transformational leadership increased team work engagement,
which in turn enhanced team performance [57].
Another antecedent of team work engagement is team job crafting or collaborative crafting (i.e.,
the process by which groups of employees determine together how they can alter their work to meet
their shared work goals). Team job crafting predicted team work engagement which then predicted
leader-rated performance [92], and team-rated performance [62]. In a similar vein, McClelland et
al. [93] found support for a model in which collaborative crafting led to three team processes (team
efficacy, team control, and team interdependence), which then led to team work engagement and
subsequent improved performance in a sample of 242 call centre teams.
Moderators. Some moderators have been shown to strengthen the influence of team work
engagement on performance such as task conflict [87], and climate for innovation [90]. In a study with
research teams, Costa et al. [87] found that task conflict may enhance the benefits of engaged teams
on objective performance, because engaged teams are more open to discussing new ideas positively
and can integrate their members’ contributions better. In another study, multilevel analyses showed
significant positive direct relationships between team engagement and service quality indicators in
hotel and restaurant units, and a consistent moderating role of climate for innovation—recognition
of employees’ ideas and suggestions to improve work methods and the service delivered—so that
the relationship between team engagement and service performance became stronger as climate for
innovation increased [90].
In summary, the main theoretical framework at the base of the HPWU literature on team work
engagement is the job–demands–resources model of work engagement. Thus, team resources increase
engagement, particularly when challenging demands are high, creating a positive a↵ective-motivational
shared state, which leads to improved team performance. This literature emphasizes a varied array
of team resources, which increase team work engagement, and in turn enhance team performance.
Moreover, it benefits from some examples of multilevel research, which takes into account the e↵ects of
team-level well-being and behavioral processes together with individual well-being and performance.
3.2.3. Research Question 3: What Is the Evidence for Causal or Reciprocal Relationships between
Collective Well-Being and Collective Performance?
Despite the frequently reported positive significant correlations, the causal relationship between
well-being and performance is far from clear. Does well-being increase performance? Or does good
performance increase well-being? In the most recent meta-analysis about satisfaction, citizenship
behaviors, and performance in work units, Whitman et al. [12] reported the lack of enough longitudinal
studies to meta-analytically test causal relationships between collective satisfaction and performance
at the unit-level. Therefore, in this section, we first summarize the findings on two meta-analyses
on causal HP relationships at the individual and organizational level [94,95]. Then, we describe
the findings about causal or reciprocal relationships between collective well-being and collective
performance at the work-unit level.
Two important meta-analyses published at the individual and organizational level provide
interesting findings on causal relationships between well-being and performance. At the individual
level, Riketta (2008) conducted a meta-analysis of 16 panel studies finding support for job attitudes
to increase performance (in-role, extra-role, and objective performance) after controlling for baseline
performance, whereas e↵ects of performance on subsequent job attitudes were nonsignificant. E↵ects
of job attitudes on performance were stronger for shorter time lags (less than 6 months compared to
longer time lags) suggesting that time lag was a moderator of the cross-lagged relationship. Riketta [94]
suggests that attitudes e↵ects may be short lived and recommends exploring shorter spans (e.g.,
a few days). Furthermore, Riketta [94] found a counterintuitive negative e↵ect of performance
Int. J. Environ. Res. Public Health 2020, 17, 69
18 of 39
on job satisfaction for moderate time lags, which he attributed to people who perform strongly
but do not perceive to be adequately rewarded for their performance. Based on these results,
he suggests studying the potential moderating role of reward systems and justice perceptions on the
job satisfaction–performance relationship (p. 479).
At the organizational level, a meta-analysis by Schneider et al. [95] using data from 35 companies
over 8 years showed organizational financial and market performance to be predictors of overall
job satisfaction and satisfaction with security more strongly than the reverse. They also reported a
more reciprocal relationship of organizational financial and market performance with satisfaction
with pay, which they suggest may be mediated by OCB. The authors contend that “the relationship
between employee attitudes and organizational performance is complex, and it is too simplistic to
assume that satisfaction attitudes lead to organizational financial or market performance—some do
and some do not, and some employee attitudes apparently are the result of financial and market
performance” (p. 849). They also suggest that non-financial organizational outcomes may show a
stronger relationship with satisfaction than financial performance.
Five studies investigated time-lagged or longitudinal HP relationships at the work-unit level,
three on collective satisfaction [33,36,37], and two on group positive a↵ect [38,39] (see Table 3 for a
summary). In an empirical study, Koys [33] addressed the issue of whether work-unit satisfaction and
behaviors (OCB and turnover) influenced business outcomes (profitability and customer satisfaction) in
a sample of 28 restaurant units from a chain, and explored the reverse relationship as well. In stressing
the relevance of behaviors, he argued that “employee attitudes cannot influence organizational
e↵ectiveness on their own; employees must also behave appropriately” (p. 103). Results supported
the HP model, in that human resources outcomes (work-unit satisfaction and behaviors) influence
work-unit e↵ectiveness, rather than the other way around. More specifically, cross-lagged regression
analyses showed that unit-level employee satisfaction, OCB, and turnover measured at year 1, predicted
two unit-level profitability measures at year 2 (R2 = 0.14, and 0.17), with only OCB having a significant
beta weight. The same independent variables predicted customer satisfaction at year 2 (R2 = 0.31), with
only unit-level employee satisfaction having a significant beta weight. Thus, OCB had an impact on
profitability, and employee satisfaction had an impact on customer satisfaction. This research supports
the idea that unit-level employee satisfaction leads to OCB, which in turn leads to profitability; and
additionally, employee satisfaction leads to customer satisfaction.
Messersmith et al. [36] studied the link between high-performance work systems (HPWS) and
time-lagged performance in a sample of 119 public service departments in Wales. Their results support
a research model in which department-level HPWS enhanced what they called the black box (employee
attitudes–job satisfaction, organizational commitment, psychological empowerment, and behaviors
(OCB)), which was further related to objective departmental performance. The authors highlight the
important role that aggregate discretionary behaviors (OCB) may play in the success of departmental
units. HPWS initiate a chain in which employees are more likely to engage in the prosocial behaviors
that help organizational units to meet goals and objectives. In combination, these helping behaviors
allow organizational units to be more efficient and flexible, as “employees are more likely to step
beyond the bounds of their narrowly defined job descriptions to assist each other as well as to help
maximize their overall departmental functions. In addition, this reciprocity is likely to have continual
positive e↵ects in the department as OCBs become enmeshed as a part of the established norms and
values in the culture of the unit” (p. 1114).
A third study explored the longitudinal relationships between work-unit climate and labor
productivity in a sample of 171 bank branches in the Netherlands [37]. Based on previous findings at the
individual level, the main hypothesis was that two climate types (goals and service orientation) would
positively influence (objective) productivity through increased work-unit satisfaction. The rationale is
that shared positive attitudes would be a prerequisite for engaging in collaborative e↵ort and accepting
organizational goals. They also explored the reversed causation model in which productivity would
increase the branch resources to invest in their employees, resulting in higher positive climate scores
Int. J. Environ. Res. Public Health 2020, 17, 69
19 of 39
and work attitudes. Contrary to their expectations, they found no evidence for work satisfaction as an
intermediary mechanism at the business level, and additionally they found no e↵ects between work
satisfaction and productivity. Thus, they concluded that the happy–productive thesis valid at the
individual level, does not obtain empirical support at the branch-level. They attributed these results
to the sample (business sector instead of multiple or educational), to the lower associations usually
found for longitudinal rather than cross-sectional associations (average time lag was 2 years), and to
the use of aggregated work satisfaction. They suggest that “at branch level, more active concepts like
OCB or work engagement may be more strongly related to unit performance compared to traditional
attitudinal concepts like work satisfaction” (p. 306).
Table 3.
Summary of time-lagged correlations between happy–productive teams and
productive–happy teams.
Happy–Productive
T1
T2
r
Time Lag
González-Romá et al.
(2012)
Team positive mood
Team positive mood
Team performance
0.39 **
1 year
Team e↵ectiveness
0.21 ns
Koys (2001)
Satisfaction
Satisfaction
Satisfaction
Satisfaction
Manager rated OCB
Profit sales
Profit year 2
Customer Satisfaction
0.19 ns
0.35 *
0.27t
0.61 *
1 year
Messersmith et al. (2011)
Job Satisfaction
Job Satisfaction
Department performance
Self-rated OCB
0.36 *
0.36 *
1 year
Rego et al. (2013)
Positive a↵ective tone
Performance subsequent
semester
0.07 ns
6 months
Van de Voorde et al.
(2014)
Satisfaction
Productivity
0.06 ns
Average 2 years
Productive–Happy
T1
T2
r
Time lag
Koys (2001)
Manager rated OCB
Profit Sales
Profit Year
Customer Satisfaction
Satisfaction
Satisfaction
Satisfaction
Satisfaction
0.32 *
0.15 ns
0.05 ns
0.36 *
1 year
Productivity
Satisfaction
0.02 ns
Average 2 years
Van de Voorde et al.
(2014)
Note. * p < 0.05. ns not significant.
Two time-lagged studies explored the relationship between group a↵ect and collective performance.
In a study with Spanish bank branches, a team climate of support from the organization was positively
related to positive team mood, which in turn was positively related to team members’ ratings of team
performance but not to leader-rated team performance [39]. Another study explored how store positive
a↵ective tone predicted store performance (i.e., sales achievement) in a sample of 94 Brazilian retail
stores [38]. Although the correlation and direct path between positive a↵ect and store performance were
non-significant, results showed that positive a↵ective tone predicted the stores’ performance through
the mediating role of creativity, even after controlling the e↵ects of preceding stores’ performance.
Thus, “happier” stores were more creative and more e↵ective (i.e., increased sales).
Two of these studies additionally explored a reverse causality direction [33,37] from performance
(Time 1) to happiness (Time 2). Koys [33] found a stronger correlation between collective work-unit
satisfaction (Time 1) and customer satisfaction (Time 2) (r = 0.61), than the reverse (r = 0.36). He also
found stronger correlations between collective work-unit satisfaction and two profit measures (r = 0.35;
r = 0.27), than the reverse (ns). On the other hand, he also reported a stronger correlation for
manager-rated OCB (Time 1) and collective satisfaction (Time 2) (r = 0.32), than the reverse (ns).
Van de Voorde [37] reported cross-lagged correlations between objective indicators of performance
(financial branch yearly productivity index) and collective satisfaction in two directions, both
were nonsignificant.
Int. J. Environ. Res. Public Health 2020, 17, 69
20 of 39
In summary, four out of five studies exploring causal relationships between collective well-being
and collective performance at the unit level provide empirical support to a happy–productive direction.
Three of them obtain support for a causal chain between unit-level well-being (work-unit satisfaction
or group positive a↵ect), unit-level behaviors (OCB or team creativity), and objective unit-level
performance (profitability, departmental performance, and sales respectively) [33,36,38]. These three
studies propose a causal chain in at least three steps “well-being–team performance–objective
performance”. Interestingly, the fourth study proposed a direct link between well-being and objective
performance, without considering a “team behavior” as a mediator, and found no empirical support
for the collective satisfaction–performance link. Overall, the very limited existing evidence suggests
that collective well-being would enhance relevant discretionary team behaviors (OCB and creativity),
which in turn increase objective productivity.
4. Discussion
The aim of this systematic review was to o↵er an integrated overview on the literature on
happy-productive work-units (HPWU). More specifically, we reviewed quantitative peer-reviewed
studies published between 2001 and 2018 on the relationship between collective happiness and
collective performance for teams and work-units. With our systematic review, we found 30 empirical
studies on HPWU, which adopted three main collective well-being constructs and four categories of
collective performance. Research has focused on hedonic well-being (satisfaction, 7 studies; group
A↵ect, 14 studies), and more recently on eudaimonic well-being (teamwork engagement, 9 studies).
We could not identify research on other eudaimonic constructs applied to teams (e.g., collective
flourishing, purpose or meaning of work), which could, we believe, further explain extra-ordinary team
e↵orts and success (e.g., such as the world-watched rescue of 12 soccer players from a flooded cave in
Thailand in July 2018). On the other hand, collective performance relies mainly on team performance
(task performance, OCB, creativity; supervisor-rated and member-rated), and less so on customer
satisfaction or financial/objective ratings. The literature on HPWU is scarce, diverse, and disintegrated.
There is diversity both in the operationalization of collective well-being and performance and in the
theoretical frameworks used.
Our main contribution is the analysis of the strengths, commonalities, and di↵erences across these
three well-being literatures to get a comprehensive picture of what is known on happy–productive
teams. To do so, we reviewed and summarized how collective well-being and performance is measured,
the theories that attempt to explain how happy teams become productive teams or productive teams
become happy, and whether both collective phenomena reciprocate. In this section, we summarize
and discuss the results following the research questions set out for the review, reflect on the limitations
of our study, and suggest avenues for future research.
4.1. Discussion
4.1.1. Research Question 1—Which Are the Main Features of the Conceptualization and
Operationalization of Collective Well-Being?
The HPWU literature builds on diverse conceptualizations and operationalizations of well-being
and performance. A question that remains open is about the relationship among the three constructs of
collective well-being and their relative contribution to collective performance. Far from addressing this
issue, the reviewed literature about collective well-being mostly ignores it. An exception is the work by
Mason & Griffin [35], who di↵erentiated and explored the e↵ects of group task satisfaction and group
a↵ective tone on group outcomes. They found “group task satisfaction” to explain unique variance in
civic helping and sportsmanship behavior, but not in leader-rated team performance, once the e↵ects of
aggregated “individual job satisfaction” and group a↵ective tone had been taken into account. Second,
the literature on positive group a↵ect considers team satisfaction as a mediator between group a↵ect
and performance, therefore placing group a↵ect as an antecedent of satisfaction. Positive group a↵ect
Int. J. Environ. Res. Public Health 2020, 17, 69
21 of 39
has been considered as an antecedent of both satisfaction [45] and engagement [6,7]. Third, literature
on engagement proposes satisfaction as either an antecedent or a consequent of engagement [6].
Although engagement and satisfaction have shown considerable overlap, enough discriminant validity
between them justifies their di↵erentiation [7]. Overall, only good quality, longitudinal research
studying simultaneously group a↵ect, group satisfaction, and team engagement will be able to
elucidate the relationship among di↵erent types of well-being, whether they overlap or complement
each other, and their relative contribution to performance.
Regarding collective performance, the overreliance on subjective e↵ectiveness measures is an
additional weakness of existing research. Although team-member and leader-rated team performance
are valid and useful measures of performance, studying more distal (e.g., customer satisfaction) or
objective team performance criteria would add extra value to future research. Task and contextual
team performance are the main focus of collective performance by the three well-being literatures.
A particular strength of the collective satisfaction literature is evaluating performance not only through
team performance (task performance and OCB) but also through distal team e↵ectiveness outcomes (i.e.,
customer satisfaction and/or financial performance). Besides, only group a↵ect researchers study team
performance by means of team creativity. Using a combination of multiple valid operationalizations of
collective well-being and collective performance would contribute to a more comprehensive picture of
the HPWU relationship and allow for sound comparisons among HP constructs.
Regarding operationalizations of collective well-being, despite some valuable contributions in
defining and measuring work-unit satisfaction [12,35], they had limited influence both on subsequent
research and extending the use of valid group-satisfaction measures. However, significant results
obtained across diverse operationalizations support the consistency of the relationship between
collective satisfaction and performance. Alternatively, operationalizations of group a↵ect and team
engagement are more homogeneous and uniform than measurement of satisfaction, thus allowing for
comparability among studies and results.
In general, recommendations for appropriate measurement of team-level well-being includes use
of valid instruments, use of team referents (vs. individual referents), and use of multiple informants
(e.g., leaders, peers). Furthermore, collective well-being ratings generally rely on the aggregated unit’s
average score. This method emphasizes sharedness of well-being, a core quality of collective well-being,
however there are calls to investigate the e↵ects of the strength of well-being among team-members
and over time. Additionally, an issue of substantial interest is to examine the amount of variability and
dispersion of work-unit well-being within a team and its influence on collective performance [12,96].
Overall, the variety in definitions and operationalizations of collective constructs make it difficult
to reach consistent conclusions about HP relationships but it provides a more comprehensive and
holistic view on these relationships.
4.1.2. Research Question 2—Which Theoretical Frameworks Are Used to Explain the Collective
Happy–Productive Work Unit Thesis?
The theoretical frameworks on the HPWU relationship and mechanisms linking collective
well-being and collective performance are specific for each body of literature. Regardless of the
consideration of well-being as hedonic or eudaimonic, it is implicitly or explicitly assumed that
well-being shared among team-members is a relevant antecedent of collective performance. In this
section, we reflect on the strengths of di↵erent theoretical e↵orts to explain how collective well-being
influences collective performance and the mechanisms through which shared well-being translates
into better team performance.
The literature on team satisfaction builds on the general research on attitudes and behavior.
The predominant theoretical framework expands the happy–productive thesis to the team level,
complemented with additional theoretical models like social exchange theory, linkage research, or the
service–profit chain. The rationale behind the HPWU thesis is that when collective satisfaction emerges
as a shared phenomenon, it activates collaboration and OCBs among team members (i.e., a measure of
Int. J. Environ. Res. Public Health 2020, 17, 69
22 of 39
team performance/processes), which subsequently leads to improved (objective) performance. Thus,
team satisfaction facilitates collaborative e↵ort towards, and acceptance of, organizational objectives.
The literature in satisfaction proposes and finds empirical support for “OCB” as a key mediator
between collective well-being and objective/financial performance, following a causal chain “collective
satisfaction–team performance (OCB)–financial performance” [12,33,97].
The literature on group a↵ect showed a strong focus on uncovering the mediating mechanisms
between well-being and performance. Building on the broaden-and-build theory [74], the rationale
is that shared positive group a↵ect activates relevant cognitive (e.g., goal setting and reviewing),
motivational (e.g., goal commitment), attitudinal (e.g., team satisfaction), and behavioral (e.g., providing
help and support) group processes, which subsequently improve performance. Existing cross-sectional
research finds empirical support for these mediating mechanisms. Based on the mood-as-input
model [75], another relevant contribution of the group a↵ect literature is the study of the combined
e↵ect or interaction between positive group a↵ect and negative group a↵ect on team’s performance
(e.g., mainly team creativity). Negative group a↵ect has been shown to enhance the positive e↵ects of
positive group a↵ect on team performance in particular situations in which the team needs to solve
problems or face difficulty [38].
Research on team work engagement benefits from a sound theoretical framework (i.e., the job
demands–resources model of work engagement, JDR), a precise concept, and well-established
instruments. Research linking team work engagement and collective performance argues that a
balance between team resources and challenging demands promotes energized team members, who
consider their task meaningful and show active, productive, and helpful behaviors. Research interest in
the engagement literature emphasizes the identification of team resources as antecedents of well-being
(transformational leadership, resiliency, collective efficacy).
The reviewed studies o↵er empirical evidence of the relevance of multiple antecedents of well-being,
and moderators of the HP collective relationship. Regarding antecedents, the role of leadership seems
especially relevant, in particular transformational and charismatic leadership behaviors have shown a
significant e↵ect on a work unit’s collective well-being and behavior [12,45,57]. Other antecedents
include organizational practices (HPWS or climate), work attributes (team task characteristics), and team
resources of multiple kinds. Several moderators stand out as particularly important in the literature
reviewed on HPWU such as sharedness (or strength of well-being), sector, team size, team tenure,
and third variables such as group identification, team trust, negative a↵ect, and shared job crafting.
Further research is needed to clarify and compare the roles of antecedents, mediators and moderators
of the HPWU relationship in order to guide interventions and investments [14].
4.1.3. Research Question 3—What Is the Evidence for Causal or Reciprocal Relationships between
Collective Well-Being and Collective Performance?
The predominant view in previous research and across the 30 HPWU studies identified in our
review is that collective well-being is an antecedent of collective performance. The happy–productive
relationship obtains generalized empirical support as a positive and significant relationship both
in previous meta-analyses and in our findings. Previous meta-analyses have provided moderate
corrected correlations between work-unit satisfaction and performance (r = 0.34) [12], group a↵ect and
group task performance (r = 0.33) [11] and business-unit engagement and performance (r = 0.42) [55].
In our systematic review, we found 76.2% of the correlations reported were positive and significant
across di↵erent constructs of collective well-being and performance. Existing evidence so far shows a
moderate relationship, does not allow concluding causal direction, and is a↵ected by mediating and
moderating third variables. However, these results heavily rely on correlational and cross-sectional
studies, and thus the causal direction between di↵erent types of well-being and di↵erent types of
performance remains an open question.
Two meta-analyses on longitudinal relationships between well-being and performance are available
at the individual [94] and organizational [95] levels of analyses, with none available at the work-unit
Int. J. Environ. Res. Public Health 2020, 17, 69
23 of 39
level due to the dearth of longitudinal studies [12]. Overall, their results show weaker or non-significant
correlations between collective well-being and time-lagged measurements of performance compared
to cross-sectional measurements. Shorter time-lags (less than 6 months) yielded stronger relationships
between job satisfaction and performance at an individual level meta-analysis [94]. Careful selection
of time-lags between measurements of collective satisfaction and performance may shed light as
to whether the e↵ects of collective well-being vary short-term vs. long-term. Another time-related
question is whether some collective well-being constructs have longer impact on performance than
others. For instance, it has been suggested that engagement is associated with the development of
resources and the pursuit of long-term goals [98].
Furthermore, stronger correlations in the direction of well-being to performance than the reverse
were found at the individual level [94], and mixed evidence on the direction HP or PH at the
organizational level depending on the specific measure of satisfaction used [95]. Only five studies
analyzed time-lagged HP relationships, and only two reported correlations in the reverse direction (PH).
The limited but very interesting findings of these five studies showed that collective well-being would
lead to relevant discretionary team behaviors (OCB and creativity), which in turn increased objective
productivity. Overall, the question remains open as to whether well-being leads to performance
or the reverse is true until more research with time-lagged or longitudinal designs is conducted.
Future research should undertake panel studies at the work-unit level with improved methodological
quality to be able to shed light on issues of causality or reciprocity between collective well-being and
collective performance.
4.2. Implications for Practice
The findings from this systematic review suggest several implications for practice on how to
increase collective well-being, and how to enhance transformation of collective well-being into collective
performance. Based on the empirical evidence reviewed, strategies to improve collective well-being
should focus on relevant antecedents such as implementing HPWS, encouraging transformational and
charismatic leadership, allowing for collaborative job crafting, improving team work design, promoting
organizational support climate, and providing team resources. Building on the mediating mechanisms
identified, it is also recommended to train team leaders and members on team work processes (e.g.,
team reflexivity, team helping behavior, OCB) and on how to maintain positive interactions (e.g.,
building on others’ ideas, morale-building communication). Finally, attending to (instead of ignoring)
important moderators such as negative a↵ect or task conflict help teams to focus e↵orts on relevant
team problems and avoid defective team decision-making.
4.3. Recommendations for Future Research
4.3.1. Antagonistic Patterns of HPWU
The relationship between well-being and performance is more complex than the HPWT proposes
and needs to be re-defined [9]. Beyond happy-productive workers or teams (synergistic pattern),
alternative and antagonistic patterns of happy–unproductive or unhappy–productive teams should
be considered. For instance, Peiró et al. [9] found that over 50% of the respondents were classified
in antagonistic patterns in a sample of Spanish workers. Furthermore, they found that the same
employee belonged to di↵erent patterns of well-being and performance in di↵erent operationalizations
of well-being (hedonic vs. eudaimonic) and performance (self-rated vs. supervisor rated), e.g., the same
employee could be hedonically happy, eudaimonically unhappy, and receive high or low performance
ratings depending on the source of evaluation. At the team level, HPWU research emphasizes the
positive influence of well-being on valuable performance outcomes such as task performance [11,12],
team creativity [38,79,83], and customer satisfaction [33,70]. However, evidence exists also on the
negative consequences of being a happy team (defective decision-making, group-think, social loafing).
Thus, applying an expanded HPWT model with synergistic and antagonistic patterns to the study of
Int. J. Environ. Res. Public Health 2020, 17, 69
24 of 39
teams and work-units would be a fruitful avenue for future research. Researchers might, for example,
investigate the conditions under which a team transitions from one happy–productive pattern to
another pattern over time; explore team composition to understand how individual members’ HP
patterns contribute to a team’s general HP pattern; study which top-down (e.g., leadership) or
bottom-up factors (e.g., team processes) enhance team’s happiness and productivity. To address these
questions, we believe both qualitative and quantitative research is strongly needed to uncover the
dynamic relationship between collective well-being and performance.
Relationship between hedonic and eudaimonic well-being. A relevant question for future research
is the relationship between hedonic well-being and eudaimonic well-being. In other words, can team
members be hedonically satisfied and not feel engaged? Can team members feel engaged while
experimenting negative a↵ect or dissatisfaction? The likely answer is “yes” they can, but additional
questions arise. How long can a team stay in a situation in which eudaimonic well-being is present but
hedonic well-being is absent? How do they move or which dispositional or situational factors help the
team stay in one state or change from one well-being form to another? This issue is related to team
dynamics and transitions over time.
4.3.2. Gain Spirals
There is too limited longitudinal evidence to draw conclusions about the causal ordering of team
happiness and productivity. Most likely collective well-being and collective performance maintain
a reciprocal and dynamic relationship as teams and team-members move through a↵ective states
and performance episodes. Previous research has found empirical support for gain spirals between
resources and work engagement [99], and between work engagement and performance indicators like
financial returns [100]. A gain spiral is a cycle of positive, mutual reinforcement relationship among
constructs and an increase in their levels over time. We believe this theme could be expanded to the
study of the HPWU relationship to investigate whether reciprocal relationships between collective
well-being and performance may lead to positive cycles and upward spirals, or to negative cycles and
downward spirals. Moreover, researchers might identify key third variables with an impact on these
spirals such as collective efficacy or conflict management.
4.3.3. Situational and Personal Features
There may be other factors, beyond the work environment, that could a↵ect work performance
and well-being. For example, employee impaired health can be critical for organizations, because
workers with worse health often lose more work hours, ask for more sick leave, and are resultantly
less productive than healthy workers [101]. Recent studies on the HPWT suggest to identify
situational and personal features that are associated with adscription to di↵erent happy-productive
clusters [9,14]. Current research has considered situational features related to job characteristics such
as task demands [69] or supervisor behavior [45,102]. Future research should consider other situational
features (e.g., time pressure, availability of feedback) as well as personal and social factors related to team
members. For instance, factors such as individual health status and chronic diseases [103], age [104],
gender [9], educational qualification [105], occupational category [9], and cultural background [106]
have shown to have an influence on well-being and/or performance. Further research on the e↵ect of
these third variables on patterns of well-being and performance would enrich the knowledge about
happy-productive teams.
4.3.4. Multi-Level Methodology
The use of a multilevel methodology would be highly recommended to explore cross-level
relationships among organizational, unit-level, and individual constructs. For instance, Tims et al. [62]
found support for team work engagement to influence individual work engagement and individual
performance. Mäkikangas et al. [88] found support for shared job crafting as a cross-level moderator
so that in teams with high levels of shared job crafting engaged individuals perceived better team
Int. J. Environ. Res. Public Health 2020, 17, 69
25 of 39
performance. In a longitudinal study on the role of workforce engagement to predict organizational
financial and customer satisfaction, Schneider et al. [54] found that organizational practices (e.g., senior
leadership communication of company’s goals) were surprisingly the strongest correlate of workforce
engagement compared to supervisory support and work attributes. Further research could explore
how organizational level variables influence and promote work-unit well-being and performance
(e.g., HPWS).
4.3.5. Methodological Issues
Some recommendations on methodological issues can be drawn from previous research [94,95].
Recommendations would include using consistent, valid, and multiple measures of well-being and
performance; careful selection of administration procedures and time lags between measurements;
control for sectors, countries, and industry e↵ects; and consider aggregation issues beyond the unit’s
average. Furthermore, another point of interest would be to widen the size and diversity of samples.
Whitman [12] suggests to increase the number of teams over 400 units, but it is also important to
research teams and workgroups in di↵erent conditions such as virtual or disperse teams, teams with
short vs. long term belonging members, teams with frequent membership changes or with multiple
supervisors. Investigating how well-being develops among these teams (e.g., virtual teams, or with
frequent membership changes) and how this relates to team performance would be an interesting
avenue for future research.
4.4. Limitations
There are important limitations to consider within the literature identified through the systematic
review. First, there is a dearth of research on eudaimonic constructs beyond team engagement,
and theoretically relevant perspectives such as Kahn’s conceptualization are not developed at the
team/work-unit level. Second, collective performance relies on single measurements, one-faceted, and
mainly on subjective evaluations of team performance rather than objective measurements. Third,
most studies rely on cross-sectional designs to test proposed causal models.
At review level, there are some limiting factors worth mentioning. The focus of our review
was on happy–productive teams and work-units. Therefore, we adopted a positive perspective
and excluded concepts that indicate ill-being or lack of well-being such as dissatisfaction, burnout
or negative a↵ect just to name a few. Obviously, teams and work-units go through bad times
and the management of dissatisfaction, conflict, and frustration may be more important than the
management of well-being. Previous research has studied how dissatisfaction or negative a↵ect
influences group performance, and found promising results on how negative well-being can lead to
improved performance under certain conditions [11]. However, studying unhappy teams was out of
the scope of our review. We also excluded team outcomes not directly related to productivity such
as absenteeism or turnover. As Schneider et al. [95] pointed out, it may be that satisfaction shows
stronger relations with other outcomes rather than financial productivity. We have focused on refereed
studies to ensure a certain level of quality in the empirical evidence reviewed. This may have left out
interesting unpublished research and to a certain extent bias our review with shortcomings associated
with published research (i.e., over-representation of significant results and lack of replication studies).
In this line, publication of studies with non-significant results and replication studies would make
it possible to accumulate enough and better evidence to progress knowledge and understanding on
HPWU. Besides, the scarce number of studies that focus on the relationship between well-being and
performance at the collective level of analysis coupled with the heterogeneity among these studies
impede carrying out a meta-analysis that would have helped to further integrate the results. Once we
dispose of enough accumulated studies on this relationship, we suggest future research to perform a
meta-analytic study on this topic in order to add valuable information, in particular about causality.
Int. J. Environ. Res. Public Health 2020, 17, 69
26 of 39
5. Conclusion
Despite all its limitations, literature on collective well-being has contributed to understanding
the relevant role of a↵ective processes happening in teams and work groups, which have largely
been ignored compared to cognitive processes. Theoretical frameworks underpinning the collective
well-being–performance relationship are mainly the happy-productive worker thesis and general
attitude-behavior link for collective satisfaction; the broaden-and-build theory and input-as-mood
theory for group a↵ect; and the job-demands-resources model and broaden-and-build theory for team
engagement. The positive e↵ects of collective well-being (or a↵ective climates) on team performance,
team creativity, customer satisfaction, and financial performance have been empirically tested and
found throughout the studies included in this systematic review. Across a diversity of samples,
organizational sectors, countries, conceptualizations, and operationalizations of well-being and
performance, collective well-being is positively correlated to collective performance at the meso-level of
analysis (team, group, work-unit). In particular, the satisfaction and group a↵ect literatures have shed
light on mediating team processes that explain the link between collective well-being and performance.
Additionally, literature found on the three collective well-being constructs o↵ers very interesting inputs
on antecedents (e.g., transformational leadership, resources, task characteristics), and moderators of
the HPWT (e.g., strength of well-being, group identity, negative group a↵ect, organizational support)
at the unit-level.
Supplementary Materials: The following are available online at http://www.mdpi.com/1660-4601/17/1/69/s1.
Author Contributions: Conceptualization, J.M.P., M.E.G.-B., and M.W.K.; Methodology, M.E.G.-B., J.M.P., and
M.W.K.; Data gathering and databases, M.E.G.-B., M.I.M.-J., S.O.-B., and M.W.K.; Data analysis, M.E.G.-B.,
M.I.M.-J., and S.O.-B.; Writing—original draft preparation, M.E.G.-B., and J.M.P.; Writing—review and editing,
M.E.G.-B., J.M.P., M.I.M.-J., S.O.-B., and M.W.K.; Funding acquisition, J.M.P. All authors have read and agreed to
the published version of the manuscript.
Funding:
The present study was funded by the MINECO/FEDER Research agencies:
PSI2015-64862-R(MINECO/FEDER).
Conflicts of Interest: The authors declare no conflict of interest.
project
Int. J. Environ. Res. Public Health 2020, 17, 69
Study Goal
Theories
Appendix A
Source
HP a
HP
HP
PH
HP
JS Definition b
Team
satisfaction
(3- items;
Barsade et
al., 2000)
JS
Measure
n/a
n/a
Team
member
overall
satisfaction
(2-items;
Cohen,
1996)
Employee
satisfaction
(4-items;
Foodservice
Research
Forum,
1997)
Team satisfaction is
an attitudinal
construct that reflects
a team’s shared
attitude toward team
tasks and their
associated
environments
(Mason & Griffin,
2005)
Team
members;
Individual
Employees;
Individual
Team
members;
Individual
Global/Facets JS Informant
c
JS Referent
G
G
G
Rf
0.46 **
Design e
0.29 **
P Measure d
Performance scale (4-items;
Edmonson, 1999).
Employees. Subjective
0.27 *
Objective performance
(first-year commission,
first-year premium, total
commissions, team goal
achievement). Supervisors.
Objective
JS(T1)-OCB(T1) = 0.47 **;
JS(T1)-OCB(T2) = 0.19ns;
JS(T2)-OCB(T2) = 0.61 **
C
OCB (5-items; Organ, 1988).
Leader. Subjective
OCB (5-items; Organ, 1988).
Leader. Subjective
Profit sales (company
records). Leader. Objective
Profit year (company
records). Leader. Objective
PY(T1)-JS(T2) = -0.05ns
CS(T1)-JS(T2) = 0.36 *
OCB(T1)-JS(T2) = 0.32 *
JS(T1)-PS(T1) = 0.37 *;
JS(T1)-PS(T2) = 0.35 *;
JS(T2)-PS(T2) = 0.43 **
JS(T1)-PY(T1) = 0.10ns;
JS(T1)-PY(T2) = 0.27;
JS(T2)-PY(T2) = 0.22ns
JS(T1)-CS(T1) = 0.49 **;
JS(T1)-CS(T2) = 0.61 **;
JS(T2)-CS(T2) = 0.09ns
Customer satisfaction
(4-items; n/a). Customers.
Subjective
PS(T1)-JS(T2) = 0.15ns
Customer satisfaction
(4-items; n/a). Customers.
Subjective
Profit year (company
records). Leader. Objective
0.32 **
0.52 **
Profit sales (company
records). Leader. Objective
Overall team performance
(5-items; Rosenstein, 1994).
Team members. Subjective
Overall team performance
(5-items; Rosenstein, 1994).
Managers. Subjective
C
CL (1
year)
Performance scale (4-items;
Edmonson, 1999).
Supervisors. Subjective
Table A1. Description of the studies on Collective Satisfaction – Collective Performance.
1. Chi, Chung,
& Tsai (2011)
[45]
Input-process-output
model of teams
(Hackman, 1987).
Social Exchange
Theory (Blau, 1964;
refering to OCB)
Attitude- cooperation
collaboration- unit
productivity (Ryan et
al., 1996); climate for
service (Schneider et
al., 2005); service
profit chain (Heskett
et al, 1997); social
exchange theory
(Blau, 1964; refering
to OCB)
Input-process-output
model of teams
(Hackman, 1987);
Emotional contagion
(Hatfield et al., 1994);
Broaden-and-build
theory (Fredrickson,
1998)
Examine whether
positive employee
attitutes and
behaviours influence
business outcomes or
whether positive
business outcomes
influence positive
employee attitudes
and behaviors
Examine two
mediating
mechanisms that
explain the leader
positive moods–team
performance linkage:
transformational
leadership, and
positive group
a↵ective tone
2. Koys (2001)
[33]
3. Li, Li, &
Wang (2009)
[69]
Explore the
relationships among
traditional task
characteristics, team
performance and
team member
satisfaction
Sample
27 of 39
Team
Size
28 (T1); 25
(T2)
7.34
28
restaurant
units. n/a
3.82
85 sales
teams.
Taiwan
92 teams.
n/a
Study Goal
Social exchange
theory (Blau, 1964)
HP a
HP
Emotional contagion
(Hatfield et al., 1994).
Atraction-selection-attrition HP
e↵ects. Social
information
Theories
Int. J. Environ. Res. Public Health 2020, 17, 69
Source
4. Mason &
Griffin (2005)
[35]
Test the validity and
utility of group task
satisfaction and
investigate whether
group task
satisfaction would
explain incremental
variance in
organizational
citizenship behaviors,
group performance,
and absenteeism
norms, after the
variance explained
by aggregated
individual job
satisfaction and
group a↵ective tone
was taken into
account
5.
Explore potential
Messersmith,
individual attitudinal
Patel, Lepak,
and behavioral
&
mediators
Gould-Williams aggregated at the
(2011) [36]
unit level that
operate in the black
box between HR
systems and
departmental
performance
JS
Measure
G
F
Department
members;
Individual
Group
members;
Individual
Group
members;
Team
Global/Facets JS Informant
c
JS Referent
Table A1. Cont.
JS Definition b
Group
task
satisfaction
(10-items;
Mason &
Griffin,
2005)
Individual
job
satisfaction
(MSQ;
20-items;
Weiss et
al., 1967)
The group’s shared
attittude towards its
task and the
associated work
environment (Mason
& Griffin, 2002)
n/a
Satisfaction
(3-items;
Bowling &
Hammond,
2008;
Spector et
al., 1999;
Vancouver
& Schmitt,
1991)
Design e
Rf
0.20ns (civic helping)
0.21ns (sportmanship)
P Measure d
0.19ns
0.32 * (civic helping) 0.43
** (sportmanship)
OCB (civic helping,
sportsmanship; Podsako↵ et
al., 1997). Supervisors.
Subjective
0.35 ** (civic helping)
0.32 * (sportmanship)
C
Group performance (quality,
customer service,
productivity; n/a).
Supervisors. Subjective
0.22ns (civic helping)
0.21ns (sportmanship)
OCB (civic helping,
sportsmanship; Podsako↵ et
al., 1997). Group members.
Subjective
OCB (civic helping,
sportsmanship; Podsako↵ et
al., 1997). Group members.
Subjective
0.31 *
0.21 *
0.36 *
OCB (civic helping,
sportsmanship; Podsako↵ et
al., 1997). Supervisors.
Subjective
CL (1
year)
Group performance (quality,
customer service,
productivity; n/a).
Supervisors. Subjective
Departamental performance
(% success). Managers.
Objective
OCB(8-items; Smith et al.,
1983). Employees. Subjective
Team
Size
28 of 39
Sample
9.32
148
55 work
groups
variety of
industries.
Australia
92
departments
local
government
authorities.
Wales
(United
Kingdom)
Study Goal
Theories
HP
HP a
Satisfaction-behavior-productivity
(Kopelman, Ostro↵);
HP
climate-attitudes-performance
(Schneider et al.,
2005); service profit
chain (Heskett et al,
1997)
Linkage research
(Schneider et al,
2005). Service-profit
chain (Heskett et al,
1997)
Int. J. Environ. Res. Public Health 2020, 17, 69
Source
6.
Examine the role that
Namasivayam, psychological
Guchait, &
empowement and
Lei (2014) [70] employee satisfaction
play in the
relationship between
leader empowering
behaviors and
customer satisfaction
and employees’
organizational
commitment
7. Van de
Voorde, Van
Veldhoven, &
Paauwe
(2014) [37]
Test the mediating
role of work
satisfaction in the
relationship between
work unit climate
and labour
productivity
Employees;
Individual
Frontline
employees;
Individual
Global/Facets JS Informant
JS Referent
G
G
c
Table A1. Cont.
Satisfaction
(2-items;
Hirschfield,
2000)
JS
Measure
n/a
Job
satisfaction
(10-items;
Bakker et
al., 2010)
JS Definition b
Group task
satisfaction as the
group’s shared
attitude towards its
task and the
associated work
environment (Mason
& Griffin, 2002)
P Measure d
Customer satisfaction
(6-items; n/a). Customers.
Subjective
Labour productivity
(profits-to-costs ratio).
Finance and control
department. Objective
C
0.57 *
Rf
JS(T1)-LP(T1) = 0.08ns
Design e
CL (1-4
years)
JS(T2)-LP(T2) = 0.17 *
JS(T1)-LP(T2) = 0.06ns
JS(T2)-LP(T1) = 0.02ns
Sample
40
restaurant
units.
Northeastern
US
29 of 39
n/a
Team
Size
171
financial
84.7 (T1);
services
86.9 (T2)
branches.
Netherlands
a HP = Happy-Productive; PH = Productive-Happy; b JS = Job Satisfaction; c G = Global; F = Facets; d P = Performance; e C = Cross-sectional design; CL = Cross-lagged design; f R =
correlation coefficient; ns = not significant; * = p < 0.05; ** = p < 0.01; *** = p < 0.001.
Study Goal
n/a
Theories
Int. J. Environ. Res. Public Health 2020, 17, 69
Source
1. Boerner &
Freiherr von
Streit (2007)
[50]
Investigate the degree
to which a conductor’s
transformational
leadership and
orchestral musicians’
positive group mood
have a beneficial e↵ect
on orchestral
performance
HP
HP
HP a
Group a↵ective tone
reflects team members’
a↵ective reactions
toward current team
conditions (George &
King, 2007)
Work group mood
(Bartel & Saavedra,
2000) or group
emotion (Barsade &
Gibson, 1998) is a
specific disposition
developed through
processes of cognitive
and emotional
self-regulation among
group members
GA Definition
(1) PANAS (n/a;
Watson et al., 1988) (2)
team members
evaluation the extent
to which each of a list
of adjectives described
their mood states at
team meetings during
the past week (e.g.,
Tsai et al., 2012)
Group mood (8-items;
Boerner & Freiherr
von Streit, 2007)
GA Measure b
Team
members;
Individual
Employees;
Group
Team performance
scale (5-items scale;
Edmondson, 1999).
Supervisors.
Subjective
Artistic quality
(Auvinen, 2001): (1)
the reaction of third
parties to the
orchestra’s
achievement (2)
Quality compared to
other orchestras of the
same quality). Two
members. Subjective
P Measure c
0.56 **
Re
Sample
12
Team Size
30 of 39
C
Design d
22 Symphony
orchestras.
Germany
6,1
4.42 (T2
and T3)
7,34
4.5
0.58 **
C
85 teams.
Insurance
firms. Taiwan
62 teams.
High-technology
firms. Taiwan
C
0.36 **
0.30
**(supervisor);
0.35
**(employees)
59
Team positive
mood(T2)-Team branches.Saving
performance(T3) banks. Spain
= 0.39 **
0.40 ***
Group performance
scale (2-items; Jehn et
al., 1999). Employees.
Subjective
C
Team e↵ectiveness
(1-item; n/a).
Supervisor. Subjective
Creative performance
scale and creativity
scale (6-items;
Oldham & Cummings,
1996; Zhou and
George, 2001).
Supervisor. Subjective
97 teams.
Di↵erent
organizations
(eg. service,
backing and
financial
service,
manufacturing,
and other).
Korea
Team positive
mood(T2)-Team
e↵ectiveness-(T3)
= 0.21ns
CL (1 year)
First-year commission,
first-year premium,
and total commissions
earned by the team.
Supervisor. Objective
Employees;
Individual
HP
Team member;
Individual
Employees;
Individual
Performance scale
(4-items; Edmonson,
1999). Supervisor and
employees. Subjective
PANAS (4-items;
Watson et al., 1988). At
work
A↵ective well-being
scale (6-items; Segura
& González-Romá,
2003). Over the last
weeks
PANAS (10-items;
Watson et al., 1988).
Past two weeks. Team
meeting
HP
HP
Group a↵ective tone is
defined as consistent
or homogeneous
a↵ective reactions
within a group
(George, 1990)
Positive team a↵ect
refers to the positive
moods shared by team
members (Gamero,
González-Romá, &
Peiró, 2008)
Positive group
a↵ective tone is
defined as the
homogeneous positive
a↵ective states within
the group (George,
1990)
GA Informant
GA Referent
Table A2. Description of the studies on Group A↵ect – Collective Performance.
Three-stage model
of transformational
leadership (Conger
& Kanungo, 1998)
Input-process-output
model of teams
(Hackman, 1987);
Emotional contagion
(Hatfield et al., 1994);
Broaden-and-build
theory (Fredrickson,
1998)
2. Chi &
Huang (2014)
[84]
3. Chi, Chung
& Tsai (2011)
[45]
Examine how
transformational
leadership, and
positive group
a↵ective tone mediate
the relationship
between leader
positive moods and
team performance
Motivational control
theory (Hyland,
1988; Klein, 1989)
Explore the
mechanisms that
explain the
relationship between
transformational
leadership and team
performance
4.
González-Romá
& Gamero
(2012) [39]
Social cognitive
theory (Bandura,
1986); Group
creativity process
model (Dzindolet,
2008);
Broaden-and-build
theory (Fredrickson,
1998)
Test whether the
relationship between a
team climate of
support from the
organization and team
performance is
mediated by positive
team mood
5. Kim & Shin
(2015) [80]
Examine cooperative
group norms and
group positive a↵ect
as antecedents of team
creativity and explore
collective efficacy as
an intermediary
mechanism between
these relationships
Source
Study Goal
Mood-as-input
model (Martin et al.,
1993)
Theories
HP
HP a
Int. J. Environ. Res. Public Health 2020, 17, 69
6. Kim, Choi &
Lee (2016) [82]
Examine the
moderating role of
group a↵ective climate
and group reflexivity
in the relationship
between trait a↵ect
and creativity
HP
HP
HP
7. Meneghel,
Salanova &
Martínez
(2016) [77]
Emotional contagion
(Hatfield et al., 1994);
Mood-as-information
theory (Forgas &
Vargas, 2000);
Broaden-and-build
theory (Fredrickson,
2001)
Broaden-and-build
theory of positive
emotions
(Fredrickson, 1998)
Broaden-and-build
theory of positive
emotions
(Fredrickson, 1998,
2001)
Examine the
mediating role of
group social resources
between group
positive a↵ect and
group performance
Examine the
relationship between
collective positive
emotions at work and
team resilience
8. Peñalver,
Salanova,
Martínez &
Schaufeli
(2017) [81]
9. Rego, Júnior,
Pina,
Stallbaum &
Neves (2016)
[38]
Examine whether (1)
store positive a↵ective
tone predicts store
performance through
creativity, and (2) store
negative a↵ective tone
enhances the
relationship between
positive a↵ective tone
and creativity
n/a
n/a
GA Definition
The a↵ective
composition of the
group members
(Barsade & Gibsonm
1998), resulting from
feeling similar levels
of individual emotions
when people work
together (Barsade,
Knight, 2015)
Group (store’s)
a↵ective tone is
defined as consistent
or homogeneous
a↵ective reactions
within a group
(George, 1990)
Table A2. Cont.
GA Measure b
Positive and negative
a↵ective climate
(Haslam, 1995). In
general. At work
Five collective
emotions: enthusiasm,
optimism, satisfaction,
comfort, and
relaxation. Faces Scale
(Kunin 1955). Last
year
Group positive a↵ect
(4-items; Salanova,
Llorens, Cifre, &
Martínez, 2012). Past
year. At work
Positive a↵ective tone
(3-items; Turban et al.,
2009). 6 months
Employees;
Group
Employee creativity
scale (6-items; Zhou &
George, 2001).
Supervisor. Subjective
P Measure c
GA Informant
GA Referent
Employees;
Team
0.47 *
Re
Sample
n/a
Team Size
31 of 39
C
Design d
50 teams. Two
organizations.
Korea
12,5
5,14
0.15 *
C
0.46 ***
94 stores’
supervisors.
Retail
organization
(appliances
sector). Brazil
417 teams.
Di↵erent
companies.
Spain
216 teams.
4,99
Commercially
oriented
service
organizations
(shops, bars,
restaurants and
physiotherapists’offices).
Spain
0.20 *
0.13 **
C
C
CL
0.14 **
Store creativity
(13-items; Zhou &
George, 2001).
Supervisor. Subjective
Team performance
scale: Extra-role
(3-items; adaptation of
the scale of Goodman
& Svyantek, 1999).
Supervisor. Subjective
Team performance
scale: In-role (3-items;
adaptation of the scale
of Goodman &
Svyantek, 1999).
Supervisor. Subjective
Team performance
scale: Extra-role (n/a;
adaptation from
Godman and
Svyantek (1999).
Supervisor. Subjective
Team performance
scale: In-role (n/a;
adaptation from
Godman and
Svyantek (1999).
Supervisor. Subjective
Employees:
Individual
Supervisors;
Team
Sales achievement.
Top management.
Objective
performance in
the semestre
(0.25 **);
performance
subsequent
semester
(0.07ns)
Int. J. Environ. Res. Public Health 2020, 17, 69
Study Goal
A↵ective-consistency
perspective (Yu,
2009);
Broaden-and-build
theory (Fredrickson,
1998)
Theories
HP
HP a
Source
10. Seong &
Choi (2014)
[78]
Examine the
relationship between
positive a↵ect of
leaders and members
with group-level fit
perceptions and
subsequent group
processes and
performance
Table A2. Cont.
Delighted; pleased;
happy; comfortable;
satisfied; relaxed
(6-items; Posner,
Russell, & Peterson,
2005). In general. At
work
GA Measure b
n/a
PANAS (4-items;
Watson et al., 1988).
One week frame
GA Definition
Group a↵ective tone is
defined as consistent
or homogeneous
a↵ective reactions
within a group
(George, 1990)
Group a↵ective tone is
defined as consistent
or homogeneous
a↵ective reactions
within a group
(George, 1990)
PANAS (10-items;
Watson et al., 1988).
Past week. At work
PANAS (10-items;
Watson et al., 1988).
Past week. Team
meetings
Group a↵ective states
refers to the shared
emotions or shared
moods (George, 2002)
HP
n/a
Positive a↵ect scale
(6-items; Larsen &
Diener, 1992). Felt at
very particular
moment
HP
HP
HP
11. Shin (2014)
[79]
Group creativity
model (Paulus &
Dzindolet, 2008);
Broaden-and-build
theory (Fredrickson,
1998, 2001)
Examine whether
positive group
a↵ective tone is
positively associated
with team
e↵ectiveness and if
this e↵ect is stronger
for higher levels of
group identification
Explore group-level
mechanisms linking
positive group
a↵ective tone and
team creativity
12. Tanghe,
Wisse & Van
der Flier (2010)
[46]
Explore boundary
conditions of the
relationship between
positive group
a↵ective tone and
team creativity
Group-centrism
perspective
(Kruglanski et al.,
2006); ’Dual-tuning’
perspective
(Kruglanski, Pierro,
Mannetti, & De
Grada, 2006)
Broaden-and-build
theory (Fredrickson,
1998); Social identity
perspective (Turner,
1985); Circumplex
model of a↵ect
(Larsen & Diener,
1992)
13. Tsai, Chi,
Grandey &
Fung (2012)
[85]
Mood-as-input
model (Martin &
Stoner, 1996)
14. Tu (2007)
[83]
Examine how
contextual factors
moderate the
relationship between
team a↵ective tone
and team creativity
P Measure c
C
Design d
0.02ns
Re
GA Informant
GA Referent
Sample
96 teams.
Defense
industry.
Korea
Team
members;
Team
0.40 ***
Team performance
scale (4- items;
adaptation of the scale
of Zellmer-Bruhn &
Gibson, 2006).
Supervisors.
Subjective
C
98 teams.
Di↵erent
companies
(banking and
finance,
service, and
manufacturing).
Korea
32 of 39
10,35
Team Size
5,8
0.09 ns
68 teams.
High-technology
firms. Taiwan
5,71
5,9
2-4
0.34 *
106 teams.
Di↵erent
industries
(computer;
semi-conductors;
audio and
video
electronic).
Taiwan
0.19ns
0.40 **
Team
members;
Individual
C
C
C
71 teams.
Service
organizations.
n/a
Creativity scale
(5-items; Zhou &
George, 2001)
Supervisors.
Subjective
Employees;
Individual
Willingness to engage
in OCB (5-items;
Moorman and Blakely,
1995) Employees.
Subjective
Employees;
Individual
Team creativity scale
(3-items; Van der Vegt
& Janssen, 2003).
Supervisors.
Subjective
Perceived team
performance (4-items;
n/a). Employees.
Subjective
Employees;
Individual
Team creativity.
Adaptation of team
creativity scales (Scott
& Bruce, 1994; Zhou &
George, 2001).
Employees and
supervisors.
Subjective
a HP = Happy-Productive; PH = Productive-Happy; b GA = Group A↵ect; PANAS = Positive A↵ect and Negative A↵ect Schedule; c P = Performance; d C = Cross-sectional design;
TL = Time-lagged design; e R = correlation coefficient; ns = not significant; * = p < 0.05; ** = p < 0.01; *** = p < 0.001.
Source
Study Goal
Job
demands-resources
model (Demerouti &
Bakker, 2011);
Broaden-and-build
theory (Fredrickson,
1998)
Theories
Int. J. Environ. Res. Public Health 2020, 17, 69
1. Costa,
Passos, &
Bakker (2015)
[87]
Understand whether the
two types of conflict impact
di↵erently on proximal
(team work engagement)
and distal (team
performance) team
outcomes, directly;
simultaneously, to explore
the moderator influence of
team conflict on the job
demands-resources model
Healthy and resilient
organizations model
(Salanova, 2008)
HP
HP a
EG Definition
EG Measure b
EG Informant
EG Referent
P Measure c
Number of
publications, oral
presentations in
congresses; leader;
objective
Team
members;
Team
In-role; 3-items;
employees; subjective
Extra-role; 3-items;
employees; subjective
Employees;
Team
Team work
engagement
scale (9-items;
Costa et al.,
2014)
HP
UWES
(18-items;
Schaufeli et al.,
2002; Salanova
et al., 2003)
Service recovery
performance; 5-items;
leaders; subjective
HP
Service quality:
functional and
relational (22-items;
customers; subjective)
Employees;
Team
Perceived team
performance; 5-items;
employees; subjective
Employees;
Individual
UWES
(3-items; Tims
et al., 2013)
Employees;
Team
UWES-9
spanish
version
(9-items;
Schaufeli,
Bakker, &
Salanova,
2006)
HP
Work engagement is a
positive, fulfilling,
work-related and shared
psychological state of mind
(Salanova et al., 2003)
Team Work
Engagement
Scale (4-items;
Costa et al.,
2014)
Satisfaction and
loyalty (6-items;
customers; subjective)
HP
Work engagement is a
positive, fulfilling, and rather
consistent state of mind
characterized by vigour,
dedication, and absorption
(Schaufeli et al., 2002).
Work engagement is defined
as a positive, fulfilling,
work-related state of mind
that is characterized by
vigour, dedication, and
absorption (Schaufeli et al.,
2002)
Team engagement is defined
as ’a positive, fulfilling,
work-related and shared
psychological state
characterized by team work
vigor, dedication and
absorption which emerges
from the interaction and
shared experiences of the
members of a work team’
(Torrente, Salanova, Llorens,
& Schaufeli, 2012)
Team work engagement is
defined as a shared, positive
and fulfilling, motivational
emergent state of
work-related well-being
(Costa et al., 2014)
Table A3. Description of the studies on Team engagement – Collective Performance.
2. Cruz-Ortiz,
Salanova, &
Martínez
(2013) [57]
Job
demands-resources
model of work
engagement (Bakker &
Demerouti, 2007)
Attitude theory
(Bagozzi, 1992)
Job
demands-resources
model of work
engagement (Bakker &
Demerouti, 2008)
Test the relationship
between transformational
leadership, team work
engagement and team
performance
Investigate the relationship
between collective job
crafting and team service
recovery performance via
the mediation mechanism
of team work engagement
Examine the moderating
role of team climate for
innovation on the
relationship between team
engagement and service
performance
4. Luu (2017)
[92]
Examine if individual and
team work engagement are
associated with team
members’ perceived team
performance
3.
García-Buades,
Martínez-Tur,
Ortiz-Bonnín,
& Peiró (2016)
[90]
5. Makikangas,
Aunola,
Seppala, &
Hakanen
(2016) [88]
0.24 *
Re
Sample
3.41
Team Size
33 of 39
C
Design d
82 research
teams.
Southern
European
country
7.23
4
8.94
0.37 **
C
0.38 **
0.18ns; 0.26
*
0.39 ***
181
clinicians
teams.
Vietnam
10.53
0.07ns;
0.09ns
0.30 **
86
reception
and
restaurant
teams.
Spanish
mediterranean
coast
58 teams
di↵erent
SMEs.
Spain
C
C
C
102
teachers
and
administrative
teams.
Finnish
Source
Examine the antecedents
and outcomes of team-level
collaborative crafting
Study Goal
Theories
Int. J. Environ. Res. Public Health 2020, 17, 69
6. McClelland,
Leach, Clegg,
& McGowan
(2014) [93]
Hypothesize that team job
crafting relates positively to
team performance through
team work engagement
Job
demands-resources
model (Demerouti et
al., 2001)
Job
demands-resources
model (Bakker &
Demerouti, 2007);
Broaden-and-build
theory (Fredrickson,
1998)
Job
demands-resources
model of work
engagement (Bakker &
Demerouti, 2008)
Analyze the mediating role
of team work engagement
between team social
resources, and team
performance
Examine the mediating role
of service climate in the
prediction of employee
performance and customer
loyalty
Role adjustments lead
to improve
performance through
changes in job content,
higher self-efficacy,
and higher motivation
(Clegg & Spencer,
2007)
7. Salanova,
Agut, & Peiró
(2005) [91]
8. Tims,
Bakker, Derks,
& Rhenen
(2013) [62]
9. Torrente,
Salanova,
Llorens, &
Schaufeli
(2012) [58]
HP a
EG Definition
UWES
(9-items;
Schaufeli et al.,
2006)
EG Measure b
Table A3. Cont.
HP
Work engagement is a job
holder’s a↵ective
psychological connection to
his/her work tasks (Schaufeli
& Bakker, 2004)
0.30 **
Re
Sample
34 of 39
11.1
C
Design d
Team Size
P Measure c
3
EG Informant
EG Referent
0.10ns
114
reception
and
restaurant
units. n/a
16.12
Employees;
Individual
0.54 **
54 health
services
teams
company.
Netherlands
n/a
0.25 *
Team achievements,
efficiency, work
quality, and mission
fulfilment; 4-items;
supervisors; subjective
C
C
C
0.12ns
62 teams
from 13
enterprises.
n/a
242
retaliers
and
insurance
provider
call centre
teams.
United
Kingdom
Work
Engagement
Scale
(Schaufeli et al.,
2002)
Employees;
Individual
HP
Engagement is a positive,
fulfilling, work-related state
of mind that is characterized
by vigor, dedication, and
absorption (Shaufeli et al.,
2002)
Empathy and
excellent job
performance; 6-items;
customers; subjective
HP
UWES
Employees;
Williams and
(9-items/3-items; Individual/team Anderson
Schaufeli et al.,
(1991).5-items;
2006)
employees;subjective
Extra-role; 3-items;
supervisors; subjective
In-role; 3-items;
supervisors; subjective
Work engagement is defined
as a positive, fulfilling,
work-related state of mind
that is characterized by vigor,
dedication, and absorption
(Schaufeli et al., 2002)
Employees;
Team
Team work
engagement
scale (9-items;
Torrente,
Salanova,
Llorens, &
Schaufeli,
2013)
HP
Work engagement is a
positive, fulfilling,
work-related and shared
psychological state
characterized by teams work
vigor, dedication and
absorption which emerges
from the interaction and
shared experiences of the
members of a work team
(Salanova et al., 2003)
a HP = Happy-Productive; PH = Productive-Happy; b EG = Engagement; UWES = Ultrecht Work Engagement Scale; c P = Performance; d C = Cross-sectional design; CL = Cross-lagged
design; e R = correlation coefficient; ns = not significant; * = p < 0.05; ** = p < 0.01; *** = p < 0.001; Sources 3, 8, & 10 r = mean correlation of vigour, dedication, and absorption.
Int. J. Environ. Res. Public Health 2020, 17, 69
35 of 39
References
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
Ia↵aldano, M.T.; Muchinsky, P.M. Job satisfaction and job performance: A meta-analysis. Psychol. Bull. 1985,
97, 251–273. [CrossRef]
Judge, T.A.; Thoresen, C.J.; Bono, J.E.; Patton, G.K. The job satisfaction-job performance relationship: A
qualitative and quantitative review. Psychol. Bull. 2001, 127, 376–407. [CrossRef] [PubMed]
Bowling, N.A.; Khazon, S.; Meyer, R.D.; Burrus, C.J. Situational strength as a moderator of the relationship
between job satisfaction and job performance: A meta-analytic examination. J. Bus. Psychol. 2015, 30, 89–104.
[CrossRef]
Harrison, D.A.; Newman, D.A.; Roth, P.L. How important are job attitudes? Meta-analytic comparisons of
integrative behavioral outcomes and time sequences. Acad. Manag. J. 2006, 49, 305–325. [CrossRef]
Barsade, S.G.; Knight, A.P. Group A↵ect. Annu. Rev. Organ. Psychol. Organ. Behav. 2015, 2, 21–46. [CrossRef]
Bailey, C.; Madden, A.; Alfes, K.; Fletcher, L. The meaning, antecedents and outcomes of employee
engagement: A narrative synthesis. Int. J. Manag. Rev. 2017, 19, 31–53. [CrossRef]
Christian, M.S.; Garza, A.S.; Slaughter, J.E. Work engagement: A quantitative review and test of its relations
with task and contextual performance. Pers. Psychol. 2011, 64, 89–136. [CrossRef]
Bowling, N.A. Is the job satisfaction-job performance relationship spurious? A meta-analytic examination.
J. Vocat. Behav. 2007, 71, 167–185. [CrossRef]
Peiró, J.M.; Kozusznik, M.W.; Rodríguez Molina, I.; Tordera, N. The happy-productive worker model and
beyond: Patterns of wellbeing and performance atwork. Int. J. Environ. Res. Public Health 2019, 16, 479.
[CrossRef]
Eurofound. Sixth European Working Conditions Survey—Overview Report (2017 Update); Publications Office of
the European Union: Luxemburgo, 2017.
Knight, A.P.; Eisenkraft, N. Positive is usually good, negative is not always bad: The e↵ects of group a↵ect
on social integration and task performance. J. Appl. Psychol. 2015, 100, 1214–1227. [CrossRef]
Whitman, D.S.; Van Rooy, D.L.; Viswesvaran, C. Satisfaction, citizenship behaviors, and performance in
work units: A meta-analysis of collective construct relations. Pers. Psychol. 2010, 63, 41–81. [CrossRef]
Peiró, J.M.; Ayala, Y.; Tordera, N.; Lorente, L.; Rodríguez, I. Sustainable well-being at work: A review and
reformulation. Papeles del Psicólogo 2014, 35, 5–14.
Warr, P.; Nielsen, K. Wellbeing and work performance. In E-Handbook of Subjective Wellbeing; Diener, E.,
Oishi, S., Tay, L., Eds.; DEF Publishers: Salt Lake City, UT, USA, 2018; pp. 1–31.
Fisher, C.D. Happiness at work. Int. J. Manag. Rev. 2010, 12, 384–412. [CrossRef]
Ryan, R.M.; Deci, E.L. On happiness and human potentials: A review of research on hedonic and eudaimonic
well-being. Annu. Rev. Psychol. 2001, 52, 141–166. [CrossRef]
Sonnentag, S. Dynamics of well-being. Annu. Rev. Organ. Psychol. Organ. Behav. 2015, 2, 261–293. [CrossRef]
Porath, C.; Spreitzer, G.; Gibson, C.; Garnett, F.G. Thriving at work: Toward its measurement, construct
validation, and theoretical refinement. J. Organ. Behav. 2012, 33, 250–275. [CrossRef]
Paterson, T.A.; Luthans, F.; Jeung, W. Thriving at work: Impact of psychological capital and supervisor
support. J. Organ. Behav. 2014, 35, 434–446. [CrossRef]
Spreitzer, G.; Sutcli↵e, K.; Dutton, J.; Sonenshein, S.; Grant, A.M. A socially embedded model of thriving at
work. Organ. Sci. 2005, 16, 537–549. [CrossRef]
Hart, P.M.; Cotton, P.; Scollay, C.E. Flourishing at work: Improving wellbeing and engagement. In Flourishing
in Life, Work and Careers: Individual Wellbeing and Career Experiences; Burke, R.J., Page, K.M., Cooper, C.L.,
Eds.; Edward Elgar: Cheltenham, UK, 2015; pp. 281–313. ISBN 9781783474103.
Lorente, L.; Tordera, N.; Peiró, J.M. How work characteristics are related to European workers’ psychological
well-being. A comparison of two age groups. Int. J. Environ. Res. Public Health 2018, 15, 127. [CrossRef]
Ry↵, C.D.; Singer, B.H. Know thyself and become what you are: A eudaimonic approach to psychological
well-being. J. Happiness Stud. 2008, 9, 13–39. [CrossRef]
Ashkanasy, N.M.; Härtel, C.E.J. Positive and Negative A↵ective Climate and Culture; Schneider, B., Barbera, K.M.,
Eds.; Oxford University Press: Oxônia, UK, 2014; ISBN 9780199860715.
González-Romá, V.; Peiró, J.M.; Subirats, M.; Mañas, M.A. The Validity of A↵ective Work Team Climates.
In Innovative Theories, Tools, and Practices in Work and Organizational Psychology; Vartiainen, M., Avallone, F.,
Anderson, N., Eds.; Hogrefe & Huber Publishers: Cambridge, MA, USA, 2000; pp. 97–109.
Int. J. Environ. Res. Public Health 2020, 17, 69
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
36 of 39
Kozlowski, S.W.J.; Klein, K.J. A multilevel approach to theory and research in organizations: Contextual,
temporal, and emergent processes. In Multilevel Theory, Research, and Methods in Organizations: Foundations,
Extensions, and New Directions, 1st ed.; Jossey-Bass: San Francisco, CA, USA, 2000; pp. 3–90.
Cole, M.S.; Bedeian, A.G.; Hirschfeld, R.R.; Vogel, B. Dispersion-composition models in multilevel research.
Organ. Res. Methods 2011, 14, 718–734. [CrossRef]
Chan, D. Functional relations among constructs in the same content domain at di↵erent levels of analysis: A
typology of composition models. J. Appl. Psychol. 1998, 83, 234–246. [CrossRef]
Bliese, P.D. Within-group agreement, non-independence, and reliability: Implications for data aggregation
and analysis. In Multilevel Theory, Research, and Methods in Organizations: Foundations, Extensions, and New
Directions; Klein, K.J., Kozlowski, S.W.J., Eds.; Jossey-Bass: San Francisco, CA, USA, 2000; pp. 349–381.
LeBreton, J.; Senter, J. Answers to 20 questions about interrater reliability and interrater agreement. Organ. Res.
Methods 2007, 11, 815–852. [CrossRef]
Salas, E.; Sims, D.E.; Burke, C.S. Is there a “Big Five” in teamwork? Small Gr. Res. 2005, 36, 555–599.
[CrossRef]
Salas, E.; Reyes, D.L.; Woods, A.L. The Assessment of Team Performance: Observations and Needs.
In Innovative Assessment of Collaboration; Springer: Berlin/Heidelberg, Germany, 2017; pp. 21–36.
Koys, D.J. The e↵ects of employee satisfaction, organizational citizenship behavior, and turnover on
organizational e↵ectiveness: A unit-level, longitudinal study. Pers. Psychol. 2001, 54, 101–114. [CrossRef]
Taris, T.W.; Schreurs, P.J.G. Well-being and organizational performance: An organizational-level test of the
happy-productive worker hypothesis. Work Stress 2009, 23, 120–136. [CrossRef]
Mason, C.M.; Griffin, M.A. Group task satisfaction. The group’s shared attitude to its task and work
environment. Gr. Organ. Manag. 2005, 30, 625–652. [CrossRef]
Messersmith, J.G.; Patel, P.C.; Lepak, D.P.; Gould-Williams, J. Unlocking the black box: Exploring the link
between high-performance work systems and performance. J. Appl. Psychol. 2011, 96, 1105–1118. [CrossRef]
Van De Voorde, K.; Van Veldhoven, M.; Paauwe, J. Relationships between work unit climate and labour
productivity in the financial sector: A longitudinal test of the mediating role of work satisfaction. Eur. J.
Work Organ. Psychol. 2014, 23, 295–309. [CrossRef]
Rego, A.; Reis Júnior, D.; Cunha, M.P.E.; Stallbaum, G. Store creativity, store potency, store performance,
retailing. Manag. Res. 2016, 14, 130–149. [CrossRef]
González-Romá, V.; Gamero, N. Does positive team mood mediate the relationship between team climate
and team performance? Psicothema 2012, 24, 94–99.
Dolbier, C.L.; Webster, J.A.; McCalister, K.T.; Mallon, M.W.; Steinhardt, M.A. Reliability and validity of a
single-item measure of job satisfaction. Am. J. Heal. Promot. 2005, 19, 194–198. [CrossRef]
Ironson, G.H.; Smith, P.C.; Brannick, M.T.; Gibson, W.M.; Paul, K.B. Construction of a job in general scale: A
Comparison of global, composite, and specific measures. J. Appl. Psychol. 1989, 74, 193–200. [CrossRef]
Weiss, D.J.; Dawis, R.V.; England, G.W. Manual for the Minnesota Satisfaction Questionnaire. Minnesota Stud.
Vocat. Rehabil. 1967, 22, 120.
Judge, T.A.; Weiss, H.M.; Kammeyer-Mueller, J.D.; Hulin, C.L. Job attitudes, job satisfaction, and job a↵ect: A
century of continuity and of change. J. Appl. Psychol. 2017, 102, 356–374. [CrossRef]
George, J.M. Leader Positive Mood and Group Performance: The Case of Customer Service. J. Appl.
Soc. Psychol. 1995, 25, 778–794. [CrossRef]
Chi, N.W.; Chung, Y.Y.; Tsai, W.C. How do happy leaders enhance team success? The mediating roles
of transformational leadership, group a↵ective tone, and team processes. J. Appl. Soc. Psychol. 2011, 41,
1421–1454. [CrossRef]
Tanghe, J.; Wisse, B.; van der Flier, H. The formation of group a↵ect and team e↵ectiveness: The moderating
role of identification. Br. J. Manag. 2010, 21, 340–358. [CrossRef]
Barsade, S.; Gibson, D.E. Group emotion: A view from top and bottom. In Research on Managing Groups and
Teams; Neale, M.A., Mannix, E., Eds.; JAI: Creenwich, CT, USA, 1998; pp. 81–102.
Watson, D.; Clark, L.A.; Tellegen, A. Development and validation of brief measures of positive and negative
a↵ect: The PANAS scales. J. Pers. Soc. Psychol. 1988, 54, 1063–1070. [CrossRef]
Segura, S.L.; González-Romá, V. How do respondents construe ambiguous response formats of a↵ect items?
J. Pers. Soc. Psychol. 2003, 85, 956–968. [CrossRef] [PubMed]
Int. J. Environ. Res. Public Health 2020, 17, 69
50.
51.
52.
53.
54.
55.
56.
57.
58.
59.
60.
61.
62.
63.
64.
65.
66.
67.
68.
69.
70.
71.
72.
73.
74.
37 of 39
Boerner, S.; Von Streit, C.F. Promoting orchestral performance: The interplay between musicians’ mood and
a conductor’s leadership style. Psychol. Music 2007, 35, 132–143. [CrossRef]
Kahn, W.A. Psychological conditions of personal engagement and disengagement at work. Acad. Manag. J.
1990, 33, 692–724.
Macey, W.; Schneider, B. The meaning of employee engagement. Ind. Organ. Psychol. 2008, 1, 3–30. [CrossRef]
Schneider, B.; Macey, W.H.; Barbera, K.M. Driving customer satisfaction and financial success through
employee engagement. People Strateg. 2009, 32, 23–27.
Schneider, B.; Yost, A.B.; Kropp, A.; Kind, C.; Lam, H. Workforce engagement: What it is, what drives it, and
why it matters for organizational performance. J. Organ. Behav. 2018, 39, 462–480. [CrossRef]
Harter, J.; Schmidt, F.; Hayes, T. Business-unit-level relationship between employee satisfaction, employee
engagement, and business outcomes: A meta-analysis. J. Appl. Psychol. 2002, 87, 268–279. [CrossRef]
Schaufeli, W.A.; Salanova, M.; González-Romá, V.; Bakker, A.B. The measurement of engagement and
burnout: a two sample confirmatory factor analytic approach. J. Happiness Stud. 2002, 3, 71–92. [CrossRef]
Cruz-Ortiz, V.; Salanova, M.; Martínez, I. Liderazgo transformacional y desempeño grupal: Unidos por el
engagement grupal. Rev. Psicol. Soc. 2013, 28, 183–196. [CrossRef]
Torrente, P.; Salanova, M.; Llorens, S.; Schaufeli, W.B. Teams make it work: How team work engagement
mediates between social resources and performance in teams. Psicothema 2012, 24, 106–112.
Bakker, A.B.; Demerouti, E. Towards a model of work engagement. Career Dev. Int. 2008, 13, 209–223.
[CrossRef]
Torrente, P.; Salanova, M.; Llorens, S. Spreading engagement: On the role of similarity in the positive
contagion of work engagement. J. Work Organ. Psychol. 2013, 29, 153–159. [CrossRef]
Costa, P.; Passos, A.M.; Bakker, A. Empirical validation of the team work engagement construct. J. Pers.
Psychol. 2014, 13, 34–45. [CrossRef]
Tims, M.; Bakker, A.B.; Derks, D.; van Rhenen, W. Job crafting at the team and individual level: Implications
for work engagement and performance. Gr. Organ. Manag. 2013, 38, 427–454. [CrossRef]
Torrente, P.; Salanova, M.; Llorens, S.; Schaufeli, W.B. From “I” to “We”: The factorial validity of a team work
engagement scale. In Occupational Health Psychology: From Burnout to Well-Being; Neves, J., Gonçalves, S.,
Eds.; Scientific & Academic Publishing: Rosemead, CA, USA, 2013; pp. 335–355.
Vittersø, J.; Søholt, Y. Life satisfaction goes with pleasure and personal growth goes with interest: Further
arguments for separating hedonic and eudaimonic well-being. J. Posit. Psychol. 2011, 6, 326–335. [CrossRef]
Barrick, M.R.; Thurgood, G.R.; Smith, T.A.; Courtright, S.H. Collective organizational engagement: Linking
motivational antecedents, strategic implementation, and firm performance. Acad. Manag. J. 2015, 58, 111–135.
[CrossRef]
Ostro↵, C. The relationship between satisfaction, attitudes, and performance: An organizational level
analysis. J. Appl. Psychol. 1992, 77, 963–974. [CrossRef]
Kopelman, R.E.; Brief, A.P.; Guzzo, R.A. The role of climate and culture in productivity. In Organizational
Climate and Culture; Schneider, B., Ed.; Jossey-Bass Inc.: San Francisco, CA, USA, 1990; pp. 282–318.
Blau, P.M. Justice in Social Exchange. Sociol. Inq. 1964, 34, 193–206. [CrossRef]
Li, F.; Li, Y.; Wang, E. Task characteristics and team performance: The mediating e↵ect of team member
satisfaction. Soc. Behav. Personal. Int. J. 2009, 37, 1373–1382. [CrossRef]
Namasivayam, K.; Guchait, P.; Lei, P. The influence of leader empowering behaviors and employee
psychological empowerment on customer satisfaction. Int. J. Contemp. Hosp. Manag. 2014, 26, 69–84.
[CrossRef]
Bowen, D.E.; Schneider, B. A service climate synthesis and future research agenda. J. Serv. Res. 2014, 17,
5–22. [CrossRef]
Schneider, B.; White, S.S.; Paul, M.C. Linking service climate and customer perceptions of service quality:
Test of a causal model. J. Appl. Psychol. 1998, 83, 150–163. [CrossRef] [PubMed]
Heskett, J.L.; Sasser, W.; Schlesinger, L. The Service Profit Chain: How Leading Companies Link Profit and Growth
to Loyalty, Satisfaction, and Value; Free Press: New York, NY, USA, 1997.
Fredrickson, B.L. The role of positive emotions in positive psychology: The broaden-and-build theory of
positive emotions. Am. Psychol. 2001, 56, 218–226. [CrossRef] [PubMed]
Int. J. Environ. Res. Public Health 2020, 17, 69
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91.
92.
93.
94.
95.
96.
97.
38 of 39
Martin, L.L.; Stoner, P. Mood as input: What we think. In Striving and Feeling: Interactions Among Goals,
A↵ect, and Self-Regulation; Martin, L.L., Tesser, A., Eds.; L. Erlbaum Associates: Mahwah, NJ, USA, 1996;
pp. 279–301.
Rhee, S.Y. Group emotions and group outcomes: The role of group-member interactions. In A↵ect and
Groups (Research on Managing Groups and Teams); Mannix, E., Neale, M., Anderson, C., Eds.; Emerald Group
Publishing Limited: Bingley, UK, 2007; Volume 10, pp. 65–95, ISBN 0762314133.
Meneghel, I.; Salanova, M.; Martínez, I.M. Feeling good makes us stronger: How team resilience mediates
the e↵ect of positive emotions on team performance. J. Happiness Stud. 2016, 17, 239–255. [CrossRef]
Seong, J.Y.; Choi, J.N. E↵ects of group-level fit on group conflict and performance: The initiating role of
leader positive a↵ect. Gr. Organ. Manag. 2014, 39, 190–212. [CrossRef]
Shin, Y. Positive group a↵ect and team creativity: Mediation of team reflexivity and promotion focus.
Small Gr. Res. 2014, 45, 337–364. [CrossRef]
Kim, M.; Shin, Y. Collective efficacy as a mediator between cooperative group norms and group positive
a↵ect and team creativity. Asia Pacific J. Manag. 2015, 32, 693–716. [CrossRef]
Peñalver, J.; Salanova, M.; Martínez, I.M.; Schaufeli, W.B. Happy-productive groups: How positive a↵ect
links to performance through social resources. J. Posit. Psychol. 2019, 14, 377–392. [CrossRef]
Kim, M.J.; Choi, J.N.; Lee, K. Trait a↵ect and individual creativity: Moderating roles of a↵ective climate and
reflexivity. Soc. Behav. Pers. 2016, 44, 1477–1498. [CrossRef]
Tu, C. A multilevel investigation of factors influencing creativity in NPD teams. Ind. Mark. Manag. 2009, 38,
119–126. [CrossRef]
Chi, N.W.; Huang, J.C. Mechanisms linking transformational leadership and team performance: The
mediating roles of team goal orientation and group a↵ective tone. Gr. Organ. Manag. 2014, 39, 300–325.
[CrossRef]
Tsai, W.C.; Chi, N.W.; Grandey, A.A.; Fung, S.-C. Positive group a↵ective tone and team creativity: Negative
group a↵ective tone and team trust as boundary conditions. J. Organ. Behav. 2012, 33, 638–656. [CrossRef]
Bakker, A.B.; Demerouti, E.; Sanz-Vergel, A.I. Burnout and work engagement: The JD–R approach. Annu. Rev.
Organ. Psychol. Organ. Behav. 2014, 1, 389–411. [CrossRef]
Costa, P.L.; Passos, A.M.; Bakker, A.B. Direct and contextual influence of team conflict on team resources,
team work engagement, and team performance. Negot. Confl. Manag. Res. 2015, 8, 211–227. [CrossRef]
Mäkikangas, A.; Aunola, K.; Seppälä, P.; Hakanen, J. Work engagement–team performance relationship:
Shared job crafting as a moderator. J. Occup. Organ. Psychol. 2016, 89, 772–790. [CrossRef]
Reijseger, G.; Schaufeli, W.; Peeters, M.; Taris, T. Ready, set, go! A Model of the relation between
work engagement and job performance. In Occupational Health Psychology: From Burnout to Well-Being;
Gonçalves, S.P., Neves, J.G., Eds.; Scientific & Academic Publishing: Rosemead, CA, USA, 2012; Volume 1,
pp. 287–306.
García-Buades, E.; Martínez-Tur, V.; Ortiz-Bonnín, S.; Peiró, J.M. Engaged teams deliver better service
performance in innovation climates. Eur. J. Work Organ. Psychol. 2016, 25, 597–612. [CrossRef]
Salanova, M.; Agut, S.; Peiró, J.M. Linking organizational resources and work engagement to employee
performance and customer loyalty: The mediation of service climate. J. Appl. Psychol. 2005, 90, 1217–1227.
[CrossRef]
Luu, T.T. Collective job crafting and team service recovery performance: A moderated mediation mechanism.
Mark. Intell. Plan. 2017, 35, 641–656. [CrossRef]
McClelland, G.P.; Leach, D.J.; Clegg, C.W.; McGowan, I. Collaborative crafting in call centre teams. J. Occup.
Organ. Psychol. 2014, 87, 464–486. [CrossRef]
Riketta, M. The causal relation between job attitudes and performance: A meta-analysis of panel studies.
J. Appl. Psychol. 2008, 93, 472–481. [CrossRef]
Schneider, B.; Hanges, P.J.; Smith, D.B.; Salvaggio, A.N. Which comes first: Employee attitudes or
organizational financial and market performance? J. Appl. Psychol. 2003, 88, 836–851. [CrossRef]
Bashshur, M.R.; Hernández, A.; González-Romá, V. When managers and their teams disagree: A longitudinal
look at the consequences of di↵erences in perceptions of organizational support. J. Appl. Psychol. 2011, 96,
558–573. [CrossRef] [PubMed]
Menguc, B.; Auh, S.; Katsikeas, C.S.; Jung, Y.S. When does (mis)fit in customer orientation matter for frontline
employees’ job satisfaction and performance? J. Mark. 2016, 80, 65–83. [CrossRef]
Int. J. Environ. Res. Public Health 2020, 17, 69
39 of 39
98.
Henderson, L.; Knight, T. Integrating the hedonic and eudaimonic perspectives to more comprehensively
understand wellbeing and pathways to wellbeing. Int. J. Wellbeing 2012, 2, 196–221. [CrossRef]
99. Salanova, M.; Schaufeli, W.B.; Xanthopoulou, D.; Bakker, A.B. The gain spiral of resources and work
engagement: Sustaining a positive worklife. In Work Engagement: A Handbook of Essential Theory and Research;
Psychology Press: East Sussex, UK, 2010; pp. 118–131.
100. Xanthopoulou, D.; Bakker, A.B.; Demerouti, E.; Schaufeli, W.B. Work engagement and financial returns: A
diary study on the role of job and personal resources. J. Occup. Organ. Psychol. 2009, 82, 183–200. [CrossRef]
101. Singh, A.; Syal, M.; Grady, S.C.; Korkmaz, S. E↵ects of green buildings on employee health and productivity.
Am. J. Public Health 2010, 100, 1665–1668. [CrossRef] [PubMed]
102. Gil, F.; Rico, R.; Alcover, C.M.; Barrasa, Á. Change-oriented leadership, satisfaction and performance in work
groups: E↵ects of team climate and group potency. J. Manag. Psychol. 2005, 20, 312–328. [CrossRef]
103. Brady, G.M.; Truxillo, D.M.; Cadiz, D.M.; Rineer, J.R.; Caughlin, D.E.; Bodner, T. Opening the Black Box:
Examining the Nomological Network of Work Ability and Its Role in Organizational Research. J. Appl.
Psychol. 2019. [CrossRef]
104. Truxillo, D.M.; Cadiz, D.M.; Rineer, J.R. The Aging Workforce: Implications for Human Resource Management
Research and Practice. In Oxford Handbooks Online: Business & Management; Oxford University Press: Oxônia,
Inglaterra, UK, 2014; ISBN 9780199935406.
105. Ayala, Y.; Peiró Silla, J.M.; Tordera, N.; Lorente, L.; Yeves, J. Job Satisfaction and Innovative Performance in
Young Spanish Employees: Testing New Patterns in the Happy-Productive Worker Thesis—A Discriminant
Study. J. Happiness Stud. 2017, 18, 1377–1401. [CrossRef]
106. Hau↵, S.; Richter, N.F.; Tressin, T. Situational job characteristics and job satisfaction: The moderating role of
national culture. Int. Bus. Rev. 2015, 24, 710–723. [CrossRef]
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Why success doesn’t lead to satisfaction - January 2023
https://hbr.org/2023/01/why-success-doesnt-lead-to-satisfaction
What the longest study on human happiness found is the key to a good life
https://apple.news/A5hQ0-pBkRVmNn-9i2wAd8g
Happy Soldiers are highest performers
https://ppc.sas.upenn.edu/sites/default/files/happysoldiershighperformers.pdf
This Study Says Being Happy at Work Really Makes You More Productive
https://fortune.com/2015/10/29/happy-productivity-work/
Why Happy Employees are 12% More Productive
https://www.fastcompany.com/3048751/happy-employees-are-12-more-productive-at-work
Does Employee Happiness Have an Impact on Productivity?
https://deliverypdf.ssrn.com/delivery.php?ID=442100001087088096001096091099100126033069042014023087069029085022114002096003112121107056043003059006011084114125007004079006098001090058041023065122101100082072086055054002072088112091007031113127095028125085066026076092098113117065126080076119110126&EXT=pdf&INDEX=TRUE
Goals, values and the pursuit of happiness
https://www.87percent.co.uk/blog/2020/10/14/goals-values-and-the-pursuit-of-happiness
How Healthy and Unhealthy Values Predict Hedonic and Eudaimonic Well-Being: Dissecting Value-Related Beliefs and Behaviours
https://link.springer.com/article/10.1007/s10902-021-00396-z
Build a Culture That Aligns with People’s Values
https://hbr.org/2020/04/build-a-culture-that-aligns-with-peoples-values
Employees Are Sick of Being Asked to Make Moral Compromises
https://hbr.org/2022/02/employees-are-sick-of-being-asked-to-make-moral-compromises
Make Your Values Mean Something
https://hbr.org/2002/07/make-your-values-mean-something
How To Sustain Company Culture In A Hybrid Work Model
https://www.forbes.com/sites/tracybrower/2021/02/07/how-to-sustain-company-culture-in-a-hybrid-work-model/?sh=f609d9100910
When Subtraction Adds Value
https://hbr.org/2022/02/when-subtraction-adds-value
Addressing burnout - Forbes
https://www.forbes.com/sites/bryanrobinson/2023/01/04/addressing-burnout-flexible-work-and-a-people-first-work-culture-in-2023/?sh=3f9972965486
1/25/23, 2:21 PM
Is Quiet Quitting Real?
SEPTEMBER 6, 2022
Is Quiet Quitting Real?
BY JI M HARTER
STORY HIGHLIGHT S
At least half of the U.S. workforce is quiet quitting
The workplace, amid the pandemic, got worse for younger workers
Managers are essential to combatting quiet quitting
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
1/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
"Quiet quitters" make up at least 50% of the U.S. workforce -- probably more, Gallup finds.
The trend toward quiet quitting -- the idea spreading virally on social media that millions
of people are not going above and beyond at work and just meeting their job description
-- could get worse. This is a problem because most jobs today require some level of
extra effort to collaborate with coworkers and meet customer needs.
U.S. employee engagement took another step backward during the second quarter of
2022, with the proportion of engaged workers remaining at 32% but the proportion of
actively disengaged increasing to 18%. The ratio of engaged to actively disengaged
employees is now 1.8 to 1, the lowest in almost a decade.
Get the insights you need to create an exceptional
workplace.
Subscribe to the Gallup at Work newsletter to get our latest articles, analytics
and advice.
Fields marked with an asterisk (*) are required
* Email Address
* Country or Region
Select One
I'm not a robot
reCAPTCHA
*
Sign Up
The drop in engagement began in the second half of 2021 and was concurrent with the
rise in job resignations. Managers, among others, experienced the greatest drop.
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
2/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
The overall decline was especially related to clarity of expectations, opportunities to
learn and grow, feeling cared about, and a connection to the organization's mission or
purpose -- signaling a growing disconnect between employees and their employers.
U.S. Employee Engagement Trend, Annual Averages
% Engaged
% Actively disengaged
0
2000
2002
50
40
30
20
10
2001
2003
2004
2005
2006
2007
2008
2009
2010
20
Get the data • Download image
Many quiet quitters fit Gallup's definition of being "not engaged" at work -- people who do
the minimum required and are psychologically detached from their job. This describes
half of the U.S. workforce.
Everyone else is either engaged (32%) or actively disengaged (18%). The latter are "loud
quitters." Actively disengaged employees tend to have most of their workplace needs
unmet and spread their dissatisfaction -- they have been the most vocal in TikTok posts
that have generated millions of views and comments.
Most employees who are not engaged or actively disengaged are already looking for
another job.
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
3/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
The Workplace Has Gotten Worse for Younger Employees
Gallup finds a decline in engagement and employer satisfaction among remote Gen Z
and younger millennials -- those below age 35.
This is a significant change from pre-pandemic years. Since the pandemic, younger
workers have declined significantly in feeling cared about and having opportunities to
develop -- primarily from their manager.
These younger employee advantages have mostly disappeared.
The percentage of engaged employees under the age of 35 dropped by six
percentage points from 2019 to 2022. And during the same time, the percentage of
actively disengaged employees increased by six points.
Younger workers have dropped 10 or more points in the percentage who strongly
agree that someone cares about them, someone encourages their development, and
they have opportunities to learn and grow.
Fully remote and hybrid young workers dropped 12 points in strong agreement that
someone encourages their development.
Disturbingly, less than four in 10 young remote or hybrid employees clearly know what
is expected of them at work.
Quiet Quitting: In Most Ca…
Ca…
Solving the Quiet Quitting Crisis
It's clear that quiet quitting is a symptom of poor management.
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
4/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
First, address manager engagement. Only one in three managers are engaged at work.
Senior leadership needs to reskill managers to win in the new hybrid environment.
Managers must learn how to have conversations to help employees reduce
disengagement and burnout. Only managers are in a position to know employees as
individuals -- their life situation, strengths and goals.
Gallup finds the best requirement and habit to develop for successful managers is
having one meaningful conversation per week with each team member -- 15-30
minutes.
Managers need to create accountability for individual performance, team
collaboration and customer value -- and employees must see how their work
contributes to the organization's larger purpose. Decisions about where people work -on-site, remote or a hybrid schedule -- should keep these factors in mind. Importantly,
every organization needs a culture in which people are engaged and feel they belong.
Gallup's findings are based on a random sample of 15,091 full- and part-time U.S.
employees aged 18 and over, surveyed in June of 2022.
Build an engaged workforce that goes the extra mile:
Learn what employee engagement means and how to improve it.
Partner with Gallup to discover what your employees need to succeed.
Explore the Q12, Gallup's science-backed survey for measuring employee
engagement.
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
5/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
AUTHOR(S)
Jim Harter, Ph.D., is Chief Scientist for Gallup's workplace management practice. He
recently coauthored Wellbeing at Work, a book that explores how to build resilient and
thriving teams in organizations. He is also coauthor of the No. 1 Wall Street Journal
bestseller It's the Manager and New York Times bestsellers 12: The Elements of Great
Managing and Wellbeing: The Five Essential Elements.
Sangeeta Agrawal, Ryan Pendell and Puneet Singh contributed to this article.
AUGU ST 3, 2022
The Old Workplace Is Gone. What's a
Board to Do?
BY JI M CLI F TON AND CHAD HOLLIDAY
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
6/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
There are 125 million full-time employees in the United States. Of them, 56% tell Gallup
they can do their office jobs remotely -- so, 70 million U.S. workers say they can work
from home (WFH).
Of these, 30% say they don't want to come into the office anymore and prefer fully
remote, 60% say they want a hybrid arrangement, and only 10% prefer to work fully onsite.
A new will of the world has emerged -- one that we couldn't have imagined the day
before the pandemic.
Who knew we would all wake up the same morning in one global Zoom conversation?
And so far, it sort of works.
What are you going to do about this new will as a board member? How you bring
employees back to the office is closely connected to very large amounts of money that
go beyond expensive office space.
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
7/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
You might say figuring out how to bring employees back is a job for the CEO and
management team, not the board. We see this as a major strategic decision that should
be implemented by the management team but probed and tested by the board.
A board member's job is to ask the right questions to support the CEO in making the final
decision. For example: Have we lost mission-critical people to other companies because
of our WFH policies? Why? Do our customers have a preference regarding our WFH
approach, or do they just care about the results?
Another critical question: How have we developed our managers to be effective in a
WFH or hybrid environment? Right now, managers don't know what to do and are
accumulating dangerous levels of stress and subsequent burnout (real mental health
issues).
According to Gallup's recent U.S. panel research, managers are more miserable at work
than their employees. Your team leaders have likely never been taught how to manage a
much less attached worker.
Right now, managers don't know what to do and are
accumulating dangerous levels of stress and subsequent
burnout (real mental health issues).
Worldwide productivity is on the line, especially because your customer connections run
through your workplace. The money players in your company are the customer-facing
teams. As goes the quality of those relationships, so goes sales, profit and stock price.
The simplest way to say it is that your employees know all your customers. Therein lies
the new risk.
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
8/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
The risk the board and CEO need to consider is a potential customer retention problem,
which will eventually affect stock price far more directly than employee retention.
Respected CEOs are all over the place about how to bring employees back. "Come back
to normal or you are fired." Others are saying, "You don't have to ever come back -- fully
remote is fine." There remains an unanswered question in every board room -- will giving
approval to hybrid and remote employees cause overall productivity to go up or down?
That is the question.
Gallup's answer: If you get it right, productivity can soar.
Have you received this call, "Hey boss, great news -- the family and I are going to sell our
home in the city and move to the lake house. So cool, my office will be in the boat house."
Then they always say this, "It won't hurt my productivity at all -- I am more productive out
here than in the office."
Your senior executives are moving to the hills, too. Dear CEO, "Mavis and the kids love the
environment so much at our Montana place, we are going to live out there much of the
year now."
CEO says, "Have you gone nuts? We need you here in customer sessions."
When Gallup asked the 70 million U.S. employees why they'd rather not come in anymore,
their first response is "the commute." Their next answer is it "helps my wellbeing" and the
third is "it works better for my family."
Worldwide productivity is on the line.
Has your board discussed if you even need people in tall buildings in big cities anymore?
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
9/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
The appeal of working in shiny steel buildings with enchanting lobby water sounds won't
bring employees in anymore. Eventually, this will crush commercial real estate as well as
supporting retail shops and cafes.
What if the shift to WFH crushes GDP per capita, America's ultimate performance
measurement? All because Zoom doesn't work as well for customer retention and
buildouts. So, deal-making can no longer ride on relationships and ideas quite like before.
Have you ever noticed that humor doesn't come across Zoom? Does it make you
wonder what else isn't coming across -- like trust and caring?
On the other hand, GDP per capita -- the sum of all the stuff we make and sell each other
-- has largely been in deceleration for 50 years. So, it isn't like, "We have to get back to
what works." We would argue, along with other experts, that America has needed
transformational workplace change for 50 years.
Doesn't it seem that our American management system was already broken if 90% of
our 70 million office workers say they don't want to come back to the office full time?
Whether it's, "I want out and I am never coming back to that rat race again" or, "I am
dropping off the grid -- forever."
A new will of the world has emerged -- one that we
couldn't have imagined the day before the pandemic.
The board and CEO need to know the big potential risks. Productivity, customer
retention, wellbeing (mental health) and fast declining relationships that bind the place
together with employees and customers -- could now all be at high risk.
Here is how to restart your workplace.
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
10/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
Call your board and CEO together and commit to hybrid. Do that or nobody with any
talent will ever work for your firm again. It is your biggest current decision and has
extraordinary implications for growth, profit and stock price.
Establish on-site days as Tuesday/Wednesday/Thursday. This is a promise employees
make to each other, not a promise they make to management. We need to know which
days we are all in together so we can collaborate. We also need to know when we can
celebrate successes, meet new colleagues and tell each other customer stories.
Not all employees will be hybrid, of course. Ten percent (10%) of your total office and
executive workers want to be on-site Monday through Friday. That's great. In addition,
managers need to know which employees will be fully remote so they can be reviewed
and coached differently.
Require a recently discovered silver bullet: The manager must now hold one meaningful
conversation per week with each employee -- 15 to 30 minutes, usually about goals,
customers and wellbeing. This prevents employees from morphing into gig workers.
Gallup finds this leadership habit magically develops rich, high-performance
relationships.
And lastly, aim every workplace decision at the customer relationship, which is hardwired to your employee relationships.
Do these four things well, and a new hybrid workplace will work better than your old one.
AUTHOR(S)
Jim Clifton is Chairman of Gallup. Chad Holliday is the former chair of DuPont, Bank of
America, and Shell.
RELEASE DATE:
September 6, 2022
SOURCE: Gallup https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx
CONTACT: Gallup World Headquarters, 901 F Street, Washington, D.C., 20001, U.S.A
+1 202.715.3030
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
11/12
1/25/23, 2:21 PM
Is Quiet Quitting Real?
Copyright © 2023 Gallup, Inc. All rights reserved.
https://www.gallup.com/workplace/398306/quiet-quitting-real.aspx?version=print
12/12
Asia Pacific Management Review xxx (2017) 1e8
Contents lists available at ScienceDirect
H O S T E D BY
Asia Pacific Management Review
journal homepage: www.elsevier.com/locate/apmrv
Pursuit of organisational trust: Role of employee engagement, psychological
well-being and transformational leadership
Lalatendu Kesari Jena a, *, Sajeet Pradhan b, Nrusingh Prasad Panigrahy c
a
Central University of Orissa, Koraput, Orissa, India
International Management Institute, New Delhi, India
c
Dredging Corporation of India Ltd, Visakhapatnam, India
b
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 10 August 2016
Received in revised form
13 August 2017
Accepted 3 November 2017
Available online xxx
Both practitioners and scholars have shown a great deal of interest to study the trust factors that compels
for establishing cordial interpersonal relations across society. However, in the context of organisation, the
study on trust stands challenged for manifold reasons: lack of clarity between trust and productivity, lack
of specificity on interventional mechanisms and the validity between trust and its possible antecedents.
Therefore, the objective of this research is twofold: firstly, to identify the direct effect of employee
engagement on organisational trust and secondly, to investigate the indirect effect of psychological wellbeing and transformational leadership on the relationship between employee engagement and organisational trust. Bootstrapping technique (Hayes, 2012) in addition to the mediation process through
PRODCLIN2 was carried out during SEM analysis. The findings indicate that executives have a higher level
of trust when they are able to perceive meaningful employee engagement, transformational leadership
and psychological well-being from their respective employer.
© 2017 College of Management, National Cheng Kung University. Production and hosting by Elsevier
Taiwan LLC. All rights reserved.
Keywords:
Employee engagement
Psychological well-being
Transformational leadership
Organisational trust
Manufacturing executives
India
1. Introduction
Modern day organizations are seeking explanations from academicians and scholars to explore the factors that may improve
willingness and involvement of employees for realizing organisational tasks (Jones & George, 1998). In this age of knowledge, fulfilling the higher order needs of employee is a priority and is
primarily realized through establishing trust among employees and
organisation. Earlier studies have evinced the fact that, trustworthy
relations endorses cooperation (Schoorman, Mayer, & Davis, 2007);
information sharing (Aryee, Budhwar, & Chen, 2002) and also
recompenses the limited abilities among employees (Laschinger &
Finegan, 2005) through fostering group dynamics.
Employees demonstrate their trust and commitment when they
are engaged properly in their work assignments (Baumruk, 2004)
as it galvanizes self-motivation to perform their role efficiently. The
* Corresponding author.
E-mail addresses: lkjena1980@gmail.com (L.K. Jena), sajeet.pradhan@imi.edu
(S. Pradhan), nrusinghpanigrahy@rediffmail.com (N.P. Panigrahy).
Peer review under responsibility of College of Management, National Cheng
Kung University.
significance of engagement as a prima-facie to organisational trust
need to be acknowledged (Macey, Schneider, Barbera, & Young,
2009; Rich, Lepine, & Crawford, 2010) and is warranted for
further empirical confirmation. Engagement is attaining importance among practitioners worldwide as it has become an established belief that meaningful work engagement connects
employees to their organisation (May, Gilson, & Harter, 2004;
Macey & Schneider, 2008; Jena & Pradhan, 2017), by fostering a
sense of ownership and loyalty. Supporting this proposition, Thayer
(2008) has urged future researchers to explore the factors that will
promote trust and satisfaction among employees. Engagement is a
driver of business success, as an engaged employee perseveres to
achieve organisational goal through displaying their proactive
attitude (Schaufeli & Bakker, 2004) amidst adverse situations.
Recent years have observed a shift in research emphasis from
dysfunctional obsession for productivity even at the cost of human
dissatisfaction to focus on psychological well-being and inclusive
growth (Kahneman, 1999, pp. 3e25; Ryff & Singer, 1998). Psychological well-being promotes creative thinking and demonstrates
pro-social behavior as it combines feeling good and working
effectively (Huppert, 2009) when there is a meaningful work
engagement (Schaufeli & Bakker, 2004). On the other hand,
https://doi.org/10.1016/j.apmrv.2017.11.001
1029-3132/© 2017 College of Management, National Cheng Kung University. Production and hosting by Elsevier Taiwan LLC. All rights reserved.
Please cite this article in press as: Jena, L. K., et al., Pursuit of organisational trust: Role of employee engagement, psychological well-being and
transformational leadership, Asia Pacific Management Review (2017), https://doi.org/10.1016/j.apmrv.2017.11.001
2
L.K. Jena et al. / Asia Pacific Management Review xxx (2017) 1e8
transformational leadership is a pragmatic approach to improve
employee's attitude (Wofford, Goodwin, & Whittington, 1998) and
performance (Judge & Piccolo, 2004) in a work setting. Transformational leadership plays a crucial role (Dvir, Eden, Avolio, &
Shamir, 2002) in instilling confidence in an engaged employee to
perform beyond expectations. Therefore, it is plausible that psychological well-being and transformational leadership can help
engaged employee to derive organisational trust. Although this
proposition sounds logical and pragmatic, there is a paucity of
studies that verify a systematic association among employee
engagement and organisational trust.
Building on earlier research works, we have attempted to make
two key contributions in this present study. First, we have investigated a probable effect of employee engagement on organisational
trust building. Previous studies on employee engagement have
focused on job attitude like job satisfaction, without inquiring their
psychological attachment and perception towards their sustainable
job relations. The present study on exploring the relationship between engagement and trust will clarify the cognitive and affective
engagement of employees towards their organisation. Second, we
have tried to examine the mediating role of psychological wellbeing and transformational leadership in explaining the effect of
the interaction between employee engagement and organisational
trust. Our assertion is that both these mediators might help us
explain the relationship between employee engagement and
organisational trust. This investigation will provide theoretical and
practical significance of clarifying the challenges associated with
the intervention mechanisms to foster organisational trust.
1.1. Employee engagement and organisational trust
Single minded dedication, vigor and gratifying state or absorption in one's work assignment are some of the essential prerequisites for employee engagement (Albrecht, 2010; Schaufeli,
Salanova, Gonzalez-Roma, & Bakker, 2002). Engagement starts
from the process of induction of an employee to an organisation
and then is followed through relevant learning and development
opportunities to do the job assignment as well as receiving a support structure from the leadership hierarchy (Macey et al., 2009).
Work engagement is evidential when an employee enjoys autonomy while making decisions without much consulting with the
superiors. Also, superior authorities allow them without meddling
much when they have trust and confidence on their subordinate's
ability and competencies.
Trust is regarded as an inclination (Farris, Senner, & Butterfield,
1973), susceptibility through experiencing the socialization (Clarke
& Payne, 1997) process and presumes mutual reliability (Mayer,
Davis, & Schoorman, 1995). Engagement is an indication that the
employee trusts the organisational values and hence is keen on
contributing to it in order to attain business goals. The trust factor
gets enhanced when it is perceived that the organisational
engagement norms are fair in having a defined reward, recognition
and succession planning in the organisation. Schaufeli and Bakker
(2004) posited that engagement improves employees' reliance towards organisation and lowers the tendency to quit. We endorse
the views of Towers Perrin (2003) which acknowledges that emotions and rationality are core constituents of trust. It is presumed
that emotions are an offshoot of trust, satisfaction and a sense of
fulfillment and in an organisation it is derived from one's productive engagement.
A perpetual difficulty that has impeded earlier research work on
trust has been the dearth of clarity and lack of identifying the
organisational factors that contribute to promulgate trust (Cook &
Wall, 1980). Earlier researchers have considered trust as a
comprehensive understanding to carry forward a relationship and
trust as the binding glue (Lewis & Weigert, 1985). In organisational
context, these broad understandings do not offer much clarity
especially, on why an employee would trust its employer and
continue to be in the same organisation for a long time.
We are of the view posited by Cook and Wall (1980) to define
trust as, “the extent to which one is willing to ascribe good intentions to and have confidence in the words and action”. Sitkin
and Roth (1993) proposed the norm of value congruence to be
the foundation of trust and defined it as, “the compatibility of an
employee's beliefs, values and engagement with the organisation's
vision and strategic goals”. In their meta-analysis of trust, which
includes 132 studies related to the same topic, Colquitt, Scott, and
LePine (2007) came to an understanding that, “trust is a vital
component of effective working relationship”. Later studies have
also empirically confirmed that trust reposed by the employer and
co-workers affect lower turnover (Ferres, Connell, & Travaglione,
2004), higher commitment (Tan & Tan, 2000) and higher
perceived organisational support (Sousa-Lima, Michel, & Caetano,
2013). Similar claims were also made by Shantz and Alfes (2015),
reporting a negative association between employee engagement
and employee's turnover intention.
Nyhan and Marlowe (1997) defined organisational trust as
having trust in one's organisation and their leaders by creating an
intra-organisational value chain both horizontally and vertically for
realizing organisational goals. Trust is a feeling of confidence and is
created on the belief of meaningful engagement. Our proposition of
trust for this study is through considering trust as a systems form
rather than considering it as an interpersonal one and is primarily
based on the derivation from the structure and process of organisational values and system. To strengthen our proposition, we
quote the empirical study of Katou (2013) which has used samples
from Greece public and private organizations to investigate the
effect of HRM system on employee engagement. Considering the
fact that very few empirical investigations (Katou, 2013) have
tested the relationship between employee engagement and
organisational trust, this study will make significant contribution
theoretically as well as will have practical implication for the organizations. To strengthen our proposition, Mondalek (2013) stated
that highly engaged employees are more likely to promote organisational trust. Similar assertion can also be drawn based on industry reports like Edelman's Trust Barometer survey (Jiang, 2016),
which suggest that employee engagement is key to building
employee trust. In addition, Nelson (2015) has clearly emphasized
how employee engagement leads to organisational trust for
improving employee's flexibility and responsiveness. In the light of
this argument, the first hypothesis of our study is:
H1. Employee engagement is positively related to organisational
trust.
1.2. Employee engagement, organisational trust: Psychological
well-being as a mediator
The construct of psychological well-being is theoretically
different from happiness as it encompasses intrapersonal features
(Garcia, 2011) associated with adaptation and self-actualization.
The multi-dimensional model of psychological well-being proposed by Ryff (1989) comprises of the following dimensions:
“positive relationship, environmental mastery, self-acceptance,
autonomy, personal growth and purpose in life”. Marlatt (2002)
in his empirical findings proved that meaningful engagement reduces despair, anxiety and hostility while it enhances one's psychological well-being.
Therefore, it is apparent that cultivating attention and mindfulness in an engaging atmosphere may likely to breed trust. The
Please cite this article in press as: Jena, L. K., et al., Pursuit of organisational trust: Role of employee engagement, psychological well-being and
transformational leadership, Asia Pacific Management Review (2017), https://doi.org/10.1016/j.apmrv.2017.11.001
L.K. Jena et al. / Asia Pacific Management Review xxx (2017) 1e8
circumflex model of emotion has added to our belief through
theorizing psychological well-being as a measure of pleasurable or
hedonic facet of one's feeling of well-being (Russell, 1980). Tripathi
(2011) in his empirical study has investigated the relationship between psy-cap and well-being confirming that; psychological wellbeing results from employee's attitude and is an off-shoot of the
experience that one derives from one's job engagement. A low rate
of work engagement might be attributed to global crisis in raising
organisational productivity and employee's psychological wellbeing (Wah, 1999). Though there is a growing interest for
enhancing engagement and providing an engaging atmosphere in
the workplace, however many employees have a continued resistance to derive psychological well-being (Mache et al., 2014).
The relationship of psychological well-being as a mediator between engagement and trust is still disputed, as practitioners and
researchers have ostensibly demoted the notion of happy and
productive worker being trustful all the time. In our study, we
propose this relegation as untimely while suggesting for understanding the role of psychological well-being as a forerunner of
organisational trust. Although this holds lot of merit, still there is
the paucity of studies explaining the relationship between
engagement and organisational trust through the role of psychological well-being. Therefore, it would be interesting to test the
mediating role of psychological well-being on the causal relationship between employee engagement and organisational trust.
H2. Psychological well-being mediates the relationship between
employee engagement and organisational trust.
1.3. Employee engagement, organisational trust: Transformational
leadership as a mediator
Contemporary times have witnessed a steady increase of interest to understand the association among leadership style and
employee's trust, well-being. Precisely, the influence of leadership
in sustaining employee's trust (DeRue, Nahrgang, Wellman, &
Humphrey, 2011; Dickson, Hartog, & Mitchelson, 2003) is highly
relevant and contentious among industry practitioners. Transformational leadership in this context articulates through creating
an engaging vision for followers towards realizing both intrinsic
need and organisational targets. Bass (1997) proposed four dimensions of transformational leadership: idealized influence,
inspirational motivation, intellectual stimulation and individualized consideration that might lead to individual well-being and
organisational growth. Idealized influence advocates leaders as role
models who articulate a compelling vision for followers. Inspirational motivation is a guiding path that constantly inspires and
motivates them to achieve the desired results despite hardships. An
important trait of transformational leadership is to encourage
creativity while prompting employees to think out of box and to be
constantly innovative. Finally, individualized consideration defines
the degree of leader's consideration to address employee's needs.
Earlier studies have posited that the dimension of individualized
consideration and idealized influence affects the perception of
follower employees' trust and confidence through gratitude and
empathy (Franke & Felfe, 2011; Molero, Cuadrado, & Morales,
2007).
An engaging work atmosphere promotes a sound leaderemployee relationship that is characterized by appreciation, confidence and trust for achieving psychological well-being (Tepper,
2000). When subordinates perceive their leader for placing
necessary efforts to resolve problems, the trust factor gets heightened which in return may positively affect their attitude towards
work (Yang, 2012; Yukl, 2012). Similar finding has also been reported by Pradhan and Pradhan (2016). In their empirical study of
3
Indian IT professionals, the duo reported that transformational
leaders' causal effect on employee's job attitudes was mediated by
meaningful work. Transformational leaders are capable of encouraging employee's to perform beyond the expectation, through
meaningful engagement and trust. In a dynamic business environment, we propose that leaders' attention to provide a meaningful engagement, openness to share constructive feedback
strengthens employee's trust towards both the leader as well as the
organisation. Therefore, we propose that transformational leadership might act as a mediator between employee engagement and
organisational trust (refer to Fig. 1). Hence,
H3. Transformation leadership mediates the relationship between employee engagement and organisational trust.
2. Method
2.1. Sample
The study was carried out with executives employed in multinational service industries operating in eastern India. The sample
respondents were employed in banking, insurance sectors and they
are posted in several units around Bhubaneswar and Kolkata region
of eastern India. Prospective executives with more than two years
of work experience and have worked one year under their reporting manager in their present establishment were asked to participate in the survey. We have approached the respective HR heads of
service establishments to help us to carry out the survey in their
company premises. After obtaining the approval from competent
authority of respective establishments through respective HR departments, a formal invitation was sent to each executive respondent stating the purpose of our research survey while assuring
them about the confidentiality of their participation. For minimizing participant's response bias, we have followed the approach
prescribed by Podsakoff and Organ (1986) through not indicating
the construct and variable details in the questionnaire. The items of
respective scales were arbitrarily ordered to observe the respondents consistency motive. The questionnaire was presented in
English language and interpretation in vernacular medium was not
required as all the sample respondents were literate and were able
to understand the items and its interpretations clearly. Willing
participants were asked to complete the survey at their convenience and were advised to return the filled in instrument in a
sealed envelope to HR department for our collection. The survey
was carried out during 1st quarter of FY 2016.
We distributed 600 questionnaires out of which we received
562 responses (93.6%) of which 511 (85.16%) were considered to be
usable for further statistical analysis. The final overall sample
Psychological Well-being
Employee Engagement
Organisational Trust
Transformational Leadership
Fig. 1. Conceptual framework of the study.
Please cite this article in press as: Jena, L. K., et al., Pursuit of organisational trust: Role of employee engagement, psychological well-being and
transformational leadership, Asia Pacific Management Review (2017), https://doi.org/10.1016/j.apmrv.2017.11.001
4
L.K. Jena et al. / Asia Pacific Management Review xxx (2017) 1e8
comprises of 394 male executive respondents (77.10%) and 117 female executive respondents (22.89%). The average age of the
sample executive was 34.62 years indicating that the majority of
the respondents were aged between 29 and 38 years. The percentage of respondents having post-graduate degrees was 39.8%
and the remaining participants were having university degree or a
professional degree.
2.2. Measures
2.2.1. Employee engagement
Utrecht Work Engagement Scale (UWES) developed by Schuafeli
and Bakker (2003) having 17 items was used to measure employee
engagement. The scale comprises of three dimensions, vigor,
dedication and absorption. There are seventeen statements in total
having, six statements each for vigor and absorption and five
statements on dedication. An item of each dimension of a scale: “At
my work I feel bursting with energy” (vigor); “I find the work I do
full of meaning and purpose” (dedication); “Time flies when I am
working” (absorption). The scale was widely used with various
samples across organizations, continents and has established
sound psychometric properties and factorial validity. Schaufeli and
Bakker (2003) have derived more than 0.70 Cronbach alpha
(Nunnally, 1978) in the three dimensions and hence has achieved
high internal consistency. Participants have rated the instrument
on a 5 point Likert type scale (1 ¼ strongly disagree to 5 ¼ strongly
agree). The overall Cronbach's alpha (a) of the scale for the present
study is 0.86.
Prior to SEM analysis for the combined structural/measurement
model (Kline, 2005) we have performed confirmatory factor analysis of the variable. The validity test resulted the factor validity of
the construct: overall cumulative variance ¼ 68.7% (exceeded 50%
with factor loading of each item exceeded 0.50); KMO ¼ 0.87
(exceeding the recommended level of 0.50); Bartlet's test of
spherecity c2 ¼ 2226.71 (p < 0.01) with the eigenvalue of three
dimensions at 6.94, 3.26 and 1.42 (exceeded the recommended
value of 1.00).
2.2.2. Psychological well-being
Ryff’s (1989) 54 item self-report scale has been used to measure
psychological well-being. The six dimensions of psychological wellbeing that was used are: self-acceptance, positive relations with
others, autonomy, environmental mastery, purpose in life and
personal growth. Items were measured on a 5 point Likert type
scale with 1 ¼ strongly disagree to 5 ¼ strongly agree. There are few
reverse scored items and due care were taking while treating the
data for further statistical analysis. A positive item of the scale includes, “In general I feel confident and positive about myself” and a
reverse scored item contains, “I don't have a good sense of what is I
am trying to accomplish in life”. Earlier research has revealed 0.94
for the 54 item scale and across dimensions the reliability was reported ranging from 0.77 to 0.86 (Kafka & Kozma, 2002). The current study has obtained 0.83 Cronbach alpha value (a) that is above
the prescribed cut-off of 0.70 (Nunnally, 1978).
The factor validity for our study has reported: overall cumulative variance ¼ 54.2% (exceeded 50% with factor loading of each
item exceeded 0.50); KMO ¼ 0.81 (exceeding the recommended
level of 0.50); Bartlett's test of spherecity c2 ¼ 2416.41 (p < 0.01)
with the eigenvalue of six dimensions of psychological well-being
at 5.91, 4.14, 4.01, 2.36, 1.81 and 1.63 (exceeded the recommended
value of 1.00).
2.2.3. Transformational leadership
Behavior of organisational leaders was measured by using 23
items transformational leadership behavior inventory (Podsakoff,
Mackenzie, Moorman, & Fetter, 1990). There are six dimensions of
the scale for measuring different facets of transformational leadership: acceptance of group goals, high performance expectations,
intellectual stimulations, appropriate role model, articulating
vision and individualized support. Responses on the scale was elicited through 5 point Likert type scale (1 ¼ strongly disagree to
5 ¼ strongly agree). Executives were briefed to respond to the items
keeping their leader or manager interacting with them in their
respective work unit on daily basis. A sample item of the scale includes, “My manager paints an interesting picture of the future for
us”. Earlier studies have reported Cronbach's alpha reliability in the
range of 0.89, 0.87 and 0.82 (Herold, Fedor, Caldwell, & Liu, 2008;
Jung, Yammarino, & Lee, 2009). The present study has reported
internal consistency of 0.90 indicating suitable reliability.
The computation of factor validity has adopted the procedures
prescribed by Kline (2005) and has reported: overall cumulative
variance ¼ 61.6% (exceeded 50% with factor loading of each item
exceeded 0.50); KMO ¼ 0.84 (exceeding the recommended level of
0.50); Bartlett's test of spherecity c2 ¼ 2111.07 (p < 0.01) with the
eigenvalue of six dimensions of transformational leadership at 6.21,
4.14, 3.22, 3.07, 2.19, 1.88 (exceeded the recommended value of
1.00).
2.2.4. Organisational trust
Present study has used 29 item “organisational trust index”
developed by Shockley-Zalabak, Ellis, and Cesaria (2000) to measure organisational trust of executives. The five dimension scale
was validated by the developers of the scale through carrying out
confirmatory factor analysis. The scale was designed to measure the
trust index through five point Likert type response format (1 ¼ very
little to 5 ¼ great deal) in terms of “how much the statement describes my organisation”. Some of the sample item of the scale
includes: “I am greatly satisfied with the capacity of the organisation to achieve its objectives” (competence); “I can tell my immediate supervisor when things are going wrong” (openness); “My
immediate supervisor speaks positively about subordinates in front
of others” (concern); “My immediate supervisor follows through
with what he/she says” (reliability); “I feel connected with my
organisation” (identification). The present study has obtained 0.82
Cronbach alpha value (a) that is above the prescribed cut-off of 0.70
(Nunnally, 1978).
Utilizing the earlier procedure we have computed the factor
validity of the construct and it has reported: overall cumulative
variance ¼ 69.7% (exceeded 50% with factor loading of each item
exceeded 0.50); KMO ¼ 0.89 (exceeding the recommended level of
0.50); Bartlett's test of sphericity c2 ¼ 1191.28 (p < 0.01) with the
eigenvalue of five dimensions of organisational trust at 6.22, 4.19,
3.85, 3.21, 1.92, 1.24 (exceeded the recommended value of 1.00).
In order to check the psychometric soundness of the major
constructs used in this study we carried out both the construct
validity (convergent and discriminant validity) and reliability of
each constructs. In our study, the convergent validity of all the
factor loadings were greater than 0.5, the p values associated with
the factor loadings were less than 0.05 (significant at 0.5) and the
cross loading also were less than 0.5. Similarly, the discriminant
validity of all the four constructs had the square root of the average
variance more than any of the correlations involving the latent
variables. In addition, the reliability of all the four constructs was
more than 0.7. This verifies that the constructs possess psychometric soundness and can be used for further statistical analysis to
test the hypotheses.
3. Data analysis and results
We have carried out SEM analysis through AMOS 20.0 to
Please cite this article in press as: Jena, L. K., et al., Pursuit of organisational trust: Role of employee engagement, psychological well-being and
transformational leadership, Asia Pacific Management Review (2017), https://doi.org/10.1016/j.apmrv.2017.11.001
L.K. Jena et al. / Asia Pacific Management Review xxx (2017) 1e8
understand the combined measurement/structural model. For
measuring the strength of mediation (to test the indirect effect);
alternative hypothesis testing method proposed by Baron and
Kenny (1986) is generally used. Hayes (2012) argued for including
the bootstrapping technique in addition to the mediation process
through PRODCLIN2 during SEM analysis. The said process has an
advantage over customary approach especially in such cases when
there is an assumption of increase in Type-I errors.
The initial analysis did not have a single factor as the first factor
in our study reckoned 28.3% of variance which is less than the
prescribed 50% (Podsakoff, Mackenzie, Lee, & Podsakoff, 2003). The
two alternative models prescribed by Podsakoff and Organ (1986)
were utilized. The first model was employed as a full model for
controlling the common method. This is used to pack out the items
of the first factor from the three constructs separately before testing
the effect of first factor as a control variable having employee
engagement, psychological well-being, transformational leadership and organisational trust as two separate analysis. The
DR2 ¼ 0.33 (p < 0.01) was achieved for the model whereas, without
the first factor, the full model got a value of R2 ¼ 0.39 (p < 0.01)
containing the original scales of employee engagement, psychological well-being and organisational trust. Similarly in the association among employee engagement, transformational leadership
and organisational trust the obtained DR2 value was 0.24 (p < 0.01)
was achieved, whereas without the first factor, the full model got a
value of R2 ¼ 0.27 (p < 0.01). As the values of R2 and DR2 are much
close, the common method variance is not a major issue in the
study. The significant regression value lends support to our first
hypothesis (H1).
Table 1 presented the mean, S.D., correlation coefficients among
the variables. For examining the possible differences among our
demographic profile chi-square test was carried out. The findings
indicated not much of differences with regard to gender (c2 ¼ 1.91,
p ¼ 0.18) and education (c2 ¼ 0.81, p ¼ 0.39). Fig-2 presented the
achievement of structural model fit (c2/df ¼ 1.84, P < 0.001;
CFI ¼ 0.97, TLI ¼ 0.95, RMSEA ¼ 0.05). The VIF (variance inflation
factor) and tolerance scores were in the range of 1.00e1.18 and 0.91
to 1.00. We have measured the outliers through examining the
Cook's distance (0.00e0.31; at M ¼ 0.02, S. D ¼ 0.03) and the
leverage values (0.01e0.14 at M ¼ 0.02, S. D ¼ 0.03) proving that the
data has maintained required frequencies. The kurtosis value was
ranging from 0.61 to 0.83, followed with skewness at 0.06
to 0.31 and critical ratio (C.R) stretching from 2.27 to 3.16 and
hence there is no defilement of residual suppositions.
In line with the recommendation of Anderson and Gerbing
(1988) we carried out the convergent and discriminant validity of
the measurement model along with its composite reliability (refer
to Table 2). All the constructs had composite reliability more than
0.7, the average variance extracted (AVE) of all the constructs were
more than 0.5 and both the maximum shared variance (MSV) and
average shared variance (ASV) less than the average variance
extracted (AVE). Thus it proves the convergent and discriminant
5
validity of the measurement model. The path coefficients of the
structural model are presented in Fig. 2. The findings from PROCLIN2 and bootstrap method are presented in Table 3 and Table 4
supporting our other two hypotheses (H2 and H3) of our proposed framework respectively.
4. Discussions and implications of the study
The mediation approach of our study was based on Baron and
Kenny (1986) and it was found that both psychological well-being
and transformational leadership were significantly mediating the
causal relationship between employee engagement and organisational trust. The findings are novel in the way that hardly any
research work has ever empirically tested the influence of
employee engagement on organisational trust. The present study
has also investigated the indirect influence of psychological wellbeing and transformational leadership on both employee engagement and organisational trust. The framework on employee
engagement and organisational trust proposed in this paper not
only suggests a new approach for endorsing organisational trust,
but also gives necessary direction for attaining trust maintenance
and continuance.
The findings of the study proved that engagement sets a “clear
connection between employee and organisational performance”,
and providing a better understanding of organisational objectives
(Hughes & Rog, 2008). Organizations witness higher employee
engagement where expected outcomes are clearly communicated
and mutual goal setting exercises are constantly been carried out
(Gallup, 2011). The trust worthy behavior of leaders generates
confidence among subordinates by creating a better engaging work
atmosphere (Wong, Spence-Laschinger, & Cummings, 2010; Hsieh
& Wang, 2015). The trust on leader combined with rational
outcome distribution begets psychological well-being (Albrecht,
2010). The positive interdimensional correlation among transformational leadership, psychological well-being and organisational trust supports the earlier work of Den Hartog and Belschak
(2012) proving that employees' perceiving their leader as ethical
and trust worthy reports more psychological engagement with
their job assignment. Our findings have proved that meaningful
engagement results in positive feelings towards work and organisation, thereby, resulting in achieving employee's psychological
well-being. In the conclusion, Gallup (cited in Lockwood, 2007)
reported that 62 percent of engaged employees reported positive
result on their physical and mental health, specifically impressing
on the fact that higher trustworthiness was culminated because of
their leader's transformational style of functioning.
The first implication of our study is related to the interaction that
we had with senior management during our data collection. Many
of them unanimously agreed to streamline the engagement and
trust factor in their recruitment and selection process, especially
while hiring prospective candidates. We have also found that
Table 2
Convergent and Discriminant Validity of the measurement model.
Table 1
Descriptive statistics, correlation and reliability.
Variables
Mean
S.D
EE
TL
PWB
OT
EE
TL
PWB
OT
3.41
3.26
3.33
3.25
0.51
0.32
0.52
0.26
(0.81)
0.41*
0.34*
0.48*
(0.83)
0.29*
0.37*
(0.81)
0.22*
(0.92)
Note: EE ¼ Employee engagement; TL ¼ Transformational leadership; PWB ¼ Psychological well-being; OT ¼ Organisational trust; The diagonal bold one's are
Cronbach alpha; *p < 0.01 (2 tailed).
Source: Author's findings.
Variables
AVE
MSV
ASV
CR
EE
TL
PWB
OT
0.62
0.68
0.64
0.73
0.54
0.56
0.59
0.67
0.48
0.51
0.52
0.63
0.91
0.94
0.92
0.96
Note: EE ¼ Employee engagement; TL ¼ Transformational leadership; PWB ¼ Psychological well-being; OT ¼ Organisational trust; AVE ¼ Average variance extracted;
MSV ¼ Maximum shared variance; ASV ¼ Average shared variance; CR¼ Composite
reliability.
Source: Author's findings.
Please cite this article in press as: Jena, L. K., et al., Pursuit of organisational trust: Role of employee engagement, psychological well-being and
transformational leadership, Asia Pacific Management Review (2017), https://doi.org/10.1016/j.apmrv.2017.11.001
6
L.K. Jena et al. / Asia Pacific Management Review xxx (2017) 1e8
5. Limitations and scope for future research
PWB
β = .39*
t = 3.21
β = .47**
t = 3.92
β = .38*
t = 3.01
EE
β = .41**
t = 3.82
Engagement and trust are mutually related to one another, as
trust and openness encourages leaders and subordinates to work
jointly in order to explore ideas for solving organisational issues
while promoting individual's psychological well-being. Taking due
care on learning and development of employees and making them
to realize about organisation's concern for their growth and
development may result in developing trust. During our observation with service sector executives we have found that a skilled
employee is happy, productive and engages wholeheartedly for
realizing the company's goal.
Although, the study has made some significant contributions,
however the present research is not devoid of limitations. First, the
variables are grounded on self-report measures and hence might
suffer from common method bias (though, we have taken procedural measures and carried out CMV test in order to counter the
common method bias). Second, the present study has considered
psychological well-being and transformational leadership as an
influencing mechanism between employee engagement and
organisational trust, however exploring interactional variable in
the existing relationship will contribute more clarity to the
construct of organisational trust. Third, the nature of organisation
and sample size can be increased for generalization of the result
findings. Given the proposition that employee engagement is a
strong predictor of organisational trust, future research should
focus on job demands and other HR factors to have a much better
understanding of this construct. Therefore, the scope is much wide
to undertake future studies on exploring several other variables
that remains unaddressed. Finally, experimental research is proposed across organizations to examine engagement interventions
for promoting organisational trust.
OT
β = .53**
t = 4.14
TL
Fig. 2. Structural model results.
Note: Path coefficients: **p < 0.01, *p < 0.5.
Source: Author’s findings.
engaged employees are hopeful, maintain good interpersonal
relationship and exhibit high level of performance. With this understanding, senior management and we have come to a conclusion
to use psychological tests especially case method of analysis of
candidates to understand their will-power and adaptability skill
during recruitment. Secondly, management needs to introduce
dynamic reward and recognition mechanisms in order to extend
intangible support, and career advancement opportunity to increase trust and confidence of employees. Employees having trust
on the leadership structure and organisational mission are likely to
develop the required coping ability. Lastly, HR department needs to
practice transparency while shunning out any kind of nepotism. We
are of the belief that, the transformation of organisational culture
and progressive HR practices will foster amicable relations among
employee and management.
Table 3
Findings of PRODCLIN2, Bootstrapping Methods and corresponding Z scores of effect size: Psychological well-being as mediator between employee engagement and
organisational trust.
Mediator
Psychological well-being
Total effects
Indirect effects
Direct effects
Boot strapping result sc
Mac. Kinnon's
PRODCLIN2a
95% CI
Product of coefficients
Bias corrected at
95% CI
Percentile
95% CI
Lower
Upper
Estimate
Bootstrap S.E
Z Scoreb
Lower
Upper
Lower
Upper
0.13
0.31
0.42
0.17
0.22
0.09
0.02
0.08
3.13
2.84
2.01
0.04
0.03
0.01
0.31
0.11
0.19
0.05
0.01
0.001
0.28
0.16
0.21
a
The interval and zero direct effect indicating full mediation.
Z score >1.96.
c
The results excludes the interval zero for computing total and indirect effect specifying significant mediation.
Source: Author’s findings.
b
Table 4
Findings of PRODCLIN2, Bootstrapping Methods and corresponding Z scores of effect size: Transformational leadership as mediator between employee engagement and
organisational trust.
Mediator
Transformational leadership
Total effects
Indirect effects
Direct effects
Boot strapping resultsc
Mac. Kinnon’s
PRODCLIN2a
95% CI
Product of coefficients
Bias corrected at
95% CI
Percentile
95% CI
Lower
Upper
Estimate
Bootstrap S.E
Z Scoreb
Lower
Upper
Lower
Upper
0.16
0.39
0.51
0.28
0.31
0.14
0.05
0.11
3.57
3.21
2.19
0.04
0.01
0.03
0.38
0.17
0.26
0.05
0.01
0.001
0.36
0.19
0.27
Note: Bootstrap sample ¼ 1000.
a
The interval and zero direct effect indicating full mediation.
b
Z score >1.96.
c
The results excludes the interval zero for computing total and indirect effect specifying significant mediation.
Please cite this article in press as: Jena, L. K., et al., Pursuit of organisational trust: Role of employee engagement, psychological well-being and
transformational leadership, Asia Pacific Management Review (2017), https://doi.org/10.1016/j.apmrv.2017.11.001
L.K. Jena et al. / Asia Pacific Management Review xxx (2017) 1e8
References
Albrecht, S. L. (2010). Handbook of employment engagement: Perspectives, issues,
research and practice. London, England: Edward Elgar.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A
review and recommended two-step approach. Psychological Bulletin, 103(3),
411e423.
Aryee, S., Budhwar, P. S., & Chen, Z. X. (2002). Trust as a mediator of the relationship
between organizational justice and work outcomes: Test of a social exchange
model. Journal of Organizational Behavior, 23(3), 267e285.
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in
social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51(6), 1173e1182.
Bass, B. M. (1997). Does the transactionaletransformational leadership paradigm
transcend organizational and national boundaries? American Psychologist,
52(2), 130e139.
Baumruk, R. (2004). The missing link: The role of employee engagement in business
success. Workspan, 47(11), 48e52.
Clarke, M. C., & Payne, R. L. (1997). The nature and structure of workers’ trust in
management. Journal of Organisational Behaviour, 18, 205e224.
Colquitt, J. A., Scott, B. A., & LePine, J. A. (2007). Trust, trustworthiness, and trust
propensity: A meta-analytic test of their unique relationships with risk taking
and job performance. Journal of Applied Psychology, 92(4), 909e927.
Cook, J., & Wall, T. (1980). New work attitude measures of trust, organizational
commitment, and personal need nonfulfillment. Journal of Occupational Psychology, 53(1), 39e52.
Den Hartog, D. N., & Belschak, F. D. (2012). Work engagement and Machiavellianism
in the ethical leadership process. Journal of Business Ethics, 107(1), 35e47.
DeRue, S. D., Nahrgang, J. D., Wellman, N., & Humphrey, S. E. (2011). Trait and
behavioral theories of leadership: An integration and meta-analytic test of their
relative validity. Personnel Psychology, 64(1), 7e52.
Dickson, M. W., Den Hartog, D. N., & Mitchelson, J. K. (2003). Research on leadership
in a cross-cultural context: Making progress, and raising new questions. The
Leadership Quarterly, 14(6), 729e768.
Dvir, T., Eden, D., Avolio, B. J., & Shamir, B. (2002). Impact of transformational
leadership on follower development and performance: A field experiment.
Academy of Management Journal, 45, 735e744.
Farris, G. F., Senner, E. E., & Butterfield, D. A. (1973). Trust, culture and organisational
behaviour. Industrial Relations, 12, 144e157.
Ferres, N., Connell, J., & Travaglione, A. (2004). Co-worker trust as a social catalyst
for constructive employee attitudes. Journal of Managerial Psychology, 19(6),
608e622.
Franke, F., & Felfe, J. (2011). How does transformational leadership impact employees’ psychological strain? Examining differentiated effects and the
moderating role of affective organizational commitment. Leadership, 7(3),
295e316.
Gallup Consulting. (2011). Employee engagement: What’s your engagement ratio?.
Retrieved
from
http://www.gallup.com/consulting/121535/EmployeeEngagement-Overview- Brochure.aspx.
Garcia, D. (2011). Adolescents’ happiness: The Role of the affective temperament model
on memory and apprehension of events, subjective well-being, and psychological
well-being. Doctoral Dissertation. Gothenburg, Sweden: University of
Gothenburg.
Hayes, A. F. (2012). Process: A versatile computational tool for observed variable
mediation, moderation, and conditional process modeling [White paper]
Retrieved fromwww.afhayes.com/public/process2012.pdf.
Herold, D., Fedor, D., Caldwell, S., & Liu, Y. (2008). The effects of transformational
and change leadership on employees’ commitment to a change: A multilevel
study. Journal of Applied Psychology, 93(2), 346e357.
Hsieh, C. C., & Wang, D. S. (2015). Does supervisor-perceived authentic leadership
influence employee work engagement through employee-perceived authentic
leadership and employee trust? International Journal of Human Resource Management, 26(18), 2329e2348.
Hughes, J. C., & Rog, E. (2008). Talent management: A strategy for improving
employee recruitment, retention and engagement within hospitality organisations. International Journal of Contemporary Hospitality Management, 20(7),
743e757.
Huppert, F. A. (2009). Psychological well-being: Evidence regarding its causes and
consequences. Applied Psychology: Health and Well-being, 1(2), 137e164.
Jena, L. K., & Pradhan, S. (2017). Joy at Work: Initial measurement and validation in
indian context. The Psychologist-manager Journal, American Psychological Association (APA), 20(2), 106e122.
Jiang, H. (2016). Cultivating employee trust: From authenticity, transparency to
engagement. Retrieved August 11, 2017, from http://www.instituteforpr.org/
cultivating-employee-trust-authenticity-transparency-engagement/.
Jones, G. R., & George, J. M. (1998). The experience and evolution of Trust: Implications for cooperation and teamwork. Academy of Management Review, 23(3),
531e546.
Judge, T. A., & Piccolo, R. F. (2004). Transformational and transactional leadership: A
meta-analytic test of their relative validity. Journal of Applied Psychology, 89(5),
755e768.
Jung, D., Yammarino, F. J., & Lee, J. K. (2009). Moderating role of subordinates’ attitudes on transformational leadership and effectiveness: A multi-cultural and
multi-level perspective. Leadership Quarterly, 20(4), 586e603.
7
Kafka, G. J., & Kozma, A. (2002). The construct validity of Ryff’s scales of psychological well-being (SPWB) and their relationship to measures of subjective wellbeing. Social Indicators Research, 57, 171e190. https://doi.org/10.1007/s11205009-9506-x.
Kahneman, D. (1999). Objective happiness. In D. Kahneman, E. Diener, &
N. Schwartz (Eds.), Well-being: The foundations of hedonic psychology. New York,
NY: Russell Sage Foundation.
Katou, A. A. (2013). Justice, trust and employee reactions: An empirical examination
of the HRM system. Management Research Review, 36(7), 674e699.
Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.).
New York, NY: Guilford Press.
Laschinger, H. K. S., & Finegan, J. (2005). Empowering nurses for work engagement
and health in hospital settings. Journal of Nursing Administration, 35(10),
439e449.
Lewis, J., & Weigert, A. (1985). Trust as a social reality. Social Forces, 63(4), 967e985.
Lockwood, N. (2007). Leveraging employee engagement for competitive advantage:
HR’s strategic role. HR Magazine, 52(3), 1e11. Special section.
Mache, S., Vitzthum, K., Wanke, E., Groneberg, D. A., Klapp, B. F., & Danzer, G. (2014).
Exploring the impact of resilience, self-efficacy, optimism and organizational resources on work engagement. 47 pp. 491e500). IOS Press. https://doi.org/
10.3233/WOR 131617.
Macey, W., & Schneider, B. (2008). The meaning of employee engagement. Industrial
and Organizational Psychology: Perspectives on Science and Practice, 1(1), 3e30.
Macey, W. H., Schneider, B., Barbera, K. M., & Young, S. A. (2009). Employee
engagement: Tools for analysis, practice and competitive advantage. London, England: Wiley-Blackwell. https://doi.org/10.1002/9781444306538.
Marlatt, G. A. (2002). Buddhist philosophy and the treatment of addictive behavior.
Cognitive and Behavioral Practice, 9(1), 44e50.
Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of
organisational trust. Academy of Management Review, 20(3), 709e734.
May, D. R., Gilson, R. L., & Harter, L. M. (2004). The psychological conditions of
meaningfulness, safety and availability and the engagement of the human spirit
at work. Journal of Occupational & Organizational Psychology, 77(1), 11e37.
Molero, I., Cuadrado, M. N., & Morales, J. F. (2007). Relations and effects of transformational leadership: A comparative analysis with traditional leadership
styles. The Spanish Journal of Psychology, 10(2), 358e368.
Mondalek, A. (2013). A culture of trust is directly connected to productivity levels.
Business Insider. Retrieved August 12, 2017, from http://www.businessinsider.
com/trust-leads-to-a-more-productive-team-don-peppers-2013-6.
Nelson, B. (2015). Why employee engagement is important. Retrieved August 8, 2017,
from
http://www.dummies.com/business/human-resources/employeerelations/why-employee-engagement-is-important/.
Nunnally, J. C. (1978). Psychometric theory (2nd ed.). New York, NY: McGraw-Hill.
Nyhan, R. C., & Marlowe, H. A. (1997). Development and psychometric properties of
the organisational trust inventory. Evaluation Review, 21(5), 614e635.
Podsakoff, P. M., Mackenzie, S. B., Lee, J. Y., & Podsakoff, N. P. (2003). Common
method biases in behavioral research: A critical review of the literature and
recommended remedies. Journal of Applied Psychology, 88, 879e903.
Podsakoff, P. M., Mackenzie, S. B., Moorman, R. H., & Fetter, R. (1990). Transformational leader behaviors and their effects on followers: Trust in leader,
satisfaction, and organizational citizenship behaviors. The Leadership Quarterly,
1, 107e142.
Podsakoff, P. M., & Organ, D. W. (1986). Self-reports in organizational research:
Problems and prospects. Journal of Management, 12(4), 531e544.
Pradhan, S., & Pradhan, R. K. (2016). Transformational leadership and job Outcomes:
The mediating role of meaningful work. Global Business Review, 17(3S),
173Se185S.
Rich, B. L., Lepine, J. A., & Crawford, E. R. (2010). Job engagement: Antecedents and
effects on job performance. Academy of Management Journal, 53(3), 617e635.
Russell, J. A. (1980). A circumplex model of affect. Journal of Personality and Social
Psychology, 39(6), 1161e1178.
Ryff, C. D. (1989). Happiness is everything, or is it? Explorations on the meaning of
psychological well-being. Journal of Personality and Social Psychology, 57(6),
1069e1081.
Ryff, C. D., & Singer, B. H. (1998). The contours of positive human health. Psychological Inquiry, 9(1), 1e28.
Schaufeli, W. B., & Bakker, A. B. (2004). Job demands, job resources, and their
relationship with burnout and engagement: A multi-sample study. Journal of
Organizational Behavior, 25(3), 293e315.
Schaufeli, W. B., & Bakker, A. B. (2003). Utrecht work engagement scale: Preliminary
manual. The Netherlands: Department of Psychology, Utrecht University.
available from www.schaufeli.com.
Schaufeli, W. B., Salanova, M., Gonzalez-Roma, V., & Bakker, A. B. (2002). The
measurement of engagement and burnout: A two-sample confirmatory factor
analytic approach. Journal of Happiness Studies, 3(1), 71e92.
Schoorman, F. D., Mayer, R. C., & Davis, J. H. (2007). An integrative model of organizational trust: Past, present, and future. Academy of Management Review,
32(2), 344e354.
Shantz, A., & Alfes, K. (2015). Work engagement and voluntary absence: The
moderating role of job resources. European Journal of Work & Organizational
Psychology, 24(4), 530e543.
Shockley-Zalabak, P., Ellis, K., & Cesaria, R. (2000). Measuring organizational Trust:
Feedback manual. Colorado Springs, CO: University of Colorado at Colorado
Springs.
Sitkin, S. B., & Roth, N. L. (1993). Explaining the limited effectiveness of legalistic
Please cite this article in press as: Jena, L. K., et al., Pursuit of organisational trust: Role of employee engagement, psychological well-being and
transformational leadership, Asia Pacific Management Review (2017), https://doi.org/10.1016/j.apmrv.2017.11.001
8
L.K. Jena et al. / Asia Pacific Management Review xxx (2017) 1e8
“remedies” for trust/distrust. Organization Science, 4(3), 367e392.
Sousa-Lima, M., Michel, J. W., & Caetano, A. (2013). Clarifying the importance of
trust in organizations as a component of effective work relationships. Journal of
Applied Social Psychology, 43(2), 418e427.
Tan, H. H., & Tan, C. S. (2000). Toward the differentiation of trust in supervisor and
trust in organization. Genetic, Social, and General Psychology Monographs, 126(2),
241.
Tepper, B. (2000). Consequences of abusive supervision. Academy of Management
Journal, 43(2), 178e190.
Thayer, S. E. (2008). Psychological climate and its relationship to employee
engagement and organisational citizenship behaviour. Retrieved from: http://
www.academia.edu/6709919/Employee_Engagement_and_Organizational_
Effectiveness_The_Role_of_Organizational_Citizenship_Behavior.
Towers Perrin. (2003). Working Today: Understanding what drives employee
engagement. The 2003 Towers Perrin Talent Report. Retrieved April 12, 2016,
from http://www.towersperrin.com/tp/getwebcachedoc?webc¼hrs/usa/2003/
200309/talent_2003.pdf.
Tripathi, P. (2011). Employee well-being: Role of psychological capital. Amity Journal
of Applied Psychology, 2(1), 18e22.
Wah, L. (1999). Making knowledge stick. Management Review, 24e29.
Wofford, J. C., Goodwin, V. L., & Whittington, J. L. (1998). A field study of a cognitive
approach to understanding transformational and transactional leadership. The
Leadership Quarterly, 9(1), 55e84.
Wong, C. A., Spence-Laschinger, H. K., & Cummings, G. G. (2010). Authentic leadership and nurses’ voice behaviour and perceptions of care quality. Journal of
Nursing Management, 18(8), 889e900.
Yang, Y. F. (2012). Studies of transformational leadership in consumer service:
Leadership trust and the mediatingemoderating role of cooperative conflict
management. Psychological Reports, 110(1), 315e337.
Yukl, G. (2012). Leadership in organizations. Englewood Cliffs, NJ: Prentice-Hall.
Lalatendu Kesari Jena is working as Faculty Member-OB & HR in Dept. of Business
Management, Central University of Orissa, India. He has obtained his PhD. from
Dept. of Humanities and Social Science, Indian Institute of Technology, Kharagpur, India through Senior Research Fellowship (SRF), University Grant Commission (UGC), India. He is having more than 12 years of industry experience in HR and has published
articles in several national and international journals. His research interest includes
workplace spirituality, HR effectiveness, employee engagement, performance management, organisational commitment, emotional intelligence and positive psychology.
Sajeet Pradhan is working as Assistant Professor (OB & HR) in International Management Institute, New Delhi. India. He obtained his Ph.D. from Indian Institute of
Technology, Kharagpur, India. He has published research papers in well-known national and international journals. His research interests include transformational leadership, toxic emotions, sexual harassment and abusive supervision.
Nrusingh Prasad Panigrahy is presently working as Jt. Manager-HR. He is having more
than 8 years of experience in handling different facets of human resource management. He has published research papers in well-known national and international
journals. His research interests include workplace well-being, emotional intelligence
and organisational psychology.
Please cite this article in press as: Jena, L. K., et al., Pursuit of organisational trust: Role of employee engagement, psychological well-being and
transformational leadership, Asia Pacific Management Review (2017), https://doi.org/10.1016/j.apmrv.2017.11.001
Revaluate 180 Competitive edge:
• Value-based
• “The difference between success and failure will not be in the formulation of job descriptions and compensation packages…. But with a clear sense of shared mission and values”
• Values transcend categories and fixed labels, are predictive of team performance, and can be aligned with corporate mission statements and visions
• First pillar of Revaluate focuses on individual ‘well-being’ by doing increases productivity and in turn profit
• According to research based on ‘Happy Productive Worker’ principle – when individuals ‘pursue what matters’ they become happier people
• When employees come to work happy and are surrounded by co-workers who have a shared sense of values – research shows these employees will be more engaged thus
• Research indicates that engaged employees produce up to 12% more than those who aren’t happy and engaged
• Hire for engagement and longevity
• This factor is surrounded by how happy employees are in their job. Revaluate’s value corporate training tool highlights this
• “Today, 80% of fortune 100 tout their values publicly – values that too often stand for nothing but a desire to be au courant, or worse still, political correct.”
• At Revaluate180 values are actionable, distinctive and linked to results.
• Through the workshop Revaluate 180 can restructure corporate values
• Promotes DEI (diversity, equality and inclusion)
• Supports both corporations and individuals
Reevaluate 180 over Personality tests
• Personality tests have no correlation to well-being nor productivity
• Awareness of ones personality traits merely helps with behaviour modifications and / or allows one to understand why a colleague or boss behaves a certain way based upon their personality classifications
• Personality assessments do not assist with conflict resolution or with solving complex problems across teams. Whereas values alignment among team members is predictive of job performance because shared values underpin team goals, priorities and objectives
• Personality tests can be discriminatory, sexist and unrealiable
• Whereas value based assessments screen only for value congruence irrespective of race, gender, sexual orientation and mental health
Revaluate 180 over job competency reports
• Job knowledge tests measure a candidate’s technical or theoretical expertise in a particular field and skills’ tests measure both hard and soft skills relevant to the job. However, for an organisation to succeed, skills/talent are critical but information regarding this knowledge and skill base can be easily assessed through the CV, past experiences, and personal recommendations while values are more long-term and can effect overall attrition with an employer. Skills can degrade and be re-trained or sharpened, but values make up who we are and how we may evolve with the changing landscape of an organisation when they are congruent with the mission and vision of the organisation
• Value assessments can recognise engagement and longevity which competency reports fall short of
Revaluate in conjunction with or taking place of integrity tests because:
• Integrity tests provide the employer with valuable information with respect to helping them to avoid hiring dishonest, unreliable, and/or undisciplined people. Yet, integrity tests are looking only at an individual’s misplaced or misguided morals and/or values rather than deciphering the positive aspects of an employees overall character and/or possible repenting and corrections of past negative behaviours.
• Revaluate 180 determines whether prospective employees share or have congruent values to the employer by examining early sorting choices of prospective employees through the VBT prioritization process whereby “ cluster values” in the deck such as honesty, integrity, loyalty, etc could naturally show their level of importance to the employer just in the prospective employee’s sorting choices.
• Also, it’s a better way to see the importance of values related to integrity because social desirability and potential lying is removed from the equation when not asking such direct questions as, for example: have you ever stolen from your employer or would you lie for a co-worker? People tend to answer based upon what they think the employer wants to hear and end up misrepresenting themselves; whereby in its design, VBT eliminates any such limitations.
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/230557790
Universals in the Content and Structure of Values: Theoretical Advances and
Empirical Tests in 20 Countries
Chapter in Advances in Experimental Social Psychology · December 1992
DOI: 10.1016/S0065-2601(08)60281-6
CITATIONS
READS
8,490
22,557
1 author:
Shalom H Schwartz
Hebrew University of Jerusalem
282 PUBLICATIONS 72,666 CITATIONS
SEE PROFILE
Some of the authors of this publication are also working on these related projects:
Values and Motives View project
Research with the Refined Values Theory View project
All content following this page was uploaded by Shalom H Schwartz on 21 October 2017.
The user has requested enhancement of the downloaded file.
View publication stats
The Chimp Paradox by Steve Patters
“The Chimp Model is an incredibly powerful mind management model that can help you become a happy, confident, healthier, and more successful person. The model offers a simplified way of understanding our two thinking brains and how we can learn to use them to the best of our ability.”
Newest book is called The Path Through the Jungle:
A psychological health and well being program to develop resilience and robustness
Doesn’t explicitly mention values.
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/255593558
The Meaning of Employee Engagement
Article in Industrial and Organizational Psychology · March 2008
DOI: 10.1111/j.1754-9434.2007.0002.x
CITATIONS
READS
2,071
32,246
2 authors:
William Macey
Culturefactors
Benjamin Schneider
147 PUBLICATIONS 29,105 CITATIONS
28 PUBLICATIONS 4,686 CITATIONS
SEE PROFILE
SEE PROFILE
Some of the authors of this publication are also working on these related projects:
Service climate View project
Organizational effectiveness View project
All content following this page was uploaded by Benjamin Schneider on 26 September 2015.
The user has requested enhancement of the downloaded file.
Industrial and Organizational Psychology, 1 (2008), 3–30.
Copyright ª 2008 Society for Industrial and Organizational Psychology. 1754-9426/08
The Meaning of Employee Engagement
WILLIAM H. MACEY
Valtera Corporation
BENJAMIN SCHNEIDER
Valtera Corporation and University of Maryland
Abstract
The meaning of employee engagement is ambiguous among both academic researchers and among practitioners
who use it in conversations with clients. We show that the term is used at different times to refer to psychological
states, traits, and behaviors as well as their antecedents and outcomes. Drawing on diverse relevant literatures, we
offer a series of propositions about (a) psychological state engagement; (b) behavioral engagement; and (c) trait
engagement. In addition, we offer propositions regarding the effects of job attributes and leadership as main effects
on state and behavioral engagement and as moderators of the relationships among the 3 facets of engagement.
We conclude with thoughts about the measurement of the 3 facets of engagement and potential antecedents,
especially measurement via employee surveys.
tionship between engagement and profitability through higher productivity, sales,
customer satisfaction, and employee retention.’’ Some practitioners view engagement
as having evolved from prior research on
work attitudes, directly implying that this
newer concept adds interpretive value that
extends beyond the boundaries of those traditions. We agree with this thought and hope
to show why we agree in what follows.
Although compelling on the surface, the
meaning of the employee engagement concept is unclear. In large part, this can be
attributed to the ‘‘bottom-up’’ manner in
which the engagement notion has quickly
evolved within the practitioner community.
This is not an unfamiliar stage in the incremental evolution of an applied psychological construct. Thus, similar to the manner in
which burnout was at first a construct attributed to pop psychology (Maslach, Schaufeli,
& Leiter, 2001) engagement is a concept
with a sparse and diverse theoretical and
empirically demonstrated nomological net—
the relationships among potential antecedents and consequences of engagement as
well as the components of engagement have
The notion of employee engagement is
a relatively new one, one that has been
heavily marketed by human resource (HR)
consulting firms that offer advice on how it
can be created and leveraged. Academic
researchers are now slowly joining the fray,
and both parties are saddled with competing and inconsistent interpretations of the
meaning of the construct.
Casual observation suggests that much of
the appeal to organizational management is
driven by claims that employee engagement
drives bottom-line results. Indeed, at least
one HR consulting firm (Hewitt Associates
LLC, 2005, p. 1) indicates that they ‘‘have
established a conclusive, compelling rela-
Correspondence concerning this article should be
addressed to William H. Macey. E-mail: wmacey@
valtera.com
Address: Valtera Corporation, 1701 Golf Road, Suite
2-1100 Rolling Meadows, IL 60008
William H. Macey, Valtera Corporation; Benjamin
Schneider, Valtera Corporation and University of
Maryland.
We appreciate the thoughtful comments of our colleagues Karen Barbera and Scott Young as well as constructive feedback from Paul Sackett and Allen Kraut.
3
4
not been rigorously conceptualized, much
less studied. Indeed, many HR consultants
avoid defining the term, instead referring only to its presumed positive consequences. At a minimum, the question
remains as to whether engagement is a
unique concept or merely a repackaging
of other constructs—what Kelley (1927;
quoted in Lubinski, 2004, p. 98) called the
‘‘Jangle Fallacy.’’ This is a matter of particular
significance to those who develop and
conduct employee surveys in organizations
because the end users of these products
expect interpretations of the results to be
cast in terms of actionable implications.
Yet, if one does not know what one is measuring, the action implications will be, at
best, vague and, at worst, a leap of faith.
The academic community has been slow
to jump on the practitioner engagement
bandwagon, and empirical research that
has appeared on the topic in refereed outlets
reveals little consideration for rigorously
testing the theory underlying the construct
(for exceptions, see May, Gilson, & Harter,
2004; Salanova, Agut, & Peiro, 2005). Thus,
although research exists demonstrating
that some employee attitudes called ‘‘engagement’’ are related to organizational
outcomes like turnover and productivity
(Harter, Schmidt, & Hayes, 2002) these
employee attitudes do not conceptually
reflect the notion of engagement. Thus,
further development of the construct and
its measurement requires attention (for an
example, see Schaufeli, Bakker, & Salanova,
2006).
Our goal is to present a conceptual framework that will help both researchers and
practitioners recognize the variety of meanings the engagement construct subsumes
and the research traditions that give rise to
or support those meanings. We believe that
this is important in itself as it creates a
working model for how the research literature can influence practice and vice versa.
Thus, as we organize the various literatures
relevant to engagement, we establish a
research agenda that identifies further opportunities for science and improved science–
practice linkages.
W.H. Macey and B. Schneider
Employee Engagement:
Getting Oriented
Numerous definitions of engagement can be
derived from the practice- and researchdriven literatures. Additional definitions
can be attributed to folk theory: the common
intuitive sense that people, and particularly
leaders within organizations, have about
work motivation. Common to these definitions is the notion that employee engagement is a desirable condition, has an
organizational purpose, and connotes
involvement, commitment, passion, enthusiasm, focused effort, and energy, so it has
both attitudinal and behavioral components.1 The antecedents of such attitudes
and behaviors are located in conditions
under which people work, and the consequences are thought to be of value to organizational effectiveness (see Erickson, 2005).
As a folk theory, engagement is used in
a manner that implies the opposite of disengagement. For example, a number of
popular views of engagement suggest that
engaged employees not only contribute
more but also are more loyal and therefore
less likely to voluntarily leave the organization. However, for present purposes, we
choose to focus on only those aspects of
engagement that have positive valence
(obviously from low to high). We believe
that this is crucial to developing conceptual
precision in that it maintains a clear intentional focus on benefits that inure to the
organization. For example, certain behaviors that might be considered adaptive on
the part of the individual (e.g., taking
a ‘‘mental health day’’ as a form of adaptive
withdrawal) would not be considered
within the present framework. At least temporarily, we are not taking a position on
1. Some readers may feel that there are clear hints of
‘‘motivation’’ in what we have just written and wonder to themselves why we are not saying that this is
motivation. The answer is that the construct of motivation is itself a hypothetical construct with considerable ambiguity surrounding it. Were we to introduce
it here, it might further confound the issues so we
leave the chore of integrating engagement with
‘‘motivation’’ to others.
Employee engagement
whether engagement and disengagement
are opposites (i.e., perhaps the opposite of
engagement is ‘‘nonengagement’’ rather
than disengagement or perhaps even burnout; Gonzalez-Roma, Schaufeli, Bakker, &
Lloret, 2006). Rather, we simply choose to
arbitrarily exclude from consideration
models of behavior that focus on withdrawal, maladaptive behavior, or other disengagement phenomena.
Sources of Confusion:
State, Trait, or Behavior?
As a folk term, engagement has been used to
refer to a psychological state (e.g., involvement, commitment, attachment, mood), performance construct (e.g., either effort or
observable behavior, including prosocial
and organizational citizenship behavior
[OCB]), disposition (e.g., positive affect
[PA]), or some combination of the above.
For example, Wellins and Concelman
(2005a, p. 1) suggested that engagement is
‘‘an amalgamation of commitment, loyalty,
productivity and ownership.’’ As we shall
see, the use of engagement as a psychological construct in the research literature is no
more precise; it is commonly used to refer to
both role performance and an affective state,
even within the same research context (for
an exception, see Kahn, 1990).
The reader may recognize that many
other important psychological constructs
have suffered from a similar lack of precision
at early stages in their development. A particularly noteworthy example of such imprecision is job involvement (cf., Kanungo,
1982). Thus, the lack of precision in the
engagement concept does not imply that
the concept lacks conceptual or practical
utility. However, the concept would be more
useful were it to be framed as a model that
simultaneously embraces the psychological
state and the behavior it implies. In the
absence of such a model, including potential
antecedents and moderators, it does not
seem possible to either develop relevant
research hypotheses or apply the concept
in any meaningful way including the
design of surveys and the development of
5
organizational interventions based on survey results.
On a related point, confusion exists
because engagement is used by some to refer
to a specific construct (e.g., involvement,
initiative, sportsmanship, altruism) with
unique attributes and by others as a performance construct defined as exceeding some
typical level of performance. For example,
Wellins and Concelman (2005a, p. 1) suggested that engagement is ‘‘the illusive force
that motivates employees to higher (or
lower) levels of performance.’’ Colbert,
Mount, Harter, Witt, and Barrick (2004,
p. 603) defined engagement in terms of a
‘‘high internal motivational state.’’ Similarly,
Dvir, Eden, Avolio, and Shamir (2002, p. 737)
defined active engagement in terms of ‘‘high
levels of activity, initiative, and responsibility.’’ Again, we see engagement defined both
attitudinally and behaviorally—and we subscribe to both. However, both practitioners
and researchers must be clear about the kind
of engagement they are speaking about. We
will show later the varieties of engagement
constructs that exist. As we will also show,
the various conceptualizations of engagement as state, trait, or behavior, as imprecise
as they may have been, are exceeded in
imprecision only by the various ways this
vague concept has been operationalized.
Toward Untangling the Jangle:
A Framework for Understanding
the Conceptual Space of
Employee Engagement
To move the discussion of what engagement
is to a more concrete level, consider the
overall framework for understanding the
various components that the engagement
construct might subsume (see Figure 1).
Figure 1 shows that engagement as a disposition (i.e., trait engagement) can be
regarded as an inclination or orientation to
experience the world from a particular vantage point (e.g., positive affectivity characterized by feelings of enthusiasm) and that
this trait engagement gets reflected in psychological state engagement. We conceptualize psychological state engagement as an
6
W.H. Macey and B. Schneider
Trait Engagement
State Engagement
Behavioral Engagement
(Positive views of life and work)
(Feelings of energy, absorption)
(Extra-role behavior)
Proactive Personality
Satisfaction (Affective)
Organizational Citizenship Behavior (OCB)
Autotelic Personality
Involvement
Proactive/Personal Initiative
Trait Positive Affect
Commitment
Role Expansion
Conscientiousness
Empowerment
Adaptive
Trust
Work Attributes
Variety
Challenge
Autonomy
Transformational
Leadership
Figure 1. Framework for understanding the elements of employee engagement.
antecedent of behavioral engagement,
which we define in terms of discretionary
effort (e.g., Erickson, 2005; Towers-Perrin,
2003) or a specific form of in-role or extrarole effort or behavior.
Figure 1 also shows that conditions of the
workplace have both direct and indirect
effects on state and behavioral engagement.
The nature of work (e.g., challenge, variety)
and the nature of leadership (especially
transformational leadership) are the conditions that most interest us. Figure 1 shows,
for example, that work has direct effects
on state engagement (e.g., Hackman &
Oldham, 1980) and indirect effects as a
boundary condition (moderator) of the relationship between trait and state engagement. With regard to leadership, Figure 1
shows it having a direct effect on trust and
an indirect effect through the creation of trust
on behavioral engagement (e.g., Kahn, 1990;
McGregor, 1960); more on Figure 1 later.
In our remaining comments, we outline
how various traditions and models within
the research and applied literatures fit the
model shown in Figure 1 and detail the
resulting implications. However, prior to
proceeding, it is important to note that we
do not choose a specific conceptualization
of engagement as ‘‘right’’ or ‘‘true’’ because
(a) this would not be useful at this early stage
in the development of thinking about
engagement; (b) any or all of these conceptualizations can be useful for specific purposes; and (c) identifying these different
conceptualizations will help researchers
and practitioners have a firmer idea about
the locus of the issue when they work with
it. Our goal is to illuminate the unique attributes of prior research that most occupy the
conceptual space we would call engagement so that future research and practice
can more precisely identify the nature of
the engagement construct they are pursuing.
Engagement as Psychological State:
Old Wine in New Bottles?
We begin our exploration of Figure 1 with
engagement as psychological state because
it is the state of engagement that has received
more attention, either implicitly or explicitly, than either of the other perspectives. In
addition, as both dependent and independent variable in Figure 1, it is central to the
engagement issue.
Engagement as a psychological state has
variously embraced one or more of several
related ideas, each in turn representing some
form of absorption, attachment, and/or
enthusiasm. Operationally, the measures of
engagement have for the most part been
composed of a potpourri of items representing one or more of the four different
Employee engagement
categories: job satisfaction, organizational
commitment, psychological empowerment,
and job involvement. We summarize the relevance of each of these to the concept of
engagement. We then review some more
recent thinking about the state of engagement, especially with regard to the affect of
that state. More specifically, it becomes clear
as our review unfolds that thinking and
research about engagement have evolved
to be both more precise and conceptually
appropriate. This clarity reflects an increasing emphasis on absorption, passion, and
affect and a lessening emphasis on satisfaction and perhaps also job involvement and
organizational commitment.
Engagement as satisfaction.
To some,
engagement and satisfaction are linked
directly if not regarded as completely isomorphic. Thus, Harter et al. (2002) explicitly
referred to their measure (The Gallup Work
Place Audit) as ‘‘satisfaction-engagement’’
(p. 269) and defined engagement as ‘‘the
individual’s involvement and satisfaction
with as well as enthusiasm for work’’ (p. 269,
italics added). The Gallup survey items
tap evaluative constructs traditionally conceptualized as satisfaction facets, including
resource availability, opportunities for
development, and clarity of expectations.
Perhaps even more directly, some practitioners (e.g., Burke, 2005) measure engagement as direct assessments of satisfaction
with the company, manager, work group,
job, and work environment characteristics.
Others distinguish between an affective, or
emotional, component of engagement and
rational or cognitive elements, linking the
emotional component to job satisfaction.
Thus, Towers-Perrin (2003) suggested that
‘‘the emotional factors tie to people’s personal satisfaction and the sense of inspiration and affirmation they get from their
work and being part of their organization’’
(p. 4, italics added). The reader may also note
that despite the emphasis on affect in many
definitions of satisfaction (e.g., Locke,
1976), contemporary job satisfaction measures are largely considered descriptive
(Brief & Weiss, 2002). Consider, for exam-
7
ple, the measurement of engagement with
the Gallup measure (Buckingham & Coffman, 1999; Harter et al., 2002) where the
items used to define engagement are all
items descriptive of the conditions under
which people work. The results from survey
data are used to infer that reports of these
conditions signify engagement, but the state
of engagement itself is not assessed—at least
insofar as one accepts our proposed conceptualization as one that connotes passion,
commitment, involvement, and so forth.
Erickson (2005, p. 14) articulated a view
consistent with our thoughts:
Engagement is above and beyond
simple satisfaction with the employment
arrangement or basic loyalty to the
employer—characteristics that most
companies have measured for many
years. Engagement, in contrast, is about
passion and commitment—the willingness to invest oneself and expend one’s
discretionary effort to help the employer
succeed.
Interestingly, many traditional measures
of satisfaction include items that would
seemingly tap facets that fit our conceptual
space for engagement. For example, one
item included in Brayfield and Rothe’s
(1951) measure of job satisfaction reads,
‘‘Most days I feel enthusiastic about my
work.’’ Enthusiasm is regarded as a marker
of engagement by some (e.g., Harter,
Schmitt, & Keyes, 2003), and the relevance
of satisfaction is clear in that people invest
more time in roles they find enjoyable
(Rothbard & Edwards, 2003). Nonetheless,
the conceptual similarity of items used in
engagement and satisfaction surveys indicates confusion between the concepts.
Looking ahead to our later comments, the
lack of conceptual clarity in distinguishing
engagement from satisfaction parallels the
conceptual confusion in understanding the
different uses of the term ‘‘positive affect,’’
where the common use of the term broadly
encompasses the hedonic dimension of
pleasantness, happiness, or cheerfulness
yet is portrayed more accurately when
8
W.H. Macey and B. Schneider
characterizing a high level of activation or
energy and a state of pleasantness.
In fact, the measures of engagement we
have seen in use in the world of practice are
highly similar to the measures used for
assessments of job satisfaction (or climate
or culture), albeit with a new label. Although
there may be room for satisfaction within the
engagement construct, engagement connotes activation, whereas satisfaction connotes satiation (Erickson, 2005). In addition,
although ‘‘satisfaction’’ surveys that ask
employees to describe their work conditions
may be relevant for assessing the conditions
that provide for engagement (state and/or
behavioral), they do not directly tap engagement. Such measures require an inferential
leap to engagement rather than assessing
engagement itself. This has practical significance because the advice the practitioner
offers management on addressing engagement issues requires a similar inferential leap
all too evident to the insightful executive.
A very significant exception to this dismal
portrait is work being done in Europe by
researchers from Holland and Spain (Schaufeli et al., 2006). They have designed and
validated (against customer satisfaction; Salanova et al., 2005) a nine-item measure of
state engagement that defines three factors
that conceptually link to issues we will discuss next: dedication (i.e., commitment),
absorption (i.e., involvement), and energy
(i.e., positive affective state).
Proposition 1 summarizes the points
made with regard to the relationship between satisfaction and engagement:
Proposition 1: Satisfaction when assessed
as satiation is not in the same conceptual
space as engagement. Satisfaction when
assessed as feelings of energy, enthusiasm, and similarly positive affective states
becomes a facet of engagement.
Engagement as commitment.
Some
practitioners define engagement in terms of
organizational commitment. For example,
Wellins and Concelman (2005b, p. 1) suggested that ‘‘to be engaged is to be actively
committed, as to a cause.’’ The Corporate
Executive Board (2004, p. 1) suggested that
engagement is ‘‘the extent to which employees commit to someone or something in their
organization, how hard they work, and how
long they stay as a result of that commitment.’’ In these and similar definitions, two
possible threads of reasoning are implied:
organizational and task/goal commitment;
we deal first with organizational commitment.
Commitment is regarded as a psychological state of attachment (O’Reilly & Chatman,
1986) or binding force between an individual and the organization (Meyer, Becker, &
Vandenberghe, 2004). In fact, the items comprising Meyer and Allen’s (1997) affective
commitment scale focus on the concept of
belonging, personal meaning, and ‘‘being
part of the family’’ (p. 118), and the items
in Mowday, Porter, and Steers’ (1982) measure of organizational commitment define
not only the concept of belonging but also
the additional concepts of effort and pride
(see Items 1 and 6, p. 221). In both cases,
commitment as a psychological state is
regarded as an antecedent of various organizationally relevant outcomes, including various forms of prosocial behavior and/or
organizational/job withdrawal. Based simply on the commonly specified antecedents
and consequences of commitment and state
engagement, affective commitment must be
regarded as a facet of state engagement but
not the same as state engagement. Thus, as
we will show later, there are other facets
or psychological states (e.g., feeling psychologically safe; Kahn, 1990) that make commitment only one of a number of states that
legitimately comprise the full state engagement construct.
It is important to note that the measures of
commitment cited (Meyer & Allen, 1997;
Mowday et al., 1982) are measures of the
psychological state of commitment and are
not descriptions of the conditions that might
yield that commitment. In this sense, they
clearly fit with our approach to the operationalization of engagement as psychological state. By way of summary:
Proposition 2: Organizational commitment is an important facet of the state of
Employee engagement
engagement when it is conceptualized
as positive attachment to the larger organizational entity and measured as a willingness to exert energy in support of the
organization, to feel pride as an organizational member, and to have personal
identification with the organization.
Engagement as job involvement.
At a casual level, job involvement as a construct
clearly occupies a portion of the conceptual
space labeled state engagement. Indeed, as
indicated earlier, Harter et al. (2002) specifically equated engagement with both satisfaction and involvement. Similarly, building
on the work of Lodahl and Kejner (1965),
Cooper-Hakim and Viswesvaran (2005)
defined job involvement ‘‘as the degree to
which an employee psychologically relates
to his or her job and the work performed
therein’’ (p. 244) and specifically equated
job involvement and job commitment. Similarly, in his review and meta-analysis of job
involvement, Brown (1996) indicated that
a ‘‘state of involvement implies a positive
and relatively complete state of engagement
of core aspects of the self in the job’’ (p. 235,
italics added).
Switching now to task engagement and
job commitment, these have been discussed
in the engagement literature albeit in a limited form. Erickson (2005) is one exception
who places the work people do as central to
the state of engagement. In his review of
transformational leadership, Bass (1999)
suggested that when the self-worth of the
individual is involved, higher levels of commitment to the activity (i.e., job or task commitment as opposed to organizational
commitment) follow from increased levels
of task engagement because a lack of commitment to the leader’s goals would be dissonant with the feelings of self-worth that
follow from goal attainment. Self-engagement in this context refers to the willingness
to invest effort toward task goal attainment.
The difference between work as the referent
of engagement and the organization as the
referent of engagement is critical here, and
such a distinction is even more apparent
9
when discussing the relationship between
job involvement and engagement.
As noted earlier, Erickson (2005) described the job as the key antecedent of the
state of engagement, so for her, engagement
or involvement in the task is critical to overall psychological state engagement. The key
referent of engagement here is the job, not
the organization. In addition, it follows that
the logical consequences of involvement
would be with regard to task/job outcomes
and not directly to organizational-level
outcomes.
In this regard, based on a comparison of
his meta-analytic results to those of Mathieu
and Zajac’s (1990) earlier meta-analysis of
organizational commitment relationships,
Brown (1996) concluded that job involvement is an antecedent of organizational
commitment rather than a consequence.
He based his conclusion on the fact that the
relationship between involvement and various work outcomes is typically weak, yet the
relationship between involvement and commitment is quite strong. Brown further
concluded that organizational withdrawal
decisions are less related to job involvement
than to organizational commitment.
As was true for the concept of organizational commitment, job involvement is seen
in contemporary definitions of engagement
as a facet of engagement, a part of engagement but not equivalent to it (Salanova et al.,
2005), and we would agree with this perspective. Within the broader research literature, Maslach et al. (2001) have proposed
that engagement can be characterized by
energy, involvement, and efficacy. As others
have done (e.g., Brown, 1996), these
scholars positioned job engagement as conceptually distinct from organizational commitment because the focus is on work
rather than the organization (much as job
commitment can be regarded as different
from organizational commitment) and as
different from involvement in that engagement is a broader concept encompassing
energy and efficacy. On balance, it seems
appropriate to regard Maslach et al.’s and
Salanova et al.’s views of job engagement
as a broad multidimensional construct
10
W.H. Macey and B. Schneider
encompassing a family of related and more
specific constructs focused on individuals’
relationships with their work roles. By way
of summary:
Proposition 3: Job involvement (including
task engagement and job commitment)
as traditionally conceptualized and assessed is an important facet of the psychological state of engagement.
Engagement as psychological empowerment.
Psychological empowerment has
been treated within both two- and fourdimensional frameworks (Mathieu, Gilson,
& Ruddy, 2006). Within the two-dimensional framework, Mathieu et al. (p. 98) suggested that empowerment is the ‘‘experience
of authority and responsibility.’’ Conceptually, empowerment defined in this manner
might be considered an antecedent or a condition of engagement, and the reader can see
the conceptual slipperiness with which we
are dealing.
Indeed, any distinction between the state
of engagement and psychological empowerment becomes considerably less clear when
considering the four-dimensional model
suggested by Spreitzer (1995). These dimensions include meaning (sense of purpose),
competence (self-efficacy), feelings of selfdetermination (feelings of control), and
impact (belief that one’s efforts can make
a difference). These connote a readiness
and/or an inclination toward action that fits
our perspective of state engagement as energic (see below). Indeed, Spreitzer articulated
the idea that the four cognitions imply an
active way of ‘‘wishing to’’ shape one’s work
role and context, a meaning clearly aligned
with folk conceptualizations of engagement.
In this perspective, the state of feeling
empowered, as represented in an orientation
toward action, would seem to occupy a portion of the conceptual space we would
regard as a state of engagement. Supporting
an interpretation of psychological empowerment as engagement, Spreitzer (1995) suggested that outcomes of empowerment
include effort, persistence, and initiative.
We would include these as indicants of
behavioral engagement, a topic we consider
in detail later.
This discussion of state engagement as
feelings of empowerment leads us to the
following:
Proposition 4: Feelings of empowerment
that connote an inclination to action
vis-à-vis work (feelings of self-efficacy and
control and impact from one’s action) comprise another facet of state engagement.
Summary: State engagement as old wine in
a new bottle.
Job satisfaction, organizational commitment, job involvement, and
feelings of empowerment all can have relevance for the state engagement construct.
The state engagement construct we have
presented to this point in the review is thus
a new blend of old wines with distinct characteristics and ‘‘feel.’’ More specifically,
although aspects of these older constructs
are relevant to state engagement (those connoting affect and feelings of energy), those
facets of the older constructs connoting satiation and contentment are not.
The measurement of these older constructs in practice leaves something to be
desired with regard to the kinds of affect
and sense of energy the state engagement
construct we propose would require. Some
measures of job satisfaction that have been
used to infer engagement are not affective in
nature at all and frequently do not connote or
even apply to a sense of energy but represent
conditions that might promote the state of
engagement (e.g., Harter et al., 2002), a topic
discussed in some detail later.
The next section of the review considers
in greater detail the affective nature of state
engagement. It will become clear to readers
that the state engagement construct is one
comprising not only facets of old wine but
those of new wines, too, with a focus on
affect. As we move further into the world of
affect that engagement connotes, ways in
which the old constructs and measures are
inadequate will become increasingly clear.
What will also become clear is that the state
engagement construct suggests a different
Employee engagement
emphasis than is evident in the independent
discussion of these related constructs in the
traditional industrial–organizational (I–O)
literature.
Engagement as Positive Affectivity (PA).
Engagement has been regarded by some as
a distinct affective state. Larsen and Diener
(1992) positioned PA as halfway between
(45 degrees to) the positive end of the activation dimension and the pleasant end of the
hedonic valence dimension, thus characterizing PA as ‘‘activated pleasant affect’’ (p. 31)
characterized by adjectives that connote
both activation and pleasantness. This distinction between PA with its high activation
component and pleasantness, which is neutral with respect to activation level, is similar
to the one we made earlier when discussing
satisfaction and its relationship to engagement. Although there is considerable
ongoing debate regarding the primary
dimensionality of affect (e.g., Russell &
Carroll, 1999; Watson & Tellegen, 1999),
our concern here is with regard to the
descriptors (markers) used to characterize
PA. PA markers for the Positive and Negative
Affect Schedule (PANAS) include among
others attentive, alert, enthusiastic, inspired,
proud, determined, strong, and active
(Watson, Clark, & Tellegen, 1988, p. 1064),
precisely the kinds of descriptors occasionally explicitly but more often implicitly used
in contemporary engagement definitions.
In keeping with Staw (2004), Larsen and
Diener (1992), Warr (1999), and others,
these markers of PA connote high levels of
activation. This is consistent with the practitioner literature. For example, within the
popular management press, this is referred
to as passion and excitement (Wellins &
Concelman, 2005b) or simply emotional
engagement (Fleming, Coffman, & Harter,
2005).
PA is variously used to describe mood
states, more temporary and intense emotional states, and as a dispositional trait, or
the tendency to experience events, circumstances, and situations more positively
(Thoresen, Kaplan, Barsky, Warren, & de
Chermont, 2003), further adding to the
11
potential confusion. By implication, some
people are dispositionally more prone to
be engaged, but for the present discussion
of states (compared with the later discussion
of traits) that is somewhat irrelevant; we deal
with antecedents of state engagement later.
Most interesting for present purposes is that
in the folk, practitioner, and researchers’
conceptual use of the term, engagement presumes a relatively stable state unlike the
implied ebb and flow of a transient psychological state. That is, engagement is
expected to be relatively constant, given
the continued presence of specific and recognizable job and organizational factors.
In what follows, other models of engagement as an affective state are described,
some more and some less relatively persistent and transient psychological states.
More immediately relevant to state
engagement at work, Schaufeli and his colleagues define engagement as a ‘‘persistent,
positive affective-motivational state of fulfillment in employees that is characterized by
vigor, dedication, and absorption’’ (Maslach
et al., 2001, p. 417). From a measurement
perspective, questionnaire items (Schaufeli,
Salanova, Gonzalez-Roma, & Bakker, 2002;
Schaufeli et al., 2006) tap constructs similar
to involvement and satisfaction but with an
additional emotional, energic, or affective
tone, suggesting a high degree of overlap
with PA: ‘‘I’m enthusiastic about my job’’
and ‘‘I feel happy when I am working
intensely.’’ The important considerations for
present purposes are (a) the distinct characterization of persistence or stability, if not
consistency of experience of that state, and
(b) the elevated emotional tone of the state
itself (Schaufeli et al., 2002).
In a related view, Shirom (2003) suggested the notion of vigor as an affective state
experienced as a response to the characteristics of the job. Shirom defined vigor as an
affective state but not a mood state in that
individuals can attribute their feelings of
vigor specifically to the job and the workplace. He positioned vigor as the feeling of
physical strength, cognitive liveliness, and
emotional energy. Shirom’s measure of vigor
includes items such as ‘‘I feel energetic,’’
12
W.H. Macey and B. Schneider
‘‘I feel I am able to contribute new ideas,’’
and ‘‘I feel able to show warmth to others.’’
Shirom argued, and we agree, that vigor is
not equivalent to engagement behavior,
with the feeling of vigor being a psychological state that, in combination with other positive affective states, can lead to engagement
behavior.
Shirom positioned vigor within the affect
circumplex in a manner similar to though
not perfectly aligned with PA: a mixture of
moderate arousal and moderate pleasantness. Furthermore, his conceptualization of
vigor is entirely consistent with the notion of
engagement as a relatively enduring affective state as presented here. Of particular
importance, he attributed the feeling of vigor
directly to workplace characteristics, especially the job itself. But it is useful to note
that, like Warr (1999), Shirom is explicitly
speaking about state engagement with
regard to work rather than state engagement
as a generic or general psychological state.
Proposition 5: PA associated with the
job and the work setting connoting or
explicitly indicating feelings of persistence, vigor, energy, dedication, absorption, enthusiasm, alertness, and pride
occupies a central position in the conceptualization and measurement of state
engagement. Conversely, measures of
psychological states that are devoid of
direct and explicit indicants of affective
and energic feeling are not measures of
state engagement in whole or part.
One can see in Proposition 5 a summary
of the role of job satisfaction, job involvement, organizational commitment, and
empowerment in understanding state
engagement. Additionally, however, there
are the required importance and centrality
of the energic state and positive affectivity
that are central to the uniqueness of the state
engagement construct.
Engagement as involvement of the self.
In Proposition 5 and the prior discussion
and propositions, the affective feelings and
energic states referred to are with respect to
the job and the organization. Although comprehensive with regard to state engagement,
a significant omission involves feelings with
regard to the involvement of the self: selfesteem, self-efficacy, and self-identity.
Kahn (1990), in an early and especially
insightful exploration of engagement, specifically suggested that ‘‘People can use varying degrees of their selves, physically,
cognitively, and emotionally, in the roles
they perform . . . the more people draw
on their selves to perform their roles . . .
the more stirring are their performances’’
(p. 692). This is highly similar to the definition of involvement provided by Brown
(1996) and cited earlier. Kahn defines personal engagement as ‘‘harnessing’’ of the
individual self with the work role. As such,
engagement is a binding force, similar to
commitment as defined by Meyer et al.
(2004), although Kahn (1990) also refers to
the expression of that self in task behavior.
Thus, the experience of personal engagement encompasses elements of both
involvement and commitment as psychological states and also a sense of personal identity in role behavior.
Kahn (1992) later elaborated on the concept of engagement by implicitly differentiating the notion of psychological presence
and engagement behavior. He suggested
that a true psychological presence at and
identity with work go beyond questions of
simple task motivation. Rather, true identity
with work reflects an ‘‘authenticity’’ that
results in employees connecting with work
and addressing difficult issues (i.e., the
engagement behavior). It is from the experience of being psychologically present in
the work—that the work is a part of one’s
identity—that employee development and
productivity follow. Such behavioral
engagement follows because when psychologically present, employees are attentive
and focused, connected (including the connotation of absorption), and integrated. The
‘‘experience’’ of being integrated would
entail simultaneously drawing upon all of
one’s skills, abilities, and other personal
resources in order to respond to the demands
of a role. Kahn’s (1992) description of
Employee engagement
psychological presence clarifies the distinction between the experiential state (psychological presence) and personally engaging
behaviors that may accompany that state.
Thus, engagement as behavior, a topic we
will move to shortly, is regarded as the manifestation of presence, a psychological state.
Building on Kahn’s view, Rothbard (2001,
p. 684) operationalized engagement through
self-reported attention (e.g., ‘‘I focus a great
deal of attention on my work.’’) and absorption (e.g., ‘‘When I am working, I often lose
track of time.’’).
Proposition 6: State engagement additionally refers to the investment of the self
in the person’s work and the perceived
importance of work outcomes and organization membership to that person’s
identity.
A note on the durability of state engagement.
By definition, psychological states,
like engagement, have boundaries set in
time (Weiss & Kurek, 2003). Different perspectives of engagement as a psychological
state might vary in the limits placed on these
boundaries but (a) time frames are rarely if
ever explicitly referred to in perspectives
related to engagement like those we have
described here, and (b) the previous literatures referred to seem to implicitly assume
a relatively durable engagement state. Thus,
we unfortunately do not yet have either appropriate conceptual boundaries or adequate
operationalization of those boundaries.
Within the notion of a ‘‘mind-set,’’
engagement can be considered a relatively
enduring state and one that serves to explain
persistence as well as direction of job and
organizationally focused behavior. As such,
individual measures of engagement should
be relatively stable, and intra-individual differences would be considered a reflection of
measurement error. However, engagement
can also be represented as a temporary transient state. Here, engagement measures
would be expected to fluctuate, representing
the daily ebb and flow of experiences in
response to the work environment or other
aspects of personal life. Given these distinc-
13
tions, it would seem important for measures
of engagement to bound survey items in
time—perhaps explicitly asking respondents
how often they have specific engagement
feelings and experiences and how long they
persist to provide data on the possible
transient nature versus the durability of the
feelings.
In both conceptualizations, engagement
can be viewed as a causal antecedent of
organizationally relevant behavior and outcomes. Distinguishing the short- and longterm characterizations of state engagement
serves to highlight the observation that either
the focus of engagement must be regarded as
varying in salience over time (if engagement
is a relatively enduring mind-set; see Meyer
et al., 2004) or engagement itself varies.
In either case, a comprehensive engagement
model should provide a theoretical basis for
understanding intra-individual variance in
engagement and/or engagement-related
outcomes. For example, Sonnentag (2003)
demonstrated that engagement (vigor,
absorption, and dedication) varies around
an average or ‘‘trait’’ level (trait here might
be better interpreted as a state with longer
term boundaries) and that significant variation in state engagement can be accounted
for by off-work recovery opportunities. In
a related vein, depletion theories of the effects of multiple-role obligations (Rothbard,
2001) suggest that there is a limited amount
of energy people possess that they can share,
suggesting in turn that engagement in some
roles comes at the expense of engagement in
other roles. Such a view strongly implies
considerable intra-individual variance. We
will not further consider state engagement
in its transient form and will write in what
follows under the assumption that state
engagement is relatively durable over time,
with work and organizational conditions as
well as personal traits (all to be considered
soon) supporting this durability in time.
Summary: Engagement as state.
We have
now reviewed the many ways in which the
psychological state of engagement has been
conceptualized and measured. Although
there is considerable variability in concepts
14
and measures, there appears to be considerable agreement that engagement as a state
has a strong affective tone connoting, at
a minimum, high levels of involvement (passion and absorption) in the work and the
organization (pride and identity) as well as
affective energy (enthusiasm and alertness)
and a sense of self-presence in the work.
Existing measures of the more traditional
concepts of satisfaction, job involvement,
and organizational commitment frequently
contain items referring to affect, energy, and
identity. Therefore, we would expect that
measures designed to tap state engagement
more directly will correlate significantly
with them. To be more precise, we would
expect correlations in the range of .50 among
these measures but further hypothesize that
if such measures are included with the one
designed to specifically tap state engagement
as represented in Propositions 1–6, an oblique factor analysis of the resultant items
would yield an engagement factor that
included the more affective and energic items
and be distinguished from the other items.
Importantly, we do not conceive of a measure of state engagement to be necessarily
incomplete if any facet of engagement as
described in Propositions 1–6 is missing.
Rather, these facets as we have positioned
them and as they have been characterized
in the I–O literature should be regarded as
representative of the affective and energic
aspect of state engagement.
We have carefully argued that the state of
engagement that results in and/or accompanies engagement behavior differs from that
behavior. The separate focus on behavior is
critical as it is key to the distinction between
psychological outcomes that are personally
relevant and those that are organizationally
relevant. These organizational consequences
obviously must emerge from the states being
reflected in engagement behaviors, the topic
to which we turn next.
Engagement as Behavior:
An Introduction
Within our model, engagement can be
regarded as a directly observable behavior
W.H. Macey and B. Schneider
in the work context. Clearly, the scope of
engagement is something less than the entire
domain of behavioral work performance
and thus begs the question as to how it differs
from any other form of performance-related
behavior. To this point, within the folk meaning of the term, engagement implies something special, extra, or at least atypical.
Having said that, it is conceivable that an
entire organization may have behaviorally
engaged employees with the frame of reference being other organizations, and/or
within an organization, some employees
may be engaged more than others—with
other employees within the organization
being the frame of reference.
Thus, it is common to define employee
engagement as putting forth ‘‘discretionary
effort,’’ defined as extra time, brainpower,
and energy (Towers-Perrin, 2003), with the
frame of reference implied but perhaps not
having been made explicit. Others refer to
‘‘giving it their all’’ (Bernthal, 2004), and
some combine effort with commitment in
the definition (e.g., Corporate Executive
Board, 2004; Wellins & Concelman,
2005a) with similarly somewhat ambiguous
frames of reference. A caution then is that the
frame of reference for the measurement of
engagement behaviors be specified.
As to engagement behaviors reflecting
‘‘effort,’’ unfortunately effort has been an elusive and ill-defined construct in the literature. Traditionally, effort has been regarded
as comprising (a) duration, (b) intensity, and
(c) direction (Campbell & Pritchard, 1976;
Kanfer, 1990). Campbell (1990) suggested
‘‘demonstrating effort’’ as one of the dimensions of a taxonomy of performance and
defined the dimension as consistency of performance, maintaining work levels under
adverse conditions, and in other ways,
expending extra effort when required—all
of which speak strongly to the issue of persistence. However, translating the notion of
extra effort into measurement terms has been
a challenge. Brown and Leigh (1996) found
little guidance in the literature regarding
how to measure effort and wrote items to
reflect both time commitment (e.g., ‘‘Other
people know me by the long hours I keep,’’
Employee engagement
p. 367) and work intensity (e.g., ‘‘When I
work, I really exert myself to the fullest,’’
p. 367). Van Scotter and Motowidlo (1996)
measured job dedication, a higher order
dimension of OCB, by gathering supervisory
ratings of employees putting in extra time
and effort as well as demonstrating persistence and initiative.
A construct related to effort is ‘‘role investment’’ (Lobel, 1991; Rothbard & Edwards,
2003), which is typically operationalized in
terms of time spent—again the issue of persistence—performing specific activities.
Rothbard and Edwards demonstrated that
people are more likely to invest their time
in roles that are important to them in terms
of their self-identity, even when the utilitarian value of the investment is held constant.
Thus, consistent with self-concordance theory (Sheldon & Elliot, 1999), people willingly contribute their time when their roles
are consistent with their personal goals and
when they see themselves invested in their
role performance.
From our perspective, it is limiting to
define engagement solely in terms of ‘‘extra
effort,’’ that is, just doing more of what is
usual. Kahn (1990), for example, suggested
that those who are psychologically present
bring more of themselves to their work, transcending typical boundaries in relating to
others and thereby doing something different and not just something more. Similarly,
Brown (1996) suggested that involvement
might lead to both doing things ‘‘smarter’’
and investing greater effort. Thus, highly
engaged employees might exemplify behavior both qualitatively and quantitatively different from those less engaged.
Summary.
The notion of extra effort is
a compelling one in that it implies that
employees possess a reservoir of energy from
which they can draw should they so choose;
organizations that learn how to harness this
potential will likely enjoy distinct competitive advantage. Nonetheless, defining
engagement as ‘‘extra’’ or ‘‘discretionary’’
effort presents a challenge for at least four
reasons. First and most importantly, effort is
not easily defined, and there is little evi-
15
dence of construct validity of corresponding
measures (Brown & Leigh, 1996). Second,
extra effort is an overly limiting view of
engagement if it simply connotes doing
more of the same; what may be most important is doing something different. Third,
‘‘extra’’ or ‘‘atypical’’ implies a reference or
standard that is generally left unspecified.
Fourth, discretion in itself is a complex issue,
leading to ambiguous boundary conditions
on the meaning of engagement. However,
there is more here than simple persistence
or responsiveness to the demands of the
moment. More specifically:
Proposition 7: Engagement behaviors
include innovative behaviors, demonstrations of initiative, proactively seeking
opportunities to contribute, and going
beyond what is, within specific frames of
reference, typically expected or required.
Engagement as Extra-Role Behavior
When we think of engagement behaviors
this way, that is, in terms of the behaviors
that extend beyond typical or expected inrole performance, three major threads of
research are relevant to this notion. These
include OCB and related variants (prosocial
behavior, contextual performance, and
organizational spontaneity; see Organ, Podsakoff, & MacKenzie, 2006), role expansion
and the related constructs of proactive
behavior (Crant, 2000), and personal initiative (Frese & Fay, 2001).
The reader may note that unlike the literature addressing engagement as a psychological state, the relevant literatures we will
now discuss do not use the term engagement. However, it will become clear that
these theoretical and research threads are
directly applicable to our search for an
engagement behavior definition, and we
begin the discussion with OCB.
Engagement as OCB.
Early theoretical
work on OCB emphasized the discretionary
nature of certain behaviors that were
regarded as essential to organizational success but not formally defined as part of the
16
job and therefore not explicitly rewarded.
More recently, conceptual problems have
been discussed in the literature regarding
limiting discretion to extra-role behaviors,
and the working definition of OCB has been
modified to include those behaviors that
support or in some way enhance the social
and psychological environment essential for
individual task performance (Organ, 1997), a
term more closely aligned with the meaning
of contextual performance (LePine, Erez, &
Johnson, 2002). Although the dimensionality
of OCB has recently been questioned, the
original behaviors comprising OCB can be
conceptualized as falling into the larger
themes of support for others, organizational
support, and conscientiousness (Borman,
2004; LePine et al., 2002). Note that the
behaviors falling within the latter category
imply doing ‘‘something extra,’’ a notion consistent with a folk definition of employee
engagement (e.g., ‘‘going the extra mile’’)
and distinct from the notion of simply raised
levels of job facet performance, functional
participation (Van Dyne, Graham, & Dienesch, 1994), self-discipline (Van Scotter &
Motowidlo, 1996), or generalized compliance (LePine et al., 2002).
One conceptual challenge in considering
OCB as engagement (i.e., as doing something extra) arises in addressing the issue of
whether employee engagement refers exclusively to going ‘‘above and beyond.’’ The
significance of the issue resides in the observation that the boundaries between in-role
and extra-role performance are weak at best.
Vey and Campbell (2004), for example, demonstrated that certain forms of OCB (conscientiousness and courtesy) were more likely
to be considered in-role by a panel of survey
respondents with supervisory experience.
Fundamentally, the conceptual issue is
whether the behavior of interest must be discretionary—the person made a choice to do
it—to be considered an example of engaged
behavior. This would require all behaviors to
be evaluated for the degree to which they
involved making a choice to do more, to
do something different, and so forth. We
conclude from an OCB perspective that
engaged behavior is a behavior that, given
W.H. Macey and B. Schneider
specific frames of reference, goes beyond
what is typically or normally displayed or
expected and that attributions about
whether the behavior was discretionary or
not are unnecessary. We acknowledge that
this places a conditional value on such
behaviors—they may be normal or typical
in some circumstances (some groups and
some companies), whereas the same behavior may be unusual in other circumstances.
As we have noted earlier, ‘‘atypical’’ implies
a frame of reference. That frame of reference
may originate in a variety of ways; attempts
here at greater precision are not useful.
For example, Meyer et al. (2004) suggested that under circumstances where failure to perform a task as usual might be
excused because of extraordinary conditions, otherwise in-role behaviors might be
considered extra-role. This implies that certain conditions allow for freedom of choice
as to whether to engage in certain task
behaviors; engagement, as in ‘‘doing something extra,’’ would be considered doing
what is normal when normal conditions do
not apply. However, defining engagement
behavior exclusively in such a manner
would seem limiting in that it begs the question as to the frequency with which opportunities to demonstrate such behaviors arise.
By way of summary, the ‘‘going beyond’’
label associated with the OCB construct is
an attractive one, and we use it as a basis for
defining one facet of engaged behavior as
going beyond the ordinary, yielding:
Proposition 8: Engagement behavior
includes actions that, given a specific
frame of reference, go beyond what is typical, usual, ordinary, and/or ordinarily
expected.
We say that engagement behavior is
inclusive of behaviors normally characterized as OCB, implying that there are other
behaviors that reveal other facets of engagement, and we turn to one of these, role
expansion, next.
Engagement as role expansion.
Role
expansion is not a part of the OCB
Employee engagement
landscape, but it has recently been
addressed as extra-role behavior, and we
see it as another indicant of behavioral
engagement. The choice to perform extrarole tasks can be regarded as role expansion.
Coyle-Shapiro, Kessler, and Purcell (2004),
for example, suggested that an individual
might perform certain behaviors motivated
by the norm of reciprocity, paying back for
having been treated well, whereas another
might simply consider that behavior part of
their job. In either case, of course, the
observer of the same behavior may also
make different attributions about the causes
of it, but it is still seen as a positive behavior.
Once again, it is clear that the definition of
going beyond is a relative one depending
upon the vantage point from which the
behavior emerges, but observers can apparently agree on these behaviors without reference to the attributions they might make
about their causes (Organ et al., 2006).
Morgeson, Delaney-Klinger, and Hemingway (2005) demonstrated that within
homogenous job families, some employees
perform a greater breadth of tasks than others
and found that role breadth was related to
the autonomy accorded to workers as well
as cognitive ability. Conte, Dean, Ringenbach, Moran, and Landy (2005) found that
within a relatively homogenous occupational group (travel agents), organizational
commitment and job satisfaction were both
related to the frequency with which agents
were rated as working at a narrow versus
a wide variety of tasks, the latter revealing
role expansion. Thus, role expansion by definition implies behavior that is atypical in
a comparative sense (or else it would not
be expansion) and has been found to be
related to self-efficacy (Parker, 1998) as well
as autonomy and cognitive ability (Morgeson
et al., 2005). We will have more to say about
the conditions that get reflected in engagement behaviors, both personal conditions
and contextual conditions, later. For now:
Proposition 9: Role expansion, behavior
that reveals attention to a wider range of
tasks than is typical or usual, is a facet of
engagement behavior.
17
Engagement as proactive behavior and
personal initiative.
As mentioned earlier,
Dvir et al. (2002) defined active engagement
(what we are calling behavioral engagement) in terms of initiative as well as activity
and responsibility. Although not referencing
the term engagement, Frese and his colleagues (Frese & Fay, 2001; Frese, Kring,
Soose, & Zempel, 1996) have suggested that
personal initiative comprises three facets:
self-starting, proactivity, and persistence.
Essential to Frese’s viewpoint is that these
three aspects refer to behaviors that go
beyond expectations. Frese and Fay analyzed in considerable detail the logical
issues that surface when discussing expectations and conclude that personal initiative
implies going beyond what is normal or
obvious. As Frese and Fay suggested, this
may vary by level within the organization
and by the organizational context in which
the behavior occurs, so there is again the
issue of the conditional nature on whether
a specific form of engagement behavior will
always be seen as being unexpected, going
beyond, and so forth.
A similar emphasis on proactivity has been
offered by Crant (2000; Bateman & Crant,
1993), Morrison and Phelps (1999; referred
to as ‘‘taking charge’’), and Parker (1998; ‘‘role
breadth self-efficacy’’). Like Frese and Fay
(2001), Crant (2000) emphasized the importance of personal characteristics as well as
situational characteristics as antecedents of
the behavior. Morrison and Phelps (1999)
and Parker (1998, 2003), in contrast, emphasized the importance of situational cues. We
will say more about the dispositional nature
of engagement later as well as conditions
under which they are more likely. For present
purposes, the critical feature of these views
is the common emphasis on proactivity and
initiative compared to role prescriptions as
the behavior of interest.
Morrison and Phelps (1999) specifically
suggested the notion of taking charge as
a means of extending what they viewed to
be an overly narrow interpretation of OCB,
namely, a focus on maintaining the status
quo. In contrast, Morrison and Phelps and
Kahn (1992) emphasized the value of
18
employee-driven change for the success of
the organization. That change can be in
response to something existing or anticipated. What these behaviors share is a common emphasis on adaptation. Importantly,
unlike the notion of adaptive behavior that
has an employee-driven focus (e.g., Miller
and Rosse, 2002), the focus here is on adaptive behavior in response to job and organizational challenges and opportunities. This
is similar in notion to that of LePine and Van
Dyne (2001), although their emphasis was
on voice as a manifestation of ‘‘constructive
change-oriented communication’’ (p. 326).
Viewing engagement as organizationally
focused adaptive behavior is consistent with
the recent increasing emphasis on the
changing nature of work, the dynamic
nature of job roles, and the active nature of
responding to problems and events in the
business environment (e.g., Ilgen & Pulakos,
1999). Here, the emphasis is still on the
choice of behavior, but the behavior of interest has an adaptive and proactive focus.
Thus, this view of employee engagement
might encompass certain dimensions of
adaptive performance as suggested by
Pulakos, Arad, Donovan, and Plamondon
(2000). Also, reflecting the emphasis of Frese
and Fay (2001) on the action orientation of
initiative, it would also seem that an adaptive definition of engagement would more
readily align with nonpassive behaviors,
calling into question whether conscientiousness and courtesy as defined within traditional OCB research would appropriately
be considered components of engagement.
Interestingly, the common interpretation of
engagement suggests that those behaviors
that are more likely regarded as passive
(e.g., conscientiousness; Parks & Kidder,
1994) may also be more likely to be considered in-role than extra-role (Vey & Campbell, 2004).
Thus, engagement as adaptive behavior is
a useful concept for describing a range of
behaviors that support organizational effectiveness. What is common is the fundamental notion that engagement behaviors are
discretionary (not prescribed) in that they
go beyond preserving the status quo and
W.H. Macey and B. Schneider
instead focus on initiating or fostering
change in the sense of doing something more
and/or different, whether in response to
a temporary condition or a more permanent
solution to a perceived existing organizational challenge. Engagement behavior
viewed this way is clearly an aggregate multidimensional construct, in the sense that
contextual performance (Motowidlo, 2000)
and OCB (Organ et al., 2006) are also multidimensional in nature. However, the
emphasis here is not on all behavior that
contributes to the social, psychological, or
organizational functioning of the organization. Rather, the emphasis is on those behaviors that represent responses (or anticipatory
responses) to organizational challenges:
doing more of what needs to be done, changing what needs to be changed, and/or actively
resisting change to the status quo when that
change would result in diminished organizational effectiveness. In other words, average
task performance does not (typically) define
engagement; coming to work on time does
not (typically) define engagement; and doing
what one’s boss expects one to do does not
(typically) define engagement.
The notion of engagement as adaptive
behavior is entirely consistent with Kahn’s
positioning of psychological presence and
its behavioral manifestation as engagement
behavior. Specifically, Kahn (1992) emphasized the adaptive requirements of modern
organizations, suggesting that the competitive business environment requires individuals who direct their efforts to reflecting on
what is necessary to create change so that
their organizations can be increasingly competitive and effective.
A fundamental aspect of our positioning
of behavioral engagement is that it is strategically focused and is bounded by purpose
and organizational relevance.
Proposition 10: Behavioral engagement
is adaptive behavior intended to serve
an organizational purpose, whether to
defend and protect the status quo in
response to actual or anticipated threats
or to change and/or promote change in
response to actual or anticipated events.
Employee engagement
Summary.
Behavioral engagement, like
state engagement, has numerous facets to
it. Behavioral engagement is simultaneously
citizenship behavior (OCB), role expansion,
proactive behavior, and demonstrating personal initiative, all strategically focused in
service of organizational objectives. Many
of the facets reviewed and comprising
behavioral engagement contain the notion
of ‘‘going beyond the usual or typical’’ and,
as such, imply a frame of reference for such
judgments. Frames of reference can be other
individuals, other groups/teams, and/or
other organizations so that the members
of groups and organizations can be said
to demonstrate behavioral engagement.
Behavioral engagement has to do with performances that are adaptive and innovative
and in that sense not usual or typical, and the
behavioral engagement construct as we
have defined it has not been captured well
by the individual constructs that comprise
our definition. To more fully understand
these affective and behavioral dimensions
of engagement, it is useful to consider potential antecedents of these, and it is to such
consideration we turn next.
Antecedents of State and
Behavioral Engagement
We have shown to this point that there are
a variety of ways to conceptualize and
measure both state and behavioral engagement. This explication of the various constructs offers researchers frames from which
they can pursue additional work, for example, the relationships existing among the
various kinds of adaptive behaviors and/or
the various facets of state and behavioral
engagement we have explicated. It also
offers practitioners a conceptual foundation on which to base decisions when conducting engagement projects, especially
the design of the so-called engagement
surveys.
But neither state nor behavior engagement springs forth whole; both are obviously
dependent for their existence on still more
variety, this time variety in the personal
attributes of those who are engaged and the
19
conditions under which they work. So,
although it is easy to state that people who
have passion for their work are more likely to
engage in adaptive behaviors, it is more difficult to state why some people have passion
for their work and others do not and why in
some organizations passion characterizes
employees, whereas in other organizations
it does not.
In what follows, we first consider the
attributes of individuals that might yield state
and behavioral engagement, including how
such individual attributes might interact with
conditions encountered in the workplace to
produce engagement. Then, we detail the
main issues that have been discussed as the
work conditions necessary for engagement
to exist.
Engagement as a
Dispositional Construct
Within our structure depicted in Figure 1,
engagement can be regarded as a disposition, either as a personality characteristic
or more generally as a tendency to experience state affect over time. Additionally,
certain dispositional constructs have been
suggested as causal factors in proactive
behavior, personal initiative, and the experience of ‘‘flow.’’ Four threads of research are
relevant to the notion of trait engagement,
and we address each in turn.
PA as trait engagement.
The conceptual
similarity of PA markers to the meaning of
engagement was highlighted earlier in our
discussion of engagement as an affective
state. In fact, trait PA would be a precise definition of the engaged person (i.e., energetic,
enthusiastic). PA as a trait, or enduring tendency to experience PA as state, has been
broadly considered in the organizational
behavior literature. Although PA has been
explored as a dispositional component of
job satisfaction, trait job satisfaction would
seemingly be more appropriately defined in
terms of the hedonic dimension of the affect
circumplex (Larsen, Diener, & Lucas, 2002).
Specifically, satisfaction or well-being judgments can be regarded as a function of
20
pleasant affect experiences at work (Brief &
Weiss, 2002).
Our reading of this perspective suggests
that PA would be considered more an indicator of trait engagement than trait satisfaction. Staw (2004) noted that items included
in PANAS are weighted to include those with
an activation component (e.g., enthusiastic
and attentive) rather than evaluative in tone
(i.e., happy, cheerful, pleased). A matter of
considerable confusion in the literature is
that PA is associated with feelings of ‘‘enthusiasm and excitement and not with happiness’’ (Huelsman, Furr, & Nemanick, 2003,
p. 658). Again, within that theoretical framework, satisfaction and engagement would
be correlated but not equivalent. Trait
engagement (i.e., trait PA) would serve as
a predisposition to frame organizational
experiences and determine how the individual behaves in response to those experiences
(Larsen et al., 2002; Weiss, 2002).
It is worth noting that our logic that trait
PA is more relevant to engagement than to
satisfaction also suggests that state engagement would be a stronger correlate of what
we have called adaptive behaviors than
would job satisfaction. Thus, one of the central accomplishments of researchers who
study OCB and similar constructs was showing that satisfaction is in fact related to
behavior. Our logic suggests that an even
stronger correlate of such adaptive behaviors
would be measures of state engagement.
Proactive personality as trait engagement.
As indicated earlier, Crant (2000) suggested
that proactive behavior is a product of both
dispositional and situational factors. Characterizing proactive personality as the general tendency to create or influence the
work environment, Crant (1995) demonstrated that this kind of personality is correlated with sales success of real estate
professionals; other studies have indicated
significant relationships between the proactive personality and career success (Seibert,
Kramer, & Crant, 2001). Moreover, Crant
(1995) found that proactive personality
accounted for variance in performance even
after considering the effects of both Consci-
W.H. Macey and B. Schneider
entiousness and Extraversion (or trait PA in
Big Five terms).
Conscientiousness as trait engagement.
Roberts, Chernyshenko, Stark, and Goldberg (2005) investigated the hierarchical
structure of conscientiousness as represented in major personality questionnaires
and identified the proactive aspects of
conscientiousness to include both industriousness and order. The former would
be characterized by individuals who are
‘‘hard working, ambitious, confident, and
resourceful’’ (p. 119). Viewed through a
proactive lens, it would be expected that
conscientiousness would correlate with
measures of contextual performance, especially generalized compliance as a facet of
OCB, as was demonstrated in a meta-analysis
by Organ and Ryan (1995).
Autotelic personality as trait engagement.
The state of psychological engagement,
encompassing the notion of ‘‘flow’’ or ‘‘being
present,’’ has also been investigated in relation to the ‘‘autotelic’’ personality. The autotelic personality refers to people who engage
in activities for their own sake rather than for
specific gains or rewards. Csikszentmihalyi
and his colleagues (see Nakamura &
Csikszentmihalyi, 2002, for a review) have
operationalized the autotelic personality in
terms of the Jackson Personality Research
Form factors of Sentience, Understanding,
Achievement, and Endurance, reasoning
that autotelic individuals should be open
to new challenges, persist in challenging
tasks, and be ready to engage, factors that
contribute to arriving at and maintaining
a state of flow.
Summary and partial integration.
There
are clear points of view suggesting that state
engagement and engagement behaviors are
at least partially the result of dispositional
influences. More directly, research on PA,
the proactive personality, conscientiousness, and the autotelic personality suggests
that trait engagement can be construed as
a broad dispositional construct and that
the markers of that construct are entirely
Employee engagement
consistent with conventional definitions of
engagement (i.e., passion and activation).
Moreover, this view suggests that those more
likely to experience feelings of engagement
and who demonstrate engagement behaviors are also more likely to choose the environments that provide the opportunity to do
so (e.g., Holland, 1997; Schneider, 1987;
Schneider, Goldstein, & Smith, 1995). That
is, consistent with the interpretation of
engagement as adaptive behavior, engaged
employees both select and proactively work
to create the environment in which these
behaviors will be encouraged and supported. Our proposition with regard to trait
engagement is therefore offered as:
Proposition 11: Trait engagement comprises a number of interrelated facets,
including trait positive affectivity, conscientiousness, the proactive personality,
and the autotelic personality. These all
suggest the tendency to experience work
in positive, active, and energic ways and
to behave adaptively (i.e., displaying
effort by going beyond what is necessary
and initiating change to facilitate organizationally relevant outcomes).
Importantly, as shown in Figure 1, we
conceptualize trait engagement as more
likely distal than proximal causes of engagement behavior (Kanfer, 1990). George
(1991), for example, demonstrated that
mood PA but not trait PA predicted prosocial
behavior. Frese and Fay (2001) similarly
highlighted the distal impact of such personality variables on personal initiative behaviors
and further suggested that such personality
characteristics influence orientations and
feelings (e.g., self-efficacy) and only then, in
turn, behavior. Thus, it is likely that dispositional engagement interacts with situational
factors to determine engagement state and/or
behavior, and we turn to a consideration of
those situational characteristics now.
The Situation and Engagement
Much of the early work on engagement
placed the task as central to engagement
21
(Kahn, 1990, 1992). For some (e.g., Erickson,
2005), the attributes of tasks are still the key
issue for promoting engagement. Not surprisingly, reference is made to the job characteristics research program (Hackman &
Oldham, 1980) and work on the intrinsic
nature of rewards (i.e., the intrinsic nature
of tasks; Gagne & Deci, 2005) for specification of some of the issues that drive passion,
commitment, involvement, and so forth.
Interestingly, although the task is central, it
is the degree to which the person can implement his or her preferred self in the work that
is key—but certain characteristics of tasks
like autonomy, challenge, and variety seem
to have main effects for most people.
In addition to the task itself, the conditions surrounding working have been a target
of practice and research. For example, in the
Gallup research program (emerging from
many consulting projects; see Harter et al.,
2003), a series of 12 key work conditions
was identified, which, when present, were
correlated with unit performance—the inference being that when these work conditions
existed, employees demonstrated engagement behaviors that resulted in the improved
unit performance. These conditions are very
diverse, referring among other conditions to
attributes of the work, the boss, the availability of resources, coworkers, and career progress issues. Gallup researchers deduced,
however, that there was an overriding issue,
management and the degree to which managers made these things happen was key to
having a productive work unit. Having this
insight resulted in an additional set of
research efforts to understand what differentiated effective and ineffective managers,
especially with regard to scores those managers received on the 12 items when their
employees were surveyed. A central answer
was the following: Effective managers are
those who get the work done with the people
they have, do not try to change them, and
attempt to capitalize on the competencies
their people have, not what they, the managers, wished they had (Buckingham &
Coffman, 1999).
What is clear from the Gallup research is
that units that score more highly on the 12
22
W.H. Macey and B. Schneider
items have superior performance in terms of
productivity, customer satisfaction, revenues, and turnover. However, the state and/
or behavioral engagement that these 12
items result in is not clear. But research on
transformational leadership helps understand these relationships.
The relevant literature on transformational leadership provides examples of
engagement state and behavior that closely
align with conventional conceptualizations
of engagement, including an investment of
identity in the organization and work such
that there is a sense of passion for work as
well as the capacity to think independently,
develop new ideas, and challenge convention when no longer relevant (e.g., Bass &
Avolio, 1990; Dvir et al., 2002). Indeed, Dvir
et al. demonstrated that under transformational leadership conditions, soldiers will
engage in behaviors not in their personal
best interest, which the authors described
as self-sacrifice.
Proposition 12: State and behavioral
engagement are more likely under some
conditions than others with the nature of
the work people do and the leadership
under which they work central to their
choosing to be attitudinally and behaviorally engaged.
Some of the reasons why these conditions seem to create state and behavioral
engagement have now been made clear.
Psychologically, it appears to follow that
when people have certain kinds of work to
do (e.g., the work has challenge, variety,
and autonomy) and when they work under
certain kinds of managers (e.g., the managers make expectations clear, are fair, and
recognize superior behavior), they feel
engaged and behave in adaptive and constructive ways that produce results that
were perhaps unexpected. Note that the literature on perceived organizational support would also be relevant here (Rhoades
& Eisenberger, 2002).
Central to the network of antecedent conditions is trust. Engaged employees invest
their energy, time, or personal resources,
trusting that the investment will be rewarded
(intrinsically or extrinsically) in some meaningful way. The fundamental motivation for
this may be instrumental based upon the
norm of reciprocity (Coyle-Shapiro & Conway, 2005) or social identity (Moorman &
Byrne, 2005). For example, Hui, Lee, and
Rousseau (2004) found in a Chinese sample
of employed MBA students that instrumentality mediated the relationship between
relational contract obligations and five forms
of OCB. As the authors suggested, this supports the view that employees reciprocate on
the basis of an anticipated reward, whether
concrete or abstract. This suggests that the
important distinction may be between those
demonstrated behaviors that are performed
for more explicit and clearly defined contingencies and those that are based on more
open-ended expectations, where some
degree of trust is implied and strict regulation
of behavior is unnecessary.
It logically follows from this line of reasoning that trust (in the organization, the
leader, the manager, or the team) is essential
to increasing the likelihood that engagement
behavior will be displayed. Trust becomes
important even for intrinsically motivated
behavior, as the conditions that contribute
to the investment of self require what Kahn
(1990) identified as psychological safety.
This is the belief people have that they will
‘‘not suffer for their personal engagement’’
(p. 708). One example of punishment for
extending oneself is ‘‘job creep,’’ where ‘‘discretionary contributions (such as OCB)
become viewed as in-role obligations by
supervisors and peers’’ (Van Dyne & Ellis,
2004, p. 184). Job creep does not yield trust,
so it does not yield engagement behaviors.
A second example would be performing
above the norms of a group and then being
socially punished as a rate buster.
Proposition 13: Feelings of trust mediate
the relationship between leadership
behavior and behavioral engagement
such that feelings of trust is the psychological state between leader behavior and
behavioral engagement. Thus, leaders
create trust in followers, and it is the trust
Employee engagement
followers experience that enables behavioral engagement.
Person–Environment Fit Issues and
Engagement
Implicitly, the discussion of trait engagement
and the conditions under which state and
behavioral engagement are more likely
leads to the thought that perhaps the traits
and the conditions interact, and we consider
that issue now. For example, building on
self-concordance theory (Sheldon & Elliot,
1999), self-determination theory (Ryan &
Deci, 2000), and self-concept–based theory
(Shamir, House, & Arthur, 1993), Bono and
Judge (2003) equated self-engagement with
‘‘engagement with their work,’’ suggesting
that employees who see their work as consistent with their personal values will be
more engaged. This clearly infers the notion
of fit as the determinant rather than either the
individual attribute or the environment
alone as causal.
In the frameworks of self-concordance
and self-determination theories, motivation
(and, by extension, work motivation) reflects
a continuum ranging from complete external
motivation to complete internal or intrinsic
motivation. When the goals of the organization (or leader) and the goals of the individual are entirely consistent, it follows that the
level of employee state engagement will be
higher and that a variety of adaptive behaviors are likely to be displayed.
Kahn (1990, 1992) in particular saw the
interaction of the individual and the organization as central to issues of both state and
behavioral engagement. He noted that it is
when people can use their preferred selves in
their work that they experience being
engaged by that work (state engagement)
and also perform to their fullest capacities
(behavioral engagement). Kahn did not identify the dimensions of self that might be preferred, but he did indicate that these include
interests, values, and competencies. For
Kahn, the work itself is the focus of engagement, for it is the attributes of the work with
which the preferred self is seen as interacting; Kahn (1992) called this psychological
23
presence as we noted earlier, clearly suggesting that such presence emerges as a function of the interaction of the person’s
attributes and the work he or she does.
There is strong evidence to indicate that
the organization itself, especially its goals
and values, can also be a source of attachment and commitment that lead people to
identify with the organization as a whole
and, in turn, to display adaptive behaviors
consistent with its long-term interests. Earlier
called ‘‘organizational identification’’ (cf. Hall
& Schneider, 1973) and later identificationbased commitment (O’Reilly & Chatman,
1986) and affective commitment (Meyer &
Allen, 1997), the key issue here is the fit of
personal values to organizational values.
Organizational identification, then, is a specific form of organizational commitment in
that it implies identity fit or identity matching,
a key issue in definitions of what the engaged
person might experience.
We pursue this issue of fit in some detail
because it has not characterized the research
on engagement. In brief, engagement practice and research might best be called
‘‘main effects’’ research—implying that if
certain specific conditions are appropriately
altered, employee engagement will follow. It
may be more complex in that when a specific
combination of people and conditions
exists, what results is more a product of the
two than a simple addition. That said, we
offer the following by way of summary:
Proposition 14: Trait engagement interacts with work and organizational conditions to produce state and behavioral
engagement. Alternatively, work conditions not only have a main effect on state
and behavioral engagement, but they also
may moderate the relationships between
trait engagement and state engagement as
well as relationships between state and
behavioral engagement (see Figure 1).
Summary Thoughts on the
Engagement Construct
The picture we have painted of engagement
comprises a complex nomological network
24
encompassing trait, state, and behavioral
constructs, as well as the work and organizational conditions that might facilitate state
and behavioral engagement. Although
engagement may at best fit what Law, Wong,
and Mobley (1998) described as a profile
model of a multidimensional construct, we
see engagement as not only a set of constructs but also a tightly integrated set, interrelated in known ways, comprising clearly
identifiable constructs with relationships to
a common outcome. In what follows, first
we review our position as to why we believe
that psychological engagement differs conceptually from other relevant constructs. We
follow with specific conclusions and recommendations for research and practice.
We proposed that state engagement concerns PA associated with the job and the
work setting connoting or explicitly indicating feelings of persistence, vigor, energy,
dedication, absorption, enthusiasm, alertness, and pride. As such, state engagement
has components of organizational commitment, job involvement, and the positive
affectivity components of job satisfaction.
Thus, we would predict that measures of
state engagement and these older constructs
would be significantly related. In addition to
the positive feelings noted, state engagement
also includes the sense of self-identity people have with the work they do; work is a part
of how they define themselves and that in
which they are personally invested.
We focused extensively on which conceptualizations of job satisfaction occupy
common conceptual space with state
engagement. In our view, state engagement
is characterized by feelings of passion,
energy, enthusiasm, and activation. This
reflects both the common folk wisdom
of the concept and the markers used to
reflect feelings of PA/high activation when
describing either trait or mood states (see
Warr, 1999). Although correlated with engagement, satisfaction is sufficiently characterized by a sense of well-being and
pleasantness connoting at best moderate
levels of activation or energy. It is the sense
of energy and enthusiasm in engagement
that makes the construct different, and this
W.H. Macey and B. Schneider
is what executives wish to capture. This
implies that survey questions directed at satisfaction, whether global or facet, have a misplaced emphasis. Questions such as ‘‘How
satisfied are you with the company you work
for?’’ do not measure engagement.
We proposed that behavioral engagement follows from state engagement and further that it is most broadly defined as
adaptive behavior. Adaptive behavior is
a useful concept for describing a range of
behaviors that support organizational effectiveness. What is common is the fundamental notion that engagement behaviors are
typically not prescribed and that they go
beyond preserving the status quo and
instead focus on initiating or fostering
change in the sense of doing more and/or
something different. There are obvious references in our conceptualization of engagement behaviors to existing constructs such
as OCB and role expansion, but we had
a specific emphasis on proactive and personal initiative kinds of behaviors, leading
to our use of the label ‘‘adaptive’’ to summarize our position.
We acknowledged that what is normal
task behavior under some circumstances,
for example, everyday working conditions,
may be seen as engaged behavior under
other circumstances, for example, during
Katrina or other disasters and challenges.
So we finessed the specific behaviors that
characterize engaged behavior and assume
that under specific conditions there will be
agreement on what it is.
We proposed that trait engagement
comprises a number of interrelated personality attributes, including trait positive
affectivity, conscientiousness, the proactive personality, and the autotelic personality. These all suggest the inclination to
experience work in positive, active, and
energic ways and to behave adaptively in
displaying effort at going beyond what is
necessary and initiating change to facilitate organizationally relevant outcomes.
In these senses, trait engagement would
be a significant cause of and be directly
related to state engagement and indirectly
to behavioral engagement.
Employee engagement
Our conceptualization extended to work
and organizational conditions that might
enhance (moderate) these proposed relationships and to ways those same conditions
might directly facilitate and encourage state
and behavioral engagement. Doing work
that has positive motivational attributes
(Hackman & Oldham, 1980) and the presence of a transformational leader who
behaves fairly and engenders trust (Kahn,
1990, 1992) were the two conditions on
which we mostly focused. Thus, we would
hypothesize as shown in Figure 1 that (a) job
design attributes would directly affect state
engagement, (b) the presence of a transformational leader would directly affect state
engagement, and (c) the presence of a transformational leader would directly affect trust
levels and, thus, indirectly affect behavioral
engagement.
Thus, we think of engagement as having
some cost in the form of risk to the
employee. Our view is that organizations
must promote a sense of trust that employees will benefit from the psychological and
behavioral relational contracts in which
they enter with the organization. Promoting
a sense of psychological safety (Kahn,
1990; May et al., 2004) and emphasizing
fairness and other antecedents of trust may
be critical to the development of an engaged workforce.
What we have not previously discussed is
the idea that, to at least some degree, there
are limits on the pool of energy and resources available to employees for state engagement on the one hand and behavioral
engagement on the other hand; sustained
levels of engagement will be difficult to
achieve. As Kahn (1992) suggested, psychological presence can be draining in terms of
the personal level of effort required, which,
depending on other demands on the individual, may not always be possible to sustain.
This is not to say that job satisfaction or other
forms of work attitudes we have considered
are invariant but rather that psychological
presence, activation, extra behavioral
energy, and the like represent an investment
on the part of the employee; satisfaction
presumes nothing of that kind. This is yet
25
a further characteristic that distinguishes
satisfaction and engagement.
Organizations, then, can have some, but
not complete, control over the competition
for people’s resources. Thus, Sonnentag
(2003) demonstrated the positive impact of
off-work recovery on engagement, but
Maslach et al. (2001) implied that very high
levels of engagement can cause burnout. At
the same time, there is some evidence that
behavioral engagement in one role may contribute to higher levels of engagement in
other roles (Rothbard, 2001), perhaps implicating the importance of dispositional factors in determining (a) cross-situational
consistency and (b) the degree to which high
levels of engagement yield positive versus
negative outcomes for people and their
behavior.
Consideration of trait engagement here
implies a critical link between interventions
focused on the early stages of the employment period (i.e., ‘‘on-boarding’’) and other
management-driven activities that relate to
the development of state and behavioral
engagement at work. Thus, we would further
hypothesize that dispositional (trait) engagement is a more significant determinant of
behavioral and psychological engagement
earlier than later in the employment life
cycle.
Relatedly, engagement may be a consequence of both environmental conditions
and dispositional characteristics and their
interaction. Not all investments in job design
and/or the training and performance management of leaders in organizations with
the goal of improving engagement levels will
be productive for all employees. We briefly
discussed this notion of the contingencies
under the heading of person–environment
fit and suggested that values fit in particular
might contribute to both state and behavioral engagement.
Summary Thoughts on
Engagement Measurement
From both research and practice perspectives, it is one thing to get the conceptualization correct and another thing to get the
26
operationalization correct. Most of the
engagement measures we have seen failed
to get the conceptualization correct, so the
measures do not, if you will, measure up (for
exceptions, see Salanova et al., 2005;
Schaufeli et al., 2002). Especially in the
world of practice, we have seen measures
of what we have called conditions for
engagement labeled as measures of engagement (Buckingham & Coffman, 1999), and
many measures used for years as indicators
of employee opinions have been relabeled
as indicants of employee engagement. The
latter has been true especially with measures of job satisfaction where there is little
indication of affect, energy, passion, and
so forth. As we noted earlier, any measure
that asks how satisfied an employee is with
conditions at or of work or asks about the
presence of particular conditions of or at
work is not a measure of any of the three
facets of the engagement construct we have
elucidated.
In a recent edited volume, Kraut (2006)
presented a number of chapters that are
instructive with regard to the measurement
of engagement. For example, Macey and
Schneider (2006) proposed that careful conceptualization of constructs precedes any
operationalization, and they distinguish
among other things generic employee attitudes (job satisfaction) and behavior (OCB)
from strategically focused attitudes (customer orientation) and behavior (customerfocused engagement behaviors). Schiemann
and Morgan (2006) carefully delineated in
their article the issue of assessing strategically focused employee attitudes if the goal
is to provide information for use as a basis for
making change to achieve those goals. The
conclusion from these articles is to focus
the measurement on the construct of interest; if engagement is the target, ensure that
the measure maps the content of the
construct.
In another chapter, Harter and Schmidt
(2006) used evidence they previously presented as indicating engagement correlates
with unit performance and treated the data
as if they indicated job satisfaction correlates
with unit performance—which is the same
W.H. Macey and B. Schneider
measure with which they had assessed work
conditions but inferred engagement as noted
earlier in discussion of the article of Harter
et al. (2002). This highlights the point that to
some, the concepts are indeed interchangeable. We agree with them that the unit of
analysis in employee survey and behavior
research and practice has been at the individual level of analysis and that it is time to
add additional levels of analysis to the
research repertoire. The Gallup research
they reported is all at the unit level of analysis; they and others (e.g., Schneider, White,
& Paul, 1998) continued to show that such
a change in the level of analysis reveals the
usefulness of employee survey data to managers in terms with which they empathized.
Conclusions
In a world that is changing both in terms of
the global nature of work and the aging of the
workforce (Erickson, 2005), having engaged
employees may be a key to competitive
advantage. This will be especially true if we
can show how the engagement construct
produces effects at levels of analysis of concern to management. As with all good
things, the challenge of establishing the conditions for state and behavioral employee
engagement will be great. Once again, there
seems to be no silver bullet. The beauty of
this conclusion is that companies that get
these conditions right will have accomplished something that competitors will find
very difficult to imitate. It is easy to change
price and product; it is another thing to
create a state and behaviorally engaged
workforce.
References
Bass, B. M. (1999). Two decades of research and development in transformational leadership. European
Journal of Work and Organizational Psychology,
8, 9–32.
Bass, B. M., & Avolio, B. (1990). Transformational leadership development: Manual for the Multifactor
Leadership Questionnaire. Palo Alto, CA: Consulting Psychologist Press.
Bateman, T. S., & Crant, J. M. (1993). The proactive
component of organizational behavior: A measure
and correlates. Journal of Organizational Behavior,
14, 103–118.
Employee engagement
Bernthal, P. (2004). Measuring employee engagement.
Retrieved May 4, 2005, from www.ddiworld.com/
pdf/ddi_MeasuringEmployeeEngagement_wp.pdf
Bono, J. E., & Judge, T. A. (2003). Self-concordance at
work: Toward understanding the motivational
effects of transformational leaders. Academy of
Management Journal, 46, 554–571.
Borman, W. C. (2004). The concept of organizational
citizenship. Current Directions in Psychological
Science, 13, 238–241.
Brayfield, A. H., & Rothe, H. F. (1951). An index of job
satisfaction. Journal of Applied Psychology, 35,
307–311.
Brief, A. P., & Weiss, H. M. (2002). Organizational
behavior: Affect in the workplace. Annual Review
of Psychology, 53, 279–307.
Brown, S. P. (1996). A meta-analysis and review of organizational research on job involvement. Psychological Bulletin, 120, 235–255.
Brown, S. P., & Leigh, T. W. (1996). A new look at psychological climate and its relationship to job
involvement, effort, and performance. Journal of
Applied Psychology, 81, 358–368.
Buckingham, M., & Coffman, C. (1999). First, break all
the rules. New York: Simon & Schuster.
Burke. (2005). Employee engagement. Retrieved
May 4, 2005, from www.burke.com/EOS/prac_
EmployeeEngagement.htm
Campbell, J. P. (1990). Modeling the performance
prediction problem in industrial and organizational psychology. In M. D. Dunnette & L. M.
Hough (Eds.), Handbook of industrial and organizational psychology (2nd ed., Vol. 1, pp. 687–
732). Palo Alto, CA: Consulting Psychologists
Press.
Campbell, J. P., & Pritchard, R. D. (1976). Motivation
theory in industrial and organizational psychology.
In M. D. Dunnette (Ed.), Handbook of industrial and
organizational psychology (pp. 63–130). Chicago:
Rand-McNally.
Colbert, A. E., Mount, M. K., Harter, J. K., Witt, L., &
Barrick, M. R. (2004). Interactive effects of personality and perceptions of the work situation on workplace deviance. Journal of Applied Psychology, 89,
599–609.
Conte, J. M., Dean, M. A., Ringenbach, K. L., Moran, S. K.,
& Landy, F. J. (2005). The relationship between work
attitudes and job analysis ratings: Do rating scale
type and task discretion matter? Human Performance, 18, 1–21.
Cooper-Hakim, A., & Viswesvaran, C. (2005). The
construct of work commitment: Testing an integrative framework. Psychological Bulletin, 131,
241–259.
Corporate Executive Board. (2004). Driving performance and retention through employee engagement. Retrieved September 13, 2005, from www.
corporateleadershipcouncil.com/Images/CLC/PDF/
CLC12KADBP.pdf
Coyle-Shapiro, J. A. M., & Conway, N. (2005). Exchange
relationships: Examining psychological contracts
and perceived organizational support. Journal of
Applied Psychology, 90, 774–781.
Coyle-Shapiro, J. A. M., Kessler, I., & Purcell, J. (2004).
Exploring organizationally directed citizenship
behavior: Reciprocity or ‘‘It’s my job?’’ Journal of
Management Studies, 41, 85–106.
27
Crant, J. M. (1995). The proactive personality scale and
objective job performance among real estate agents.
Journal of Applied Psychology, 80, 532–537.
Crant, J. M. (2000). Proactive behavior in organizations.
Journal of Management, 26, 435–462.
Dvir, T., Eden, D., Avolio, B. J., & Shamir, B. (2002).
Impact of transformational leadership on follower
development and performance: A field experiment.
Academy of Management Journal, 45, 735–744.
Erickson, T. J. (2005). Testimony submitted before the
U.S. Senate Committee on Health, Education, Labor
and Pensions, May 26.
Fleming, J. H., Coffman, C., & Harter, J. K. (2005). Manage your human sigma. Harvard Business Review,
83, 106–115.
Frese, M., & Fay, D. (2001). Personal initiative (PI): An
active performance concept for work in the 21st century. In B. M. Staw & R. M. Sutton (Eds.), Research in
organizational behavior (Vol. 23, pp. 133–187).
Amsterdam: Elsevier Science.
Frese, M., Kring, W., Soose, A., & Zempel, J. (1996).
Personal initiative at work: Differences between East
and West Germany. Academy of Management Journal, 39, 37–63.
Gagne, M., & Deci, E. L. (2005). Self-determination theory and work motivation. Journal of Organizational
Behavior, 26, 331–362.
George, J. M. (1991). State or trait: Effects of positive
mood on prosocial behaviors at work. Journal of
Applied Psychology, 76, 299–307.
Gonzalez-Roma, V., Schaufeli, W. B., Bakker, A. B., &
Lloret, S. (2006). Burnout and work engagement:
Independent factors or opposite poles? Journal of
Vocational Behavior, 68, 165–174.
Hackman, J. R., & Oldham, G. (1980). Work redesign.
Reading, MA: Addison-Wesley.
Hall, D. T., & Schneider, B. (1973). Correlates of organizational identification as a function of career
pattern and organizational type. Administrative
Science Quarterly, 17, 340–350.
Harter, J. K., & Schmidt, F. L. (2006). Connecting
employee satisfaction to business unit performance.
In A. I. Kraut (Ed.), Getting action from organizational surveys (pp. 33–52). San Francisco: JosseyBass.
Harter, J. K., Schmidt, F. L., & Hayes, T. L. (2002).
Business-unit-level relationship between employee
satisfaction, employee engagement, and business
outcomes: A meta-analysis. Journal of Applied Psychology, 87, 268–279.
Harter, J. K., Schmidt, F. L., & Keyes, C. L. (2003).
Well-being in the workplace and its relationship
to business outcomes: A review of the Gallup
studies. In C. L. Keyes & J. Haidt (Eds.), Flourishing:
The positive person and the good life (pp. 205–
224). Washington, DC: American Psychological
Association.
Hewitt Associates LLC. (2005). Employee engagement.
Retrieved April 29, 2005, from http://was4.hewitt.com/
hewitt/services/talent/subtalent/ee_engagement.htm
Holland, J. L. (1997). Making vocational choices: A theory of vocational personalities and work environments. Odessa, FL: Psychological Assessment
Resources.
Huelsman, T. J., Furr, R. M., & Nemanick, R. C. (2003).
Measurement of dispositional affect: Construct validity and convergence with a circumplex model of
28
affect. Educational and Psychological Measurement, 63, 655–673.
Hui, C., Lee, C., & Rousseau, D. M. (2004). Psychological contract and organizational citizenship behavior
in China: Investigating generalizability and instrumentality. Journal of Applied Psychology, 89,
311–321.
Ilgen, D. R., & Pulakos, E. D. (1999). Employee performance in today’s organizations. In D. R. Ilgen &
E. D. Pulakos (Eds.), The changing nature of work
performance: Implications for staffing, motivation,
and development (pp. 1–20). San Francisco:
Jossey-Bass.
Kahn, W. A. (1990). Psychological conditions of personal engagement and disengagement at work.
Academy of Management Journal, 33, 692–724.
Kahn, W. A. (1992). To be fully there: Psychological
presence at work. Human Relations, 45, 321–349.
Kanfer, R. (1990). Motivation theory and industrial/organizational psychology. In M. D. Dunnette & L. M.
Hough (Eds.), Handbook of industrial and organizational psychology (2nd ed., Vol. 1, pp. 75–170). Palo
Alto, CA: Consulting Psychologists Press.
Kanungo, R. N. (1982). Measurement of job and work
involvement. Journal of Applied Psychology, 67,
341–349.
Kelley, T. L. (1927). Interpretation of educational measurements. New York: World Book.
Kraut, A. I. (Ed.). (2006). Getting action from organizational surveys. San Francisco: Jossey-Bass.
Larsen, R. J., & Diener, E. (1992). Problems and promises
with the circumplex model of emotion. Review of
Personality and Social Psychology, 13, 25–59.
Larsen, R. J., Diener, E., & Lucas, R. E. (2002). Emotion
models, measures, and individual differences. In
R. G. Lord, R. J. Klimoski, & R. Kanfer (Eds.), Emotions in the workplace (pp. 64–106). San Francisco:
Jossey-Bass.
Law, K. S., Wong, C. S., & Mobley, W. H. (1998). Toward
a taxonomy of multidimensional constructs. Academy of Management Review, 23, 741–755.
LePine, J. A., Erez, A., & Johnson, D. E. (2002). The
nature and dimensionality of organizational citizenship behavior: A critical review and meta-analysis.
Journal of Applied Psychology, 87, 52–65.
LePine, J. A., & Van Dyne, L. (2001). Voice and cooperative behavior as contrasting forms of contextual
performance: Evidence of differential relationships
with Big Five personality characteristics and
cognitive ability. Journal of Applied Psychology,
86, 326–336.
Lobel, S. A. (1991). Allocation of investment in work
and family roles: Alternative theories and implications for research. Academy of Management
Review, 16, 507–521.
Locke, E. A. (1976). The nature and causes of job
satisfaction. In M. D. Dunnette (Ed.), Handbook
of industrial and organizational psychology (pp.
1297–1349). Chicago: Rand-McNally.
Lodahl, T. M., & Kejner, M. (1965). The definition and
measurement of job involvement. Journal of Applied
Psychology, 49, 24–33.
Lubinski, D. (2004). Introduction to the special section
on cognitive abilities: 100 years after Spearman’s
(1904) ‘‘‘general intelligence,’ objectively determined and measured.’’ Journal of Personality and
Social Psychology, 78, 96–111.
W.H. Macey and B. Schneider
Macey, W. H., & Schneider, B. (2006). Employee experiences and customer satisfaction: Toward a framework for survey design with a focus on service
climate. In A. I. Kraut (Ed.), Getting action from organizational surveys (pp. 53–75). San Francisco:
Jossey-Bass.
Maslach, C., Schaufeli, W. B., & Leiter, M. P. (2001). Job
burnout. Annual Review of Psychology, 52, 397–
422.
Mathieu, J. E., Gilson, L. L., & Ruddy, T. M. (2006).
Empowerment and team effectiveness: An empirical
test of an integrated model. Journal of Applied Psychology, 91, 97–108.
Mathieu, J. E., & Zajac, D. M. (1990). A review and
meta-analysis of the antecedents, correlates and
consequences of organizational commitment.
Psychological Bulletin, 108, 171–194.
May, D. R., Gilson, R. L., & Harter, L. M. (2004). The
psychological conditions of meaningfulness, safety
and availability and the engagement of the human
spirit at work. Journal of Occupational and Organizational Psychology, 77, 11–37.
McGregor, D. M. (1960). The human side of enterprise.
New York: McGraw-Hill.
Meyer, J. P., & Allen, N. J. (1997). Commitment in the
workplace: Theory, research and application. Thousand Oaks, CA: Sage.
Meyer, J. P., Becker, T. E., & Vandenberghe, C. (2004).
Employee commitment and motivation: A conceptual analysis and integrative model. Journal of
Applied Psychology, 89, 991–1007.
Miller, H. E., & Rosse, J. G. (2002). Emotional reserve
and adaptation to job dissatisfaction. In J. M. Brett &
F. Drasgow (Eds.), The psychology of work: Theoretically based empirical research (pp. 205–231).
Mahwah, NJ: Erlbaum.
Moorman, R. H., & Byrne, Z. S. (2005). How does organizational justice affect organizational citizenship
behavior? In J. Greenberg & J. A. Colquitt (Eds.),
Handbook of organizational justice (pp. 355–380).
Mahwah, NJ: Erlbaum.
Morgeson, F. P., Delaney-Klinger, K., & Hemingway,
M. A. (2005). The importance of job autonomy, cognitive ability, and job-related skill for predicting role
breadth and job performance. Journal of Applied
Psychology, 90, 399–406.
Morrison, E. W., & Phelps, C. C. (1999). Taking charge at
work: Extra-role efforts to initiate workplace change.
Academy of Management Journal, 42, 403–419.
Motowidlo, S. J. (2000). Some basic issues related to
contextual performance and organizational citizenship behavior in human resource management. Human Resource Management Review, 10,
115–126.
Mowday, R. T., Porter, L. W., & Steers, R. M. (1982).
Employee-organization linkages: The psychology
of commitment, absenteeism, and turnover. New
York: Academic Press.
Nakamura, J., & Csikszentmihalyi, M. (2002). The concept of flow. In C. R. Snyder & S. J. Lopez (Eds.),
Handbook of positive psychology (pp. 89–105).
New York: Oxford University Press.
O’Reilly, C. A., & Chatman, J. A. (1986). Organizational
commitment and psychological attachment: The
effects of compliance, identification, and internalization of prosocial behavior. Journal of Applied Psychology, 71, 492–499.
Employee engagement
Organ, D. W. (1997). Organizational citizenship behavior: It’s construct cleanup time. Human Performance, 10, 85–97.
Organ, D. W., Podsakoff, P. M., & MacKenzie, S. B.
(2006). Organizational citizenship behavior: Its
nature, antecedents, and consequences. Thousand
Oaks, CA: Sage.
Organ, D. W., & Ryan, K. (1995). A meta-analytic
review of attitudinal and dispositional predictors of
organizational citizenship behavior. Personnel Psychology, 48, 775–802.
Parker, S. K. (1998). Enhancing role breadth selfefficacy: The roles of job enrichment and other
organizational interventions. Journal of Applied
Psychology, 83, 835–852.
Parker, S. K. (2003). Longitudinal effects of lean production on employee outcomes and the mediating role
of work characteristics. Journal of Applied Psychology, 88, 620–634.
Parks, J. M., & Kidder, K. L. (1994). ‘‘Till death do us
part.’’: Changing work relationships in the 1990s.
In C. L. Cooper & D. M. Rousseau (Eds.), Trends
in organizational behavior (Vol. 1, pp. 111–136).
Chichester, UK: Wiley.
Pulakos, E. D., Arad, S., Donovan, M. A., & Plamondon,
K. E. (2000). Adaptability in the workplace: Development of a taxonomy of adaptive performance.
Journal of Applied Psychology, 85, 612–624.
Rhoades, L., & Eisenberger, R. (2002). Perceived organizational support: A review of the literature. Journal
of Applied Psychology, 87, 698–714.
Roberts, B. W., Chernyshenko, O. S., Stark, S., & Goldberg, L. R. (2005). The structure of conscientiousness: An empirical investigation based on seven
major personality questionnaires. Personnel Psychology, 58, 103–139.
Rothbard, N. P. (2001). Enriching or depleting? The
dynamics of engagement in work and family roles.
Administrative Science Quarterly, 46, 655–684.
Rothbard, N. P., & Edwards, J. R. (2003). Investment in
work and family roles: A test of identity and utilitarian motives. Personnel Psychology, 56, 699–730.
Russell, J. A., & Carroll, J. M. (1999). On the bipolarity of
positive and negative affect. Psychological Bulletin,
125, 3–30.
Ryan, R. M., & Deci, E. L. (2000). Self-determination
theory and the facilitation of intrinsic motivation,
social development, and well-being. American Psychologist, 55, 68–78.
Salanova, M., Agut, S., & Peiro, J. M. (2005). Linking
organizational resources and work engagement to
employee performance and customer loyalty: The
mediation of service climate. Journal of Applied Psychology, 90, 1217–1227.
Schaufeli, W. B., Bakker, A., & Salanova, M. (2006). The
measurement of work engagement with a short
questionnaire: A cross-national study. Educational
and Psychological Measurement, 66, 701–716.
Schaufeli, W. B., Salanova, M., Gonzalez-Roma, V., &
Bakker, A. B. (2002). The measurement of engagement and burnout: A two sample confirmatory factor
analytic approach. Journal of Happiness Studies, 3,
71–92.
Schiemann, W. A., & Morgan, B. S. (2006). Strategic
surveys: Linking people to business strategy. In
A. I. Kraut (Ed.), Getting action from organizational
surveys (pp. 76–101). San Francisco: Jossey-Bass.
29
Schneider, B. (1987). The people make the place. Personnel Psychology, 40, 437–453.
Schneider, B., Goldstein, H. A., & Smith, D. B. (1995).
The ASA framework: An update. Personnel Psychology, 48, 747–773.
Schneider, B., White, S. S., & Paul, M. C. (1998). Linking
service climate and customer perceptions of service
quality: Test of a causal model. Journal of Applied
Psychology, 83, 150–163.
Seibert, S. E., Kramer, M. L., & Crant, J. M. (2001). What
do proactive people do? A longitudinal model linking proactive personality and career success. Personnel Psychology, 54, 845–874.
Shamir, B., House, R. J., & Arthur, M. B. (1993). The
motivational effects of charismatic leadership: A
self-concept based theory. Organization Science,
4, 577–594.
Sheldon, K. M., & Elliot, A. J. (1999). Goal striving, need
satisfaction and longitudinal well-being: The selfconcordance model. Journal of Personality and
Social Psychology, 76, 482–497.
Shirom, A. (2003). Feeling vigorous at work? The
construct of vigor and the study of positive affect in
organizations. In D. Ganster & P. L. Perrewe (Eds.),
Research in organizational stress and well-being
(Vol. 3, pp. 135–165). Greenwich, CN: JAI Press.
Sonnentag, S. (2003). Recovery, work engagement, and
proactive behavior: A new look at the interface
between nonwork and work. Journal of Applied Psychology, 88, 518–528.
Spreitzer, G. M. (1995). Psychological empowerment in
the workplace: Dimensions, measurement, and validation. Academy of Management Journal, 38,
1442–1465.
Staw, B. M. (2004). The dispositional approach to job
attitudes: An empirical and conceptual review. In
B. Schneider & D. B. Smith (Eds.), Personality and
organizations (pp. 163–192). Mahwah, NJ: Erlbaum.
Thoresen, C. J., Kaplan, S. A., Barsky, A. P., Warren, C. R.,
& de Chermont, K. (2003). The affective underpinnings of job perceptions and attitudes: A metaanalytic review and integration. Psychological
Bulletin, 129, 914–945.
Towers-Perrin. (2003). Working today: Understanding
what drives employee engagement. Stamford, CT:
Author.
Van Dyne, L., & Ellis, J. B. (2004). Job creep: A reactance
theory perspective on organizational citizenship
behavior as over-fulfillment of obligations. In J. A. M.
Coyle-Shapiro, L. M. Shore, M. S. Taylor, & L. E.
Tetrick (Eds.), The employment relationship: Examining psychological and contextual perspectives
(pp. 181–205). Oxford, UK: Oxford University
Press.
Van Dyne, L., Graham, J. W., & Dienesch, R. M. (1994).
Organizational citizenship behavior: Construct
redefinition, measurement, and validation. Academy of Management Journal, 37, 765–802.
Van Scotter, J. R., & Motowidlo, S. J. (1996). Interpersonal facilitation and job dedication as separate facets of contextual performance. Journal of Applied
Psychology, 81, 525–531.
Vey, M. A., & Campbell, J. P. (2004). In-role or extra-role
organizational citizenship behavior: Which are we
measuring? Human Performance, 17, 199–135.
Warr, P. (1999). Well-being and the workplace. In
D. Kahneman, E. Diener, & N. Schwarz (Eds.),
30
Well-being: The foundations of hedonic psychology
(pp. 392–412). New York: Russell-Sage.
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of
positive and negative affect: The PANAS scales.
Journal of Personality and Social Psychology, 54,
1063–1070.
Watson, D., & Tellegen, A. (1999). Issues in the dimensional structure of affect—Effects of descriptors,
measurement error, and response formats: Comment on Russell and Carroll (1999). Psychological
Bulletin, 125, 601–610.
Weiss, H. M. (2002). Deconstructing job satisfaction:
Separating evaluations, beliefs and affective experi-
View publication stats
W.H. Macey and B. Schneider
ences. Human Resource Management Review, 12,
173–194.
Weiss, H. M., & Kurek, K. E. (2003). Dispositional influences on affective experiences at work. In M. R.
Barrick & A. M. Ryan (Eds.), Personality at work
(pp. 121–149). San Francisco: Jossey-Bass.
Wellins, R., & Concelman, J. (2005a). Creating a culture
for engagement. Workforce Performance Solutions
(www.wpsmag.com). Retrieved July 19, 2005, from
www.ddiworld.com/pdf/wps_engagement_ar.pdf
Wellins, R., & Concelman, J. (2005b). Personal engagement: Driving growth at the see-level. Retrieved
April 29, 2005, from www.ddiworld.com/pdf/ddi_
personalengagement_ar.pdf
23/05/2022, 14:27
Top Performers Have a Superpower: Happiness
MAGAZINE SPRING 2022 ISSUE • RESEARCH FEATURE
Top Performers Have a Superpower:
Happiness
A large-scale study found that well-being predicts outstanding job performance.
Paul B. Lester, Ed Diener, and Martin Seligman • February 16, 2022
The toll that working through the global pandemic has taken on employees’ job satisfaction and
emotional well-being has focused business leaders on fostering workforce happiness as never
before. While many — if not most — of us are motivated by genuine caring for the people who
READING TIME: 15 MIN
The Research
• The researchers followed nearly 1
million U.S. Army service members
power our organizations, we also intuitively know that employee happiness should boost job
for five years, measuring their
performance. Still, two nagging questions remain: Which comes first, succeeding and then being
using 25 questions drawn from
happy, or being happy and then succeeding? And just how much does initial happiness matter?
The results of our recent research, published in the Journal of Happiness Studies, have gotten us
one big step closer to answering those two questions. For our study, we followed almost 1 million
U.S. Army soldiers for nearly five years. We first asked them to rate their well-being — their
relative happiness and optimism
PANAS and the Life Orientation Test.
The questions were included on a
larger survey taken by every Army
soldier each year.
• This well-being measurement
combines individuals’ own selfassessments and their reporting on
happiness, if you will — along with their optimism, and then tracked which soldiers later received
the frequency of positive and
awards based on their job performance. We collected our data in the midst of the wars in Iraq and
yield the researchers’ measure of
Afghanistan, so the stakes were high: Some of those awards were for exemplary assigned job
performance, while others were earned for extraordinary performance in heroic actions. Receiving
negative emotions experienced, to
happiness.
• Even after the researchers controlled
for previous performance and a
an award in the Army, either for exemplary job performance or for heroism, is a relatively rare
range of demographic factors,
event. Of the nearly 1 million soldiers in our sample, only 12% received an award of any type during
most optimistic went on to earn
the five years that we ran the study.
While we expected that well-being and optimism would matter to performance, we were taken
soldiers who were the happiest and
significantly more job performance
awards across the next five years
compared with those who were
initially unhappy and pessimistic.
aback by just how much they mattered. We saw four times as many awards earned by the initially
happiest soldiers (upper quartile) compared with those who were unhappiest initially (lower
quartile) — a huge difference in performance between those groups. This gap held when we
accounted for status (officers versus enlisted soldiers), gender, race, education, and other
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/
1/5
23/05/2022, 14:27
Top Performers Have a Superpower: Happiness
demographic characteristics.1 In fact, happiness — and, to a somewhat lesser extent, optimism —
were better predictors of awards than any demographic factor we examined.
You might dismiss these results if you believe that military data somehow doesn’t apply to the
business world, but you would be wrong to do so. After all, the U.S. Department of Defense is the
single largest employer in the world, dwarfing Walmart by nearly 1 million employees. It has nearly
$3 trillion in total assets (compared with Walmart’s $236 billion) and maintains over $290 billion in
inventory (compared with Walmart’s $44 billion). The U.S. military is not just “big business”; it is, in
fact, the biggest business by an order of magnitude, so what we learn from the military can and
often does apply to the business world. There are over 190 distinct job categories in the Army —
from clerk to pilot, cook to commander — and most were included in our data.
In short, not only do happiness and optimism matter to employee performance, but they matter a
lot, and both predict how well employees will do. Our military research, along with other behavioral
science research spanning the past 40 years, highlights the competitive advantage that employee
happiness offers businesses. There are some things about employee happiness that every
business leader should know and be able to apply. And, as we emerge from a demoralizing global
pandemic, we would all do well to take stock of how to influence the happiness and optimism of
those around us in the workplace.
That raises the question, what really is happiness? The behavioral science literature often refers to
happiness as subjective well-being because the meaning of happiness varies in different contexts.
As with most concepts that emerge from psychology, definitions vary, but when it comes to
happiness, they generally coalesce around three areas: a person’s own assessment of their
satisfaction with life; how much positive emotion (such as enjoyment, enthusiasm, inspiration, or
pride) they experience; and how little negative emotion (such as hostility, irritability, fear, or
nervousness) they experience.2 We combined these three to yield our measure of happiness.
What Do We Know About Happiness?
Since the advent of positive psychology in 2000, there has been a tremendous amount of research
in the field, with well-being mentioned in over 170,000 academic articles.3 Some of that work has
found that there is truth to the perception that some people just seem happier, and researchers
have looked closely at heritability (factors we’re born with) and how our environment shapes our
happiness. If we think of general happiness as a pie, then the research suggests that heritability
accounts for about 40% of that pie while 60% is attributed to other factors, especially life
experiences. Nearly the same can be said for the workplace: In a recent long-term study,
researchers found that while heritability accounted for about 30% of job satisfaction at age 21, the
importance of heritability dropped to less than 20% when measured again at ages 25 and 30.
Thus, environmental factors within the workplace become more important over time.4
The relative importance of some of those environmental factors has shifted recently. The “World
Happiness Report 2021” noted that within the workplace, happiness before the pandemic was
largely due to employees’ sense of belonging within an organization and among coworkers, the
flexibility afforded to workers, inclusivity, and a sense of purpose to their work (in descending order
of importance).5 Things changed dramatically during the pandemic: Having a supportive manager
became the largest predictor of happiness — nearly twice as important as the next ranked
workplace happiness factor, purpose.
Not surprisingly, money matters to employee happiness too — but research has shown that is
chiefly for those employees who indicated that money is important to them. In a recent study, the
relationship between income and happiness was over four times greater for people who reported
that money was important to them compared with those who cared much less about money.6
Thus, for employees who aren’t driven by money, income may merely be a hollow way to keep
score.
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/
2/5
23/05/2022, 14:27
Top Performers Have a Superpower: Happiness
Within the workplace, we know that happier employees are more likely to emerge as leaders, earn
higher scores on performance evaluations, and tend to be better teammates.7 We also know,
based on substantial research, that happier employees are healthier, have lower rates of
absenteeism, are highly motivated to succeed, are more creative, have better relationships with
peers, and are less likely to leave a company.8 All of these correlates of happiness significantly
influence a company’s bottom line.
Taken together, the data indicates that there is a lot of room for leaders and organizations to
influence happiness within the workplace. While happiness is influenced by heritability and drivers
like finding a sense of meaning, a larger portion of the happiness pie may result from factors like
workplace flexibility, reasonable pay, type of work, and managers who are supportive. That means
it’s possible for leaders to shape the workplace to make happier employees.
What Can Business Leaders Do About
Employee Happiness?
To begin, we suggest that leaders follow the science and take a structured approach to hiring for,
promoting, and developing employee happiness. While the approach will vary based on
organizational needs, leaders should commit to three actions.
1. Measure happiness in both employees and job candidates. In many ways, “hiring the happy”
requires a bit of perspective. While we do not believe that happiness should be placed ahead of the
knowledge, skills, or talent needed for a job, we conservatively advocate using measures of
happiness and optimism as discriminators, or tiebreakers, because the risks are low and the
benefits could be important. It is also important to use proven assessment tools and not rely on
management intuition based on an employee’s affect. Many organizations already use a variety of
surveys to evaluate job candidates. Even if adding these questions about happiness and optimism
to the applicant survey results in only a small increase in downstream productivity and profitability,
most leaders would jump at this opportunity, because it costs almost nothing. While this will of
course vary across organizations and sectors, most organizations are likely better off hiring
someone who is already relatively happy and optimistic, because they will influence exceptional
performance and reduce turnover. If you extrapolate our findings from the military study to a
private sector context where 1,000 hires are going to be made, using well-being as a hiring
criterion should lead to about 11 more exceptional performers than if the company simply hired
personnel without considering well-being at all.
Why Findings From a Study of the Military Matter to All Employers
The findings from our study are broadly applicable because the sample we used was not
drawn from a specific functional area, such as salespeople or IT professionals, as is often the
case in the published research on happiness in the workplace. Rather, while some soldiers in
our study worked in typical Army jobs, such as those found in the infantry, many more were
office workers, truck drivers, police officers, medical professionals, logistics experts, pilots,
engineers, and strategists, among others. Thus, our measurement of so many professions at
this scale and in a single study is unique and makes our results highly applicable to the
business world. In short, happiness mattered across the work spectrum. The sample matters
for other reasons, too. Because it was huge and ran for five years — at nearly 1 million people,
it’s the largest long-term well-being study ever done — we could perform more detailed
analyses with the data and demonstrate that the findings held true regardless of
demographics, as described above.
READ MORE +
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/
3/5
23/05/2022, 14:27
Top Performers Have a Superpower: Happiness
Beyond hiring, employee happiness should also be a consideration when measuring organizational
performance. Yes, objective performance still matters greatly. But, while a high-performing division
within a company may bring short-term profit, if that performance was driven by toxic leadership
and management practices, then those profits could evaporate quickly if employees were to leave
in response. Unwarranted attrition is expensive. The U.S. military, for example, has caught on to
this and has fired commanding officers who have fostered poor organizational climates, and at
times it has done so preemptively, before a catastrophic event could occur. After all, it costs
several hundred thousand dollars and years of effort to recruit and train a nuclear reactor engineer,
and much more to do the same for an aviator. Losing even a few to unhappiness borne from toxic
leadership is expensive and creates personnel shortages that increase the risk to those who
remain. Attrition and talent shortages in a corporation have similar negative effects. Thus, we
advocate treating happiness as an objective performance outcome of the organization, as well as a
leading indicator of leadership success. In our study, we used one of the gold-standard measures
of well-being, the Positive and Negative Affect Schedule (PANAS), which has been used in
thousands of published studies to examine happiness in a variety of contexts. It takes about 10
minutes to complete it.9
2. Develop happiness in your workforce. Given all the training and development requirements
placed on most organizations, the thought of actively trying to develop happier employees may
initially seem daunting, time consuming, and expensive. However, the academic literature
repeatedly shows that training initiatives targeting employee well-being do not require a significant
time investment, are cost effective, and carry a high ROI.
Here are three examples of simple exercises, each backed by rigorous evidence of effectiveness. In
the first, the Gratitude Visit, participants prepare and present a 300-word testimony of gratitude to
someone who changed their life for the better. In the second, Three Good Things, participants
write down three things that went well each day and what caused those things to go well, for one
week. The third, Using Signature Strengths in a New Way, calls on participants to complete an
online strengths survey and then use one of their top strengths in a new way each day for at least a
week. Research testing these approaches found that the Three Good Things and Signature
Strengths exercises significantly increased happiness and decreased depression over six months,
while Gratitude Visit did the same over one month.10 Of course, such workplace happiness
initiatives work best when people want to become happier, are willing to put some effort into the
process, and believe that those efforts will pay dividends.11 That aside, the costs are quite low, the
interventions can occur at any level of an organization, and they don’t require outside consultants.
For organizations willing to make a larger investment, there are of course turnkey, validated
programs shown to improve employee well-being. During the height of the wars in Iraq and
Afghanistan, for example, the U.S. Army invested heavily in resilience initiatives such as
Comprehensive Soldier Fitness, which was demonstrated to improve the psychological health of
service members.12 The program included extensive training for a large cadre of instructors,
resulting in an overall ratio of about 1 trainer for every 100 service members.13 Likewise, the
Enduring Happiness and Continued Self-Enhancement (ENHANCE) program was shown to
improve happiness, with effects lasting for over six months. ENHANCE is a 24-hour training
package that can be delivered in person or online and focuses on identifying core values,
cultivating mindfulness, establishing positive social relationships, dealing with negativity and
adversity, and other areas.14
Our recommendation: First, measure well-being. Next, start with the easy exercises to
demonstrate that the company values employee well-being. Then start investing in the more
formal programs over time as happiness increases.
3. Retain employees who are happy. The pandemic has reminded us of some tough realities,
namely that organizations can contract in turbulent times just as fast as they expand when the
economy is booming. Clearly, our military study shows that organizations should want happy
employees, because they perform significantly better than those who are unhappy. But it turns out
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/
4/5
23/05/2022, 14:27
Top Performers Have a Superpower: Happiness
that organizations also need happy employees, because happiness is in fact contagious. For
example, researchers examined 20 years of data from 4,700 participants in the long-running
Framingham Heart Study and discovered not only that happiness can spread across a social
network, but also that happy people are much more connected to other happy people within the
network. Perhaps the most striking finding of this study was that the effect of happiness extended
for three degrees of separation from the focal person (so, friends of their friends’ friends).15
Another important finding from this study is that like happiness, unhappiness is also contagious.
This contagion effect places leaders in a precarious position, especially if they are presented with
the difficult scenario of being able to retain only one of two employees. With performance and
other factors held constant, they should keep the one who is happiest.
Lead by Example
Our work with the Army over the past decade consistently uncovered a foundational truth:
Employee well-being initiatives work best when confident leaders present the material and when
senior leaders place significant emphasis on the overall effort.16 Thus, leaders must be willing to
invest their efforts into making the initiatives successful by not only advocating for them — for
example, by securing resources for a program and promoting positive strategic messaging — but
also by participating in the training and incorporating it into their own behaviors. If leaders want to
improve employee happiness, they must model that which is taught so that it becomes integral to
the organization’s lexicon and culture. We learn best by watching others, so let your employees
learn to be happy by watching you.
Topics
Workplace, Teams, & Culture
Culture
Performance Management
Work-Life Balance
ABOUT THE AUTHORS
Paul B. Lester is an associate professor of management at the Naval Postgraduate School. Martin Seligman is the
Zellerbach Family Professor of Psychology at the University of Pennsylvania, director of the university’s Positive
Psychology Center, and a former president of the American Psychological Association. He was named by Academic
Influence as the world’s most influential psychologist during the last decade. Ed Diener passed away in April 2021. He
was a professor of psychology at the University of Utah and the University of Virginia, the Joseph R. Smiley
Distinguished Professor Emeritus at the University of Illinois, and a senior scientist for the Gallup Organization. He
received the American Psychological Association’s Award for Distinguished Scientific Contributions in 2012, and his
work has been cited more than 250,000 times.
REFERENCES (17)
1. P.B. Lester, E.P. Stewart, L.L. Vie, et al., “Happy Soldiers Are Highest Performers,” Journal of Happiness Studies,
Aug. 25, 2021, https://doi.org/10.1007/s10902-021-00441-x.
2. E. Diener, “Subjective Well-Being: The Science of Happiness and a Proposal for a National Index,” American
Psychologist 55, no. 1 (January 2000): 34-43.
Show All References
TAGS:
Corporate Culture, Employee Morale, Employee Performance, Human Behavior, Performance Strategies
REPRINT #: 63305
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/
5/5
23/05/2022, 14:27 Top Performers Have a Superpower: Happiness
MAGAZINE SPRING 2022 ISSUE • RESEARCH FEATURE
Top Performers Have a Superpower: Happiness
A large-scale study found that well-being predicts outstanding job performance.
Paul B. Lester, Ed Diener, and Martin Seligman • February 16, 2022 READING TIME: 15 MIN
The toll that working through the global pandemic has taken on employees’ job satisfaction and
emotional well-being has focused business leaders on fostering workforce happiness as never
The Research
•
before. While many — if not most — of us are motivated by genuine caring for the people who power our organizations, we also intuitively know that employee happiness should boost job performance. Still, two nagging questions remain: Which comes first, succeeding and then being happy, or being happy and then succeeding? And just how much does initial happiness matter?
The results of our recent research, published in the Journal of Happiness Studies, have gotten us one big step closer to answering those two questions. For our study, we followed almost 1 million •
U.S. Army soldiers for nearly five years. We first asked them to rate their well-being — their happiness, if you will — along with their optimism, and then tracked which soldiers later received awards based on their job performance. We collected our data in the midst of the wars in Iraq and
Afghanistan, so the stakes were high: Some of those awards were for exemplary assigned job •
performance, while others were earned for extraordinary performance in heroic actions. Receiving an award in the Army, either for exemplary job performance or for heroism, is a relatively rare event. Of the nearly 1 million soldiers in our sample, only 12% received an award of any type during the five years that we ran the study.
While we expected that well-being and optimism would matter to performance, we were taken aback by just how much they mattered. We saw four times as many awards earned by the initially happiest soldiers (upper quartile) compared with those who were unhappiest initially (lower quartile) — a huge difference in performance between those groups. This gap held when we accounted for status (officers versus enlisted soldiers), gender, race, education, and other
The researchers followed nearly 1 million U.S. Army service members for five years, measuring their relative happiness and optimism using 25 questions drawn from PANAS and the Life Orientation Test. The questions were included on a larger survey taken by every Army soldier each year.
This well-being measurement combines individuals’ own self assessments and their reporting on the frequency of positive and negative emotions experienced, to yield the researchers’ measure of happiness.
Even after the researchers controlled for previous performance and a range of demographic factors, soldiers who were the happiest and most optimistic went on to earn significantly more job performance awards across the next five years compared with those who were initially unhappy and pessimistic.
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/ 1/5
23/05/2022, 14:27 Top Performers Have a Superpower: Happiness
demographic characteristics. In fact, happiness — and, to a somewhat lesser extent, optimism — 1
were better predictors of awards than any demographic factor we examined.
You might dismiss these results if you believe that military data somehow doesn’t apply to the business world, but you would be wrong to do so. After all, the U.S. Department of Defense is the single largest employer in the world, dwarfing Walmart by nearly 1 million employees. It has nearly $3 trillion in total assets (compared with Walmart’s $236 billion) and maintains over $290 billion in inventory (compared with Walmart’s $44 billion). The U.S. military is not just “big business”; it is, in fact, the biggest business by an order of magnitude, so what we learn from the military can and often does apply to the business world. There are over 190 distinct job categories in the Army — from clerk to pilot, cook to commander — and most were included in our data.
In short, not only do happiness and optimism matter to employee performance, but they matter a lot, and both predict how well employees will do. Our military research, along with other behavioral science research spanning the past 40 years, highlights the competitive advantage that employee happiness offers businesses. There are some things about employee happiness that every
business leader should know and be able to apply. And, as we emerge from a demoralizing global pandemic, we would all do well to take stock of how to influence the happiness and optimism of those around us in the workplace.
That raises the question, what really is happiness? The behavioral science literature often refers to happiness as subjective well-being because the meaning of happiness varies in different contexts. As with most concepts that emerge from psychology, definitions vary, but when it comes to happiness, they generally coalesce around three areas: a person’s own assessment of their satisfaction with life; how much positive emotion (such as enjoyment, enthusiasm, inspiration, or pride) they experience; and how little negative emotion (such as hostility, irritability, fear, or nervousness) they experience. We combined these three to yield our measure of happiness. 2
What Do We Know About Happiness?
Since the advent of positive psychology in 2000, there has been a tremendous amount of research in the field, with well-being mentioned in over 170,000 academic articles. Some of that work has 3
found that there is truth to the perception that some people just seem happier, and researchers have looked closely at heritability (factors we’re born with) and how our environment shapes our happiness. If we think of general happiness as a pie, then the research suggests that heritability
accounts for about 40% of that pie while 60% is attributed to other factors, especially life experiences. Nearly the same can be said for the workplace: In a recent long-term study, researchers found that while heritability accounted for about 30% of job satisfaction at age 21, the importance of heritability dropped to less than 20% when measured again at ages 25 and 30. Thus, environmental factors within the workplace become more important over time. 4
The relative importance of some of those environmental factors has shifted recently. The “World Happiness Report 2021” noted that within the workplace, happiness before the pandemic was largely due to employees’ sense of belonging within an organization and among coworkers, the flexibility afforded to workers, inclusivity, and a sense of purpose to their work (in descending order of importance). Things changed dramatically during the pandemic: Having a supportive manager 5
became the largest predictor of happiness — nearly twice as important as the next ranked workplace happiness factor, purpose.
Not surprisingly, money matters to employee happiness too — but research has shown that is chiefly for those employees who indicated that money is important to them. In a recent study, the relationship between income and happiness was over four times greater for people who reported that money was important to them compared with those who cared much less about money. 6
Thus, for employees who aren’t driven by money, income may merely be a hollow way to keep score.
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/ 2/5
23/05/2022, 14:27 Top Performers Have a Superpower: Happiness
Within the workplace, we know that happier employees are more likely to emerge as leaders, earn higher scores on performance evaluations, and tend to be better teammates. We also know, 7
based on substantial research, that happier employees are healthier, have lower rates of absenteeism, are highly motivated to succeed, are more creative, have better relationships with peers, and are less likely to leave a company. All of these correlates of happiness significantly 8
influence a company’s bottom line.
Taken together, the data indicates that there is a lot of room for leaders and organizations to influence happiness within the workplace. While happiness is influenced by heritability and drivers like finding a sense of meaning, a larger portion of the happiness pie may result from factors like workplace flexibility, reasonable pay, type of work, and managers who are supportive. That means it’s possible for leaders to shape the workplace to make happier employees.
What Can Business Leaders Do About Employee Happiness?
To begin, we suggest that leaders follow the science and take a structured approach to hiring for, promoting, and developing employee happiness. While the approach will vary based on organizational needs, leaders should commit to three actions.
1. Measure happiness in both employees and job candidates. In many ways, “hiring the happy” requires a bit of perspective. While we do not believe that happiness should be placed ahead of the knowledge, skills, or talent needed for a job, we conservatively advocate using measures of happiness and optimism as discriminators, or tiebreakers, because the risks are low and the benefits could be important. It is also important to use proven assessment tools and not rely on management intuition based on an employee’s affect. Many organizations already use a variety of surveys to evaluate job candidates. Even if adding these questions about happiness and optimism to the applicant survey results in only a small increase in downstream productivity and profitability, most leaders would jump at this opportunity, because it costs almost nothing. While this will of course vary across organizations and sectors, most organizations are likely better off hiring someone who is already relatively happy and optimistic, because they will influence exceptional performance and reduce turnover. If you extrapolate our findings from the military study to a private sector context where 1,000 hires are going to be made, using well-being as a hiring criterion should lead to about 11 more exceptional performers than if the company simply hired personnel without considering well-being at all.
Why Findings From a Study of the Military Matter to All Employers
The findings from our study are broadly applicable because the sample we used was not drawn from a specific functional area, such as salespeople or IT professionals, as is often the case in the published research on happiness in the workplace. Rather, while some soldiers in our study worked in typical Army jobs, such as those found in the infantry, many more were office workers, truck drivers, police officers, medical professionals, logistics experts, pilots, engineers, and strategists, among others. Thus, our measurement of so many professions at this scale and in a single study is unique and makes our results highly applicable to the business world. In short, happiness mattered across the work spectrum. The sample matters for other reasons, too. Because it was huge and ran for five years — at nearly 1 million people, it’s the largest long-term well-being study ever done — we could perform more detailed analyses with the data and demonstrate that the findings held true regardless of demographics, as described above.
+
READ MORE
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/ 3/5
23/05/2022, 14:27 Top Performers Have a Superpower: Happiness
Beyond hiring, employee happiness should also be a consideration when measuring organizational performance. Yes, objective performance still matters greatly. But, while a high-performing division within a company may bring short-term profit, if that performance was driven by toxic leadership and management practices, then those profits could evaporate quickly if employees were to leave in response. Unwarranted attrition is expensive. The U.S. military, for example, has caught on to this and has fired commanding officers who have fostered poor organizational climates, and at times it has done so preemptively, before a catastrophic event could occur. After all, it costs several hundred thousand dollars and years of effort to recruit and train a nuclear reactor engineer, and much more to do the same for an aviator. Losing even a few to unhappiness borne from toxic leadership is expensive and creates personnel shortages that increase the risk to those who remain. Attrition and talent shortages in a corporation have similar negative effects. Thus, we advocate treating happiness as an objective performance outcome of the organization, as well as a leading indicator of leadership success. In our study, we used one of the gold-standard measures of well-being, the Positive and Negative Affect Schedule (PANAS), which has been used in thousands of published studies to examine happiness in a variety of contexts. It takes about 10 minutes to complete it.
9
2. Develop happiness in your workforce. Given all the training and development requirements placed on most organizations, the thought of actively trying to develop happier employees may initially seem daunting, time consuming, and expensive. However, the academic literature repeatedly shows that training initiatives targeting employee well-being do not require a significant time investment, are cost effective, and carry a high ROI.
Here are three examples of simple exercises, each backed by rigorous evidence of effectiveness. In the first, the Gratitude Visit, participants prepare and present a 300-word testimony of gratitude to someone who changed their life for the better. In the second, Three Good Things, participants write down three things that went well each day and what caused those things to go well, for one week. The third, Using Signature Strengths in a New Way, calls on participants to complete an online strengths survey and then use one of their top strengths in a new way each day for at least a week. Research testing these approaches found that the Three Good Things and Signature Strengths exercises significantly increased happiness and decreased depression over six months, while Gratitude Visit did the same over one month. Of course, such workplace happiness 10
initiatives work best when people want to become happier, are willing to put some effort into the process, and believe that those efforts will pay dividends. That aside, the costs are quite low, the 11
interventions can occur at any level of an organization, and they don’t require outside consultants.
For organizations willing to make a larger investment, there are of course turnkey, validated programs shown to improve employee well-being. During the height of the wars in Iraq and Afghanistan, for example, the U.S. Army invested heavily in resilience initiatives such as Comprehensive Soldier Fitness, which was demonstrated to improve the psychological health of service members. The program included extensive training for a large cadre of instructors, 12
resulting in an overall ratio of about 1 trainer for every 100 service members. Likewise, the 13
Enduring Happiness and Continued Self-Enhancement (ENHANCE) program was shown to improve happiness, with effects lasting for over six months. ENHANCE is a 24-hour training package that can be delivered in person or online and focuses on identifying core values, cultivating mindfulness, establishing positive social relationships, dealing with negativity and adversity, and other areas.
14
Our recommendation: First, measure well-being. Next, start with the easy exercises to demonstrate that the company values employee well-being. Then start investing in the more formal programs over time as happiness increases.
3. Retain employees who are happy. The pandemic has reminded us of some tough realities, namely that organizations can contract in turbulent times just as fast as they expand when the economy is booming. Clearly, our military study shows that organizations should want happy employees, because they perform significantly better than those who are unhappy. But it turns out
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/ 4/5
23/05/2022, 14:27 Top Performers Have a Superpower: Happiness
that organizations also need happy employees, because happiness is in fact contagious. For example, researchers examined 20 years of data from 4,700 participants in the long-running Framingham Heart Study and discovered not only that happiness can spread across a social network, but also that happy people are much more connected to other happy people within the network. Perhaps the most striking finding of this study was that the effect of happiness extended for three degrees of separation from the focal person (so, friends of their friends’ friends). 15
Another important finding from this study is that like happiness, unhappiness is also contagious. This contagion effect places leaders in a precarious position, especially if they are presented with the difficult scenario of being able to retain only one of two employees. With performance and other factors held constant, they should keep the one who is happiest.
Lead by Example
Our work with the Army over the past decade consistently uncovered a foundational truth: Employee well-being initiatives work best when confident leaders present the material and when senior leaders place significant emphasis on the overall effort. Thus, leaders must be willing to 16
invest their efforts into making the initiatives successful by not only advocating for them — for example, by securing resources for a program and promoting positive strategic messaging — but also by participating in the training and incorporating it into their own behaviors. If leaders want to improve employee happiness, they must model that which is taught so that it becomes integral to the organization’s lexicon and culture. We learn best by watching others, so let your employees learn to be happy by watching you.
Topics
Workplace, Teams, & Culture Culture Performance Management Work-Life Balance
ABOUT THE AUTHORS
Paul B. Lester is an associate professor of management at the Naval Postgraduate School. Martin Seligman is the Zellerbach Family Professor of Psychology at the University of Pennsylvania, director of the university’s Positive Psychology Center, and a former president of the American Psychological Association. He was named by Academic Influence as the world’s most influential psychologist during the last decade. Ed Diener passed away in April 2021. He was a professor of psychology at the University of Utah and the University of Virginia, the Joseph R. Smiley Distinguished Professor Emeritus at the University of Illinois, and a senior scientist for the Gallup Organization. He received the American Psychological Association’s Award for Distinguished Scientific Contributions in 2012, and his work has been cited more than 250,000 times.
REFERENCES (17)
1. P.B. Lester, E.P. Stewart, L.L. Vie, et al., “Happy Soldiers Are Highest Performers,” Journal of Happiness Studies, Aug. 25, 2021, https://doi.org/10.1007/s10902-021-00441-x.
2. E. Diener, “Subjective Well-Being: The Science of Happiness and a Proposal for a National Index,” American Psychologist 55, no. 1 (January 2000): 34-43.
Show All References
TAGS: Corporate Culture, Employee Morale, Employee Performance, Human Behavior, Performance Strategies REPRINT #: 63305
https://sloanreview.mit.edu/article/top-performers-have-a-superpower-happiness/ 5/5
High-Stakes Wall Street Professionals and Personal Values
What drives high stakes Wall Street professionals and how do they navigate the
emotional ups and downs of the stock markets, the lack of transparency which permeates the industry, and the unending expectation of profitability without losing site of their personal
values? One of the most successful billionaire hedge fund managers, Ray Dalio, in his best selling novel, Principles (2017), professes that daily meditation and focus upon one’s core principles are the necessary ingredients for personal and career success (Fabel, 2018; Dalio, 2019). World renown clinical psychologist Jordan Peterson’s, 12 Rules for Life (2018), also advances the idea that happiness is only attainable when individuals pursue what is truly meaningful and not expedient (2018). Wall Street professionals are faced with acute stress due to constant market changes, and thereby need strategies to re-ignite and balance their own personal values. Thus, it seems like an opportune time to introduce these high stakes finance professionals to Acceptance and Commitment Therapy (ACT). ACT is a modern, mindfulness-rooted, and research supported training technique. ACT helps individuals more successfully “carry” their human perplexities and sufferings while still remaining focused upon values-based living.
ACT was first developed in the late 1990s by Hayes, Barnes-Holmes, and Roche (2001) to treat various mental health conditions with the goal of teaching individuals how to shift the way they may think and/or feel about emotional pain and suffering in order for them to live healthier, happier, and fuller lives. It is a model born out of contextual behavioral sciences, and unlike its more traditional counterpart, Cognitive Behavioural Therapy (CBT), ACT fosters both mindfulness and acceptance in order for its participants to successfully pursue values-based lives (Flaxman et al., 2013). ACT’s key message is that when there is a “pouring together” or an “entanglement” of a person with his/her negative thoughts and feelings, and he/she, in turn, begins to experientially avoid these feelings, it often creates toxicity (Flaxman, et al., 2013). This
ACT process of exposure to negative thoughts and feelings and disentanglement involves “psychological flexibility” (Flaxman et al., 2013). In order to be “psychologically flexible”, an individual must fully contact the present moment, the thoughts and feelings it contains so that he/ she can persist or change behaviors in pursuance of values-based living (Hayes et al., 2016).
ACT’s workplace intervention model for “psychological flexibility” is expressed in a six sided, interactive hexagon, i.e., the Hexa-Flex, and each side represents one of the following processes: contact with the present moment, self as context, acceptance, defusion, personal values, and committed action (Flaxman et al., 2013). This model requires participants to use the latter mentioned to help isolate values-based goals and committed actions (Flaxman et al., 2013). One scholar, Harris (2019) has further simplified the Hexa-Flex process from its six core principles to the ACT Tri-Flex model whereby an individual must be present, open up, and “do what matters” in order to be “psychologically flexible”. Flaxman and colleagues (2013) describe in their ACT training manual for improving well-being and performance in the workplace that ACT’s six core procedure is essentially designed to target two main areas — 1) mindfulness and 2) values-based action. In an attempt to begin unraveling “psychological flexibility” among high stakes Wall Street professionals, this dissertation will explore only a portion of one of the two workplace, target areas — personal values.
Many psychological treatments hold personal values to be central to living productive and vital lives. ACT is considered to be a modern psychotherapy model which builds upon many other values-based psychology theories, such as: the client-centered approach of Carl Rogers,
B.F. Skinner’s “radical behaviorism”, and Martin Seligman’s positive psychology (Yadavaia & Hayes, 2009). According to Carl Rogers, individuals have the urge to expand, develop and mature — “to become [their] potentialities” or “self actualise” (Rogers ,1964). However, this self- actualisation process is often difficult because what they value is often buried beneath deep layers of facades, living to please others, and striving to meet external, moral standards (Rogers, 1964). Rogers (1964) describes the self-actualisation or client-centered therapy process to be one of “unconditional positive regard”. Unconditional positive regard is simply defined as accepting and supporting another exactly as they are, and it draws a distinction between “operative values” (i.e. infant perceptions are created in the present moment with each new experience) and “conceived values” (i.e. as we grow older our values become more rigid, inefficient, and influenced by the judgment of others) (Rogers, 1964). Client-centered therapy does not require the client to abandon conceived values, but it encourages the client to continually test and inform him or herself against everyday experiences so that values become more fluid and flexible (Rogers, 1964). Essentially, adjusting one’s behaviour based upon feedback from the environment allows individuals to live authentically (Rogers, 1964).
Similar to Rogers, Skinner (1971) associates values with operant behaviour and with pursuing what is good, i.e. “positive reinforcers”. Skinner (1971) believes that according to his notion of “radical behaviorism”, values are the reinforcing effects of consequences, and these behaviors or values can be done either for the good of others or for the good of oneself (Yadavaia & Hayes, 2009). Additionally, Martin Seligman (2017) is considered to be the father of positive psychology and like Rogers, he believes in the idea of the “self-actualisation” of potential, as well as in “self-determination theory” whereby people intrinsically move towards motivation and autonomy. However, he supplants unconditional positive regard with mindfulness techniques and activities which identify and enhance signature strengths, i.e. values. (Seligman, 2002).
ACT also works well along side or in conjunction with Shalom Schwartz’s circumplex of values, illustrated below (Schwartz, 2012). He asserts that there are ten universal and cross
cultural values that all human beings possess, such as self direction, benevolence, hedonism, achievement, security, etc (Potts, 2015; Schwartz, 2012). Schwartz’s (2012) compilation of universal values form a circular structure and reflect the motivations that each value expresses. They sit closely along side one another in the circumplex to form a continuum of motivational similarities and dissimilarities which are simultaneously congruent and conflicting across two axes —Openness to Change versus Conservation and Self-Transcendence versus Self- Enhancement (Potts, 2015; Schwartz, 2015). Based upon the opponent structure of the axes, the values which are opposite to each other compete for priority in individuals’ lives (Schwartz, 2012). In order to create this circumplex, Schwartz (1994) studied values from samples of 30,000 public school teachers, university students, and working adults from every continent across the world.
There exists a substantial body of quantitative literature exemplifying values-based living to be the central component to ACT, and in a recent systematic review Reilly and colleagues (2019) affirmed this notion when they reviewed the most psychometrically sound and appropriate measures to assess values. They describe an important distinction between values and goals, such that goals can be completed and achieved but values serve as guiding principles and reflections of what an individual finds to be meaningful (Reilly, et al., 2019).
In an effort to explore values, ACT also employs experiential exercises amidst different domains of life, such as: marriage, family, community, physical fitness, diet, arts, literature, etc. (Baer, 2015). These exercises are usually done through a Valued Living Questionnaire, values cards, and/or a semi-structured interview process whereby individuals self-rate importance of each value domain and their committed actions in each area (Baer, 2015). This is process by which participants can identify and re-direct energy “towards” areas of high priority and “away” from areas of low priority (Baer, 2015). Additional mindful activities include individuals writing their own tombstone epitaphs or a birthday speech that a friend or co-worker would give about them in order to capture how they would like to be remembered (Baer, 2015). Following these mindful exercises, ACT therapists engage the participants in thoughtful discussions regarding behaviour modifications (Baer, 2015).
Recent qualitative research investigated how 16 working adults articulate, change, and increase value congruent behaviour following a five session values clarification and congruence workshop with faculty and staff of a large metropolitan university (Fitzpatrick et al., 2016). The training was guided by both ACT’s values-based model and Shalom Schwartz’s value circumplex (Fitzpatrick et al., 2016; Schwartz, 1992). Following the workshop, the participants were interviewed regarding the process of articulating their values, changing their values, and increasing value-congruent behaviour (Fitzpatrick et al., 2016). After a thorough thematic analysis was conducted, their qualitative findings were as follows: 1) facing contextual challenges makes values clarification and resulting behaviours pertinent, 2) contextual challenges do not need to be traumatic for socialisation, exploration, and/or activation of values to occur, 3) focused attention is needed for congruent behavioural actions to take place, 4) cognitive activation or re-perceiving of values is necessary, 5) inspiration to make change or activate existing values is necessary, and 6) it’s helpful and encouraging to have a workshop partner to share and articulate values and committed actions (Fitzpatrick et al., 2016; King & Hicks, 2009; Shakespeare-Finch & Lurie-Beck, 2014; Shapiro, Carlson, Astin, & Freedman, 2006; Mendelsohn, Pine, & Schiller, 2014; Martin, Garske, & Davis, 2000).
Journal of Happiness Studies
https://doi.org/10.1007/s10902-021-00441-x
RESEARCH PAPER
Happy Soldiers are Highest Performers
Paul B. Lester1 · Emily P. Stewart2 · Loryana L. Vie2,3
Martin E. P. Seligman2 · Ed Diener5
· Douglas G. Bonett4
·
Accepted: 3 August 2021
This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may
apply 2021
Abstract
We examined the prediction of affective well-being to work performance in the United
States Army. We found that high positive affect (PA), low negative affect (NA), and high
optimism predicted awards for performance and heroism in a sample of 908,096 U.S. Army
soldiers (mean age 29.60 years old, SD = 9.16 years; with over ¼ of a million ethnic minorities and over 150,000 women). Baseline high PA, low NA, and high optimism predicted
awards over a four-year follow up window, in which 114,443 soldiers (12.60%) received
an award. Each well-being variable predicted future awards for both women and men, for
enlisted soldiers as well as officers, for several ethnicities, for varying levels of education,
and controlling for a number of other potential explanatory variables. The effects of high
positive and low negative affect were additive, with each predicting significantly beyond
the other. Comparing the soldiers highest vs. lowest in well-being predicted an almost fourfold greater award recognition in the high group. Awards were predicted by both high and
low arousal positive emotions, as well as low sadness and low anger. The relations between
PA, NA, and optimism with award attainment were curvilinear, with the greatest difference
in award attainment occurring between low and moderate levels of affective well-being,
with little effect between moderate and high well-being.
Keywords Subjective well-being · Positive affect · Negative affect · Optimism ·
Performance
In recent decades, research indicates that high levels of subjective well-being (SWB) are
associated with beneficial outcomes such as health and citizenship (Diener & BiswasDiener, 2018; Diener et al., 2015). In addition to positive affect (PA) and negative affect
* Ed Diener
ediener@illinois.edu
1
Naval Postgraduate School, Monterey, USA
2
Positive Psychology Center, University of Pennsylvania, Philadelphia, USA
3
Research Facilitation Laboratory, U.S. Army, Washington, USA
4
University of California, Santa Cruz, USA
5
The Gallup Organization, University of Utah, University of Virginia, Salt Lake City, USA
13
Vol.:(0123456789)
P. B. Lester et al.
(NA), dispositional optimism, too, has been associated with multiple benefits, including
better health (Rasmussen et al, 2009), an energetic task-focused approach to goals (Carver
et al., 2009), and better social relationships (Srivastava et al., 2006). Yet, there also is a
long scholarly tradition of examining employee well-being in relation to work outcomes.
Indeed, while much of this original workplace research focused on job satisfaction, the
focus shifted more recently to the link between affective well-being and work performance
(Kaplan et al., 2009).
A review of the evidence indicates that SWB is associated with work performance and
income, with longitudinal and some experimental evidence suggesting that this might be a
causal association (Tenney et al, 2016). In general, high positive affect has been associated
with better work performance, and high negative affect with poorer performance, and we see
this across populations, types of work, and types of well-being, as well as the shape of this
relationship (Lyubomirsky et al., 2005). Optimism, too, can have a powerful influence on
work performance (Jensen et al., 2007; Luthans et al., 2008; Seligman & Schulman, 1986;
Youssef & Luthans, 2007), though it must be realistic, as optimism can suffer from the “too
much of a good thing” phenomenon (Hmieleski & Baron, 2009; Tenney et al., 2015).
The SWB and optimism literatures are quite extensive, so much so that over 170,000 scholarly articles mentioning SWB alone were published between 1999 and 2018 (Diener et al.,
2018). Despite this, many important questions about SWB and optimism remain unanswered,
especially those that would require significant sample diversity and power to properly examine. For example, many of the published studies examining SWB employ the PANAS, which
measures many discrete emotions, but what is reported is typically restricted to dimensional
effects because the studies often lack the power to examine how those discrete emotions alone
influence outcomes (Tenney et al., 2016). Likewise, while the “too much of a good thing”
phenomenon has garnered significant attention in the workplace literature of late (Pierce &
Aguinis, 2013), little is known about the curvilinear properties of the general levels of SWB
and optimism on performance; at what point does happiness or optimism begin to negatively
impact job performance? As outlined by Diener and coauthors (2018), the literature has yet
to establish how job characteristics and demographics might moderate the link between SWB
or optimism and work performance; most studies on SWB lack sample diversity and power
to examine these questions. Finally, while several studies have examined the relationship
between SWB and work performance writ large (Judge et al., 2010; Wright et al., 2007), the
literature offers little explanation for how SWB might influence objective exemplary performance (Tenney et al., 2016).
Thus, the goal of the present study is to explore these areas, along with others described
later. Access to an enormous and diverse data set of service members from the US Army
allowed us to examine these areas with specificity and statistical power; this study includes
data from over 900,000 service members across seven years of analysis. We begin with an
overview of the criterion variable—Army performance awards—to provide context, while
also describing both the awards system and prevalence of award attainment in the Army. We
then return to a deeper discussion of important but unanswered matters connected to SWB,
optimism, and performance, we next summarize the contributions of the current study, then
move on to the pro forma sections of our empirical study.
13
Happy Soldiers are Highest Performers
1 Army Awards
As highlighted by Carpini and coauthors (2017), the workplace literature often frames certain
constructs as performance when they clearly are not (e.g., organizational citizenship behaviors,
creativity). Fortunately, U.S. Army awards are a highly accurate performance metric because
they neatly fit the definition of performance, where “performance means to do or act” (Frese
& Fray, 2001, p. 173). Thus, performance must be observable. Army regulations require that
performance awards be given for observable behavior, and these observations are meticulously
documented in paperwork twice, once on the award certificate presented to the soldier, and
once on the nomination form completed by the leader nominating the soldier for the award.
Although not unique, we submit that this level of observable performance-award specificity is
quite rare in the literature.
The Army has three broad categories of individual awards—heroism awards, service
awards for performance (hereafter, “performance awards”), and service awards for participation. Heroism awards are performance awards, where a soldier risks his or her life in specific
combat contexts (e.g., Medal of Honor, Silver Star) or non-combat contexts (e.g., Soldier’s
Medal), and they are rare because the context calling for such action is rare. The soldier must
take action that warrants such an award, a witness must see the soldier’s action, then prepare
a narrative and nominate the soldier for the award, and then the soldier’s commanders must
approve the award. For the wars in Iraq and Afghanistan, heroism awards were under such
high scrutiny that they often required the approval of a service secretary (e.g., the Secretary of
the Army), meaning that the award nomination packet must be reviewed and endorsed by 6–7
echelons of leadership prior to final approval. To provide context for the rarity of receiving a
heroism award, over 3 million service members have served in Iraq or Afghanistan since 2001.
Of those 3 million, many service members have deployed to combat multiple times, for a total
of over 6 million individual deployments; only 1007 Silver Stars have been awarded across all
military branches over the last 20 years (~ 0.016%) (U.S. Department of Defense, 2020).
Soldiers also receive awards for job performance, and these can be given for discrete
instances (e.g., a soldier wins the Soldier of the Quarter competition and is awarded the Army
Achievement Medal) or longitudinal performance (e.g., a soldier performs in exemplary fashion for three years in a specific organization and is awarded the Army Commendation Medal).
Service awards for performance are more common than heroism awards but receiving them
is predicated on excellent job performance and they are still relatively rare. Like heroism
awards, performance award nomination packets are also heavily scrutinized and usually must
be endorsed by 3–4 echelons of leadership prior to final approval. Lastly, soldiers may receive
an award for participating in a particular event, such as deploying to a combat theater of
operations or for simply being a member of the armed forces when a national emergency was
declared (e.g., the National Defense Service Medal). Because service awards for participation
are common and can be given en masse to all members of an organization, this award type is
not necessarily indicative of exemplary performance, and we did not include it in our analyses.
2 Literature Review and Contributions
A consistent theme raised within the well-being and workplace literature focuses on understanding the conditions in which happiness and optimism matter the most vis-à-vis work
performance (Diener et al., 2017a, 2017b; DiMaria et al, 2020). For example, Lucas and
Diener (2003) predicted that well-being might be more important to performance primarily
13
P. B. Lester et al.
in settings where work is less structured and routinized, and where the work requires more
creativity and initiative. Their prediction was based on the notion that structured and routinized work typically lacks autonomy and tends to be overly prescriptive, yet they did not
present evidence to directly support this hypothesis. The Army dataset allows us to explore
this hypothesis because it includes data from two broad categories of employees, enlisted
soldiers (e.g., Privates, Sergeants) and officers (e.g., Lieutenants, Captains). Generally,
work performed by enlisted soldiers tends to be more prescribed and routinized, whereas
work performed by officers tends to be more autonomous and somewhat self-driven.
Beyond understanding when well-being and optimism matter the most to work performance, another lingering question in the literature is for whom does well-being and optimism matter more for work performance (Diener et al., 2018). Importantly, our current
study may help to settle this important issue. Broadly, the research suggests that ratings of
well-being tend to be quite similar between men and women (Fujita et al., 1991), and most
slight variations are accounted for by country of origin or cultural factors (Meisenberg &
Woodley, 2015). Likewise, research also highlights how race (Waldman & Avolio, 1991)
and gender (Greenhaus & Parasuraman, 1993) factor into work performance evaluations,
though not actual performance. Thus, while there are certainly published studies examining the role that demographics play in reported subjective well-being or how work performance might be evaluated, we are unaware of robust studies that accurately account for
demographic differences between well-being and work performance. Our sample provides
enough statistical power to effectively examine several demographic categories, including
race, gender, education level, marital status, employment tenure, and full time (active duty)
vs. part time (National Guard and Army Reserve) employment status. If demographic differences exist, we expect them to be small.
An additional matter in the well-being literature needing exploration is measurement
specificity. Well-being scholars tend to divide emotions primarily into dimensions, with
positive and negative affect the two most important dimensions (Russell, 2003). Doing so
makes sense heuristically and methodologically, but the obvious tradeoff is precision. Less
explored are the discrete emotions comprising each of the affective dimensions (e.g., Izard,
1997). A review by Kaplan and coauthors (2009) conduced that both positive and negative
affect dimensions are associated with various aspects of job performance. In a meta-analysis of the literature, Shockley and coauthors (2012) found that most associations were due
to general dimensional effects rather than to discrete emotions, but this was not surprising and in large part was a methodological artifact owing to the statistically underpowered
nature of many of the studies included in the meta-analysis. Choi and coauthors (2020)
found that a latent trait of general well-being accounted for associations with various desirable behavioral outcomes such as health behaviors, with no significant additional associations found for the separate types of well-being. Despite what these studies reported, the
dimension vs. discrete question lacks a conclusive answer and thus we categorize emotions in each of these ways and examine their association with performance. Specifically,
our study’s large statistical power enables us to determine whether high positive and low
negative affect each predict performance beyond the common variance they share, while
also examining discrete emotions. Thus, we divide positive emotions into two major types,
low and high arousal, and examine three of the most important forms of discrete negative
emotions—sadness, anger, and worry. This approach is noteworthy because within these
negative emotions, Shockley and coauthors (2012) found that only sadness produced lower
performance. Data on optimism are also measured by the Army and therefore are included
in our analyses, although in line with previous research (Carver et al., 2014), we expect
optimism associations to be similar to those of positive affect.
13
Happy Soldiers are Highest Performers
Beyond the dimensional vs. discrete emotion debate, additional focus on arousal levels
is warranted because they would also likely differentially predict performance. Simply put,
individuals with high positive arousal levels measured in the current study (e.g., enthusiasm, joy, and excitement) could be energized to perform well in work tasks (Larson &
Diener, 1992). This assertion is consistent with more recent literature, such as the Broadenand-Build theory of positive emotions (Fredrickson, 2001), where positive emotions
can lead to upward spirals of performance. There are some additional indicators within
the literature suggesting that arousal level does influence factors related to performance
(Lyubomirsky et al., 2005), such as curiosity and exploration (Kashdan et al., 2004), intentions to quit, and conflict with coworkers (Van Katwyk et al., 2000). Past findings from the
health arena also suggest that high arousal PA might not be as beneficial as low arousal
(Pressman & Cohen, 2005). Most research on well-being outcomes, however, has not differentiated between high and low arousal positive and negative feelings. Therefore, in addition to examining general PA, optimism, and general NA, we examine whether different
arousal levels vary in their prediction of performance. Here, we examine both low and high
arousal PA, as well as low and high arousal NA. Further, an unresolved question in the literature relates to how each type of well-being and optimism might work in concert to predict performance (Tenney et al., 2016). Framed more succinctly, is the predictive power of
PA, optimism, and NA on performance due to their overlap or to unique variance in each?
And, are their effects additive or interactive? In sum, we examined both broad and narrow
affective well-being measures as predictors of performance, both individually and together.
Another important yet unresolved matter within the well-being literature is determining
if the relationship between affect and work performance departs from linearity. Specifically,
two questions emerge: First, do the effects of well-being show declining marginal patterns,
such that the benefits are strongest moving from low to moderate levels, and then decline
as one moves to higher levels? Second, do those highest in well-being accrue the most benefits, or is there a downturn in performance after some inflection point? These questions
dovetail with reviews by both Pierce and Aguinis (2013) and Grant and Schwartz (2011),
who hypothesized a “too-much-of-a-good-thing” pattern emerges, such that performance
initially improves but begins to drop off after typically desirable management characteristics are taken to the extreme and saturate a workplace. What results is a nonlinear relation
between the construct of interest and performance, which has been empirically illustrated
in the literature repeatedly, including personality (Le et al., 2011), optimism (Brown &
Marshall, 2001; Haaga & Stewart, 1992; Hmieleski & Baron, 2009; Tenney et al., 2015),
persistence (Moon, 2001), generosity (Flynn, 2003), experience (Sturman, 2003), learning
orientation (Bunderson & Sutcliffe, 2003), and various forms of leadership (Cheong et al.,
2019; Trevino et al., 2000). With these compelling findings in mind, we would reasonably
expect to see a similar nonlinear relation between well-being and performance, and the
current literature suggests this might be the case, albeit inconclusively. For example, Oishi
and coauthors (2007) found a linear relation between well-being and social relationships,
with the highest well-being individuals having the best social lives. However, for income,
the association peaked at a moderately high level of well-being, but it dropped off at maximal affective well-being. Thus, going from very low to moderate levels might facilitate
performance, but above moderate levels, the gains might be small or even reversed. In the
present study, our very large sample enables us to reliably examine the curvilinear effects
in order to ascertain whether intermediate levels of affective well-being are optimal for
performance.
Moreover, we also intend to use this sample to accurately and perhaps conclusively
quantify the strength of the prediction of well-being and optimism on performance. Given
13
P. B. Lester et al.
the wide range of factors and interactions that could come together to influence performance, it is likely that the effects of well-being and optimism on performance are small,
but still both statistically and practically significant. This would accord with a long-running
debate about the beneficial effects of job satisfaction, where Iaffaldano and Muchinsky
(1985) argued that the effects of job satisfaction on performance are small; they found correlations in the 0.17 range. Later, Judge and coauthors (2001) disattenuated the association
for the unreliability of measures and argued that the correlation between job satisfaction
and performance is about .30. Returning to well-being, a systematic analysis of the size of
the effects of PA and NA on performance in a very large and very diverse sample enables
us to reliably estimate the magnitude of predictions for various well-being types and in
various subgroups.
Finally, as our repeated reference thus far to statistical power and our demographically
diverse sample insinuates, we fully expect the current study to reinforce several findings
previously published in the literature; indeed, we view this as an important contribution
to the literature. Replication in behavioral science research can no longer be assumed, as
evidenced by the compelling findings reported by the Open Science Collaboration (2015).
With this in mind, our study leverages several methodological strengths to examine if wellbeing and optimism predict outstanding performance. As we describe in more detail below,
this study is longitudinal and controls for numerous potential confounds, thus improving
the strength of the inferences made about how well-being and optimism influence performance. Second, we rely on an objective outcome—attainment of heroic performance or job
performance awards—rather than self-reports of work performance. Third, whereas past
research has analyzed the range of work performance, and thus might be heavily influenced
by weak performance of unhappy employees, we examined the other end of the spectrum—exemplary performance.
3 Summary of the Major Contributions
Using a very large and diverse longitudinal sample, we were able to address several
important questions about well-being and optimism with precision, specificity, and statistical power. For context, the sample size within each of our demographic categories
often exceeds the pooled sample size of most published meta-analyses on well-being and
optimism.
1. We examined the two major dimensions of affect, PA and NA, as well as key discrete
emotions (low and high arousal PA, as well as sadness, anger, and worry), in relation to
work performance.
2. We examined the predictive power of affective well-being in differing types of work,
where officer versus enlisted status and level of education served as proxies for differing
types of work.
3. We analyzed whether the well-being and work association is generalizable across demographic groups, including ethnic minorities and gender, as well as education.
4. We explored two types of work performance—a performance award based on exemplary
work behavior over time and heroic performance that depends on exceptional risk to life
in an episode.
5. We accurately estimated the strength of the associations between the various types of
well-being measures and work performance.
13
Happy Soldiers are Highest Performers
6. Finally, we analyzed whether performance is predicted by well-being in a linear or
curvilinear way, in order to determine if there are diminishing returns to performance
with increasing levels of well-being, and if there is an inflection point after which there
is less superior performance.
4 Method
4.1 Study Subjects
We examined a cohort of 908,096 Army active duty, Reserve, and National Guard soldiers
who were 17–65 years of age at baseline, completed the Army Global Assessment Tool
(GAT) between October 1, 2009 and September 30, 2012, and indicated through an electronic “opt-in” procedure that their responses could be used for research purposes. We then
assessed if participants received an award after completing the GAT used in this study;
the awards assessment follow up period ran through September 30, 2016. The university’s
Institutional Review Board and the Army Human Research Protections Office regulatory
authority both approved the current study.
4.2 Measures
4.2.1 Well‑being
Three measures of baseline affective well-being were taken from the GAT (Version 1.0), a
self-report psychosocial questionnaire that Army soldiers completed annually. The GAT is
not a standalone psychometric instrument but rather is a collection of validated measures
commonly found in the literature (Peterson et al., 2011; Vie et al., 2016). The present study
draws from relevant measures found on the GAT, described below.
Ten PA items were used from the Positive and Negative Affect Schedule Expanded
Form (PANAS-X; Watson & Clark, 1994) and assessed on a 1 (never) to 5 (most of the
time) Likert response scale. Questions assessed general PA over the past four weeks (e.g.,
“inspired,” “happy,” “proud,” and “calm”) and were internally consistent (𝛼 = 0.94). In
addition to assessing general PA, we also employed subscale scores reflecting high arousal
PA (“enthusiasm,” “joy,” and “excitement”; 𝛼 = 0.86) and low arousal PA (“calmness,”
“contentment”; 𝛼 = 0.80). Across all PA measures, higher scores indicate higher PA levels.
Eleven NA items were also adapted from the PANAS-X (Watson & Clark, 1994). Questions assessed general NA over the past four weeks (e.g., “distressed,” “scared,” “angry,”
“guilty,” and “sad”) and were internally consistent (𝛼 = 0.90). In addition to assessing
general NA, we also formed two high arousal subscales (hostility [“angry,” “hostile”; 𝛼 =
0.77], and anxiety [i.e., “anxiety,” “fearfulness”; 𝛼 = 0.69]) and assessed low-arousal NA
with a single item (i.e., “sadness”). Across all NA measures, higher scores indicate higher
NA levels.
Four optimism items were adapted from the revised Life Orientation Test (Scheier et al.,
1994). Respondents indicated their agreement with four statements (e.g., “Overall, I expect
more good things to happen to me than bad”) using a five-point response scale, ranging from 1 (strongly disagree) to 5 (strongly agree). After reverse scoring the negatively
13
P. B. Lester et al.
worded items, we averaged the optimism items, with higher scores indicating higher optimism levels. Optimism items demonstrated adequate internal consistency (𝛼 = 0.75).
4.2.2 Awards
This study examined Army heroism and performance awards (for a full list, see Table 1).
We examined both whether a soldier received a heroism or performance award during follow up, and separately, we examined the type of award received (heroism award, performance award only, or neither).
4.2.3 Demographic and Military Characteristics
Demographic and military characteristics were derived from electronic administrative
records housed at the Defense Manpower Data Center and were assessed at the time of
each soldier’s baseline GAT. Demographic characteristics included as predictors at baseline
were gender (male or female), age (years), race/ethnicity (White or other ethnic groups),
educational attainment (high school educated and below or greater than high school) and
marital status (married, never married, other).
Military characteristics included as control variables at baseline included deployment
status (prior deployment versus no prior deployment), rank (enlisted soldier or officer), service component (active duty, Reserve, or Guard), length of Army service (years), and prior
award attainment (received versus did not receive a heroism or performance award before
baseline). Because approximately 20% of the soldiers left the Army during the follow-up
window, we also accounted for length of follow up (years); please see Table 2 for detailed
descriptive statistics.
Table 1 Awards included in this study, by type
Heroism awards
Performance awards
Medal of Honor
Defense Distinguished Service Medal
Distinguished Service Cross*
Silver Star Medal
Distinguished Flying Cross
Soldier’s Medal
Bronze Star (with V device)
Purple Heart
Air Medal (with V device)*
Army Commendation Medal (with V device)
Army Distinguished Service Medal
Defense Superior Service Medal
Legion of Merit
Bronze Star (without V device)
Defense Meritorious Service Medal
Meritorious Service Medal
Air Medal (without V device)
Army Commendation Medal (without V
device)
Army Achievement Medal
Military Outstanding Volunteer Service Medal
Army Achievement Medal (with V device)*
*Although included in the heroism category, these awards were not observed in the sample during the study
follow up period. We excluded awards with a narrow eligibility pool (e.g., specific occupations, deployment
locations, military units, or components), as well as awards associated with other services (Navy, Coast
Guard, Air Force, Marine Corps)
13
Happy Soldiers are Highest Performers
Table 2 Descriptive statistics by award status
Characteristic
No award
(N = 793,653)
87.40%
Award
(N = 114,443)
12.60%
Effect sizea
Positive Affect: M (SD)
3.73 (0.79)
3.85 (0.72)
.159
Negative Affect: M (SD)
Optimism: M (SD)
Age, in years: M (SD)
Years in service: M (SD)
Years of follow-up: M (SD)
Gender: n (%)
Male
Female
Race/Ethnicity: n (%)
White, Non-Hispanic
Black
Hispanic
Other
Prior Awards: n (%)
None
One or more
Rank: n (%)
Enlisted
Officer
Deployment before study: n (%)
Deployed
Did not deploy
Army Component: n (%)
Active duty
Reserve
National Guard
Education: n (%)
Up to high school diploma
More than high school
Marital Status: n (%)
Married
Never Married
Other
2.24 (0.70)
3.71 (0.83)
29.60 (9.26)
9.16 (8.99)
3.55 (1.01)
2.13 (0.62)
3.82 (0.76)
29.56 (8.54)
9.33 (8.54)
3.94 (0.39)
– .166
.138
– .004
.019
.509
653,345 (82.87%)
135,021 (17.13%)
98,164 (85.78%)
16,278 (14.22%)
1.04
0.83
508,597 (64.51%)
151,161 (19.17%)
82,482 (10.47%)
46,148 (5.85%)
82,368 (71.97%)
15,530 (13.57%)
10,582 (9.25%)
5,963 (5.21%)
1.12
0.71
0.88
0.89
735,650 (92.69%)
58,003 (7.31%)
51,966 (45.41%)
62,477 (54.59%)
0.47
7.47
671,751 (85.21%)
116,636 (14.79%)
94,123 (82.25%)
20,319 (17.75%)
0.96
1.20
432,293 (54.47%)
361,360 (45.53%)
61,846 (54.04%)
52,597 (45.96%)
0.99
1.01
412,173 (52.28%)
179,790 (22.80%)
196,423 (24.91%)
36,761 (28.30%)
1,448 (1.27%)
76,234 (66.61%)
0.54
0.06
2.67
611,961 (77.95%)
173,125 (22.05%)
87,330 (76.44%)
26,912 (23.56%)
0.98
1.07
389, 667 (49.50%)
347,524 (44.14%)
50,103 (6.36%)
57,027 (49.85%)
50,533 (44.18%)
6,831 (5.97%)
1.01
1.00
0.93
a
The effect size is Cohen’s d for the six quantitative variables and a proportion ratio for each level of the
eight categorical variables. All variables were significantly related to award status at p < .01 except for Age.
The No Award and Award groups were compared using an independent-samples t-test (equal variances not
assumed) for the six quantitative variables and a chi-square test of independence for the eight categorical
variables
13
P. B. Lester et al.
4.3 Statistical Analyses
Analyses were performed using SAS, version 9.4, in the Person-Event Data Environment,
a secure, cloud-based environment that houses Army workforce, medical, and personnel
data (Vie et al., 2013, 2015). Logistic regression models were used to predict future award
attainment from baseline PA, NA, and optimism. We did not impute missing data because
our sample size was very large and less than 2% of our sample had missing values for
well-being or other key measures. Gender, age, race/ethnicity, education level, marital status, military rank, prior deployment, Army component, military service length, prior award
attainment, and follow-up length in years were included as control variables.
Quadratic effects for each well-being measure were used to assess nonlinearity, and we
estimated the point on each well-being scale associated with the greatest odds of receiving
an award (see Darlington & Hayes, 2017, p. 356). If the maximum occurs outside the possible 1 to 5 range on a well-being scale, the conclusions are simplified because the direction of the linear trend will apply across the entire range of possible well-being values. In
cases where the maximum occurs inside the possible range, the direction of the linear trend
changes at the maximum, and this necessitates a qualification of the results. To illustrate
the nonlinear relation between award attainment and well-being, we plotted the predicted
probabilities of award attainment across the range of possible well-being values. The linear
and quadratic effects were estimated after mean-centering each well-being measure (see
Darlington & Hayes, 2017, p. 355).
To further explore the data beyond the general regression reported above, we also examined whether the associations were similar across four sets of demographic categories
for which we thought effects could potentially differ: education (< = high school, > high
school), gender (men, women), race/ethnicity (White, Black, Hispanic), and rank (enlisted,
officer) in separate analyses. We included an interaction term for PA with education, gender, race/ethnicity, and rank (separately). These two-way interaction effects were also
examined for NA in separate models. Second, we ran each PA and NA model stratified by
education, gender, race/ethnicity, and rank.
5 Results
5.1 Demographic Characteristics
Over the four-year follow up window, 114,443 soldiers (12.60%) received an award. The
soldiers in this study were fairly young (mean age 29.60 years old; SD = 9.16 years), and
the majority were White (65.46%), male (83.24%), had a high school education or less
(81.06%), and had no previous awards at baseline (86.73%). Approximately half the sample was married (49.54%), active duty (49.73%), and had deployed to a combat zone (e.g.,
Iraq, Afghanistan, etc.) at least once prior to baseline (54.41%). The majority of soldiers
(81%) completed the full four years of follow-up. Relative to the scale midpoints (3), soldiers reported moderate PA (M = 3.75) and optimism (M = 3.72), and low NA (M = 2.23).
Table 2 displays baseline characteristics by award status during follow-up. Award recipients had higher average PA scores (d = 0.159), lower NA scores (d = -0.166), and higher
optimism scores (d = 0.138) than soldiers who did not receive an award. Award recipients
were more likely to have received an award prior to baseline (54.59% vs. 7.31%), be in the
13
Happy Soldiers are Highest Performers
National Guard (66.61% vs. 24.91%), and be White (75.93% vs. 68.52%). Award recipients were more likely to be officers (17.75% vs. 14.79%), college educated (23.56% vs.
22.05%), male (85.78% vs. 82.87%) and have a longer mean follow-up time (3.94 years vs.
3.55 years).
5.2 Associations by Type of Affective Well‑being
Our first set of logistic regression analyses examines the effect of eight different measures of affective well-being on subsequent award attainment. The All Awards category
was the outcome variable in these analyses.
5.2.1 PA
We observed modest and statistically significant positive linear effects of general PA
(OR = 1.12, 95% CI [1.11,1.13], p < 0.001), high arousal PA (OR = 1.11, 95% CI [1.10,
1.12], p < 0.001), and low arousal PA (OR = 1.09, 95% CI [1.08, 1.11], p < 0.001) on
subsequent award attainment, after controlling for demographic and military covariates
(Table 3). Statistically significant (p < 0.001) quadratic effects were detected, but the estimated maximums for all three measures of positive affect occurred outside the range of
observed well-being scores (Fig. 1). Thus, the observed positive linear effects hold across
all values of the three PA measures.
5.2.2 NA
We observed modest and statistically significant negative linear effects of general NA
(OR = 0.87, 95% CI [0.86, 0.88], p < 0.001, high arousal NA (hostility and anxiety)
(OR = 0.91, 95% CI [0.90, 0.92], p < 0.001), and low arousal NA (sadness) (OR = 0.91,
95% CI [0.90, 0.92], p < 0.001) on subsequent award attainment, after controlling for
demographic and military covariates (Table 3). Statistically significant (p < 0.001) quadratic effects were detected and the estimated maximums occurred outside the range of negative affect measures except for general NA. For general NA, the maximum occurred at
NA = 1.30, with a slight increase in the odds of an award occurring between NA = 1 and
NA = 1.30, followed by a decrease in the odds of receiving an award between NA = 1.30
and NA = 5 (Fig. 1).
5.2.3 Optimism
Similar to PA and NA, we observed a modest and statistically significant positive linear
effect of optimism on award attainment after controlling for demographic and military
covariates (OR = 1.10, 95% CI [1.09, 1.11], p < 0.001); see Table 3. A statistically significant (p < 0.001) quadratic effect also was detected. The maximum occurred at optimism = 4.38, such that award attainment increased between optimism values of 1 and 4.38
and then slightly decreased for optimism values of 4.38 to 5 (Fig. 1).
We also examined the unique effects of general PA, general NA, and optimism on subsequent All Awards attainment by including all three of these well-being measures as predictors in a logistic regression model. As expected, NA was inversely correlated with PA
(r = -−.58) and optimism (r = -−.53), whereas PA was positively correlated with optimism
(r = 0.58). The unique linear effects for all three predictors remained statistically significant
13
P. B. Lester et al.
Table 3 Odds ratios (95% CI) and quadratic estimates for associations between well-being and award
attainment
Well-being
measure
All awards (n = 114,443)
Heroism awards (n = 802) Performance awards
(n = 113,641)
OR [95% CI]
Quad
OR [95% CI]
Positive Affect
1.12 [1.11,
1.13]***
High arousal
PA
Low arousal
PA
Negative affect
High arousal
NA
Anger/hostility
Anxiety/
worry
Low arousal
NA
Sadness
Optimism
Quad
OR [95% CI]
Quad
–0.04*** 1.13 [1.02,
1.25]*
–0.07
1.12 [1.11,
1.13]***
–0.04***
1.11 [1.10,
1.12]***
1.09 [1.08,
1.10]***
0.87 [0.86,
0.88]***
–0.03*** 1.10 [1.00,
1.20]*
–0.03*** 1.11 [1.02,
1.21]*
–0.07*** 0.92 [0.82, 1.03]
–0.03
1.11 [1.10,
1.12]***
–0.06 1.09 [1.08,
1.10]***
–0.13* 0.87 [0.86,
0.88]***
–0.03***
0.91 [0.90,
0.92]***
0.95 [0.94,
0.96]***
–0.02*** 1.05 [0.95, 1.16]
–0.06
–0.02***
–0.02*** 0.95 [0.87, 1.04]
0.01
0.91 [0.90,
0.92]***
0.95 [0.94,
0.96]***
0.91 [0.90,
0.92]***
1.10 [1.09,
1.11]***
–0.03*** 0.88 [0.81,
0.96]**
–0.07*** 1.14 [1.04,
1.26]**
–0.03
0.91 [0.90,
0.92]***
1.10 [1.09,
1.11]***
–0.03***
–0.06
–0.03***
–0.07***
–0.02***
–0.07***
All models adjust for gender, age, race/ethnicity, education level, marital status, military rank, prior deployment, Army component, military service length, prior award attainment, and follow-up length. Each wellbeing measure was examined in a separate model. OR = odds ratio; CI = confidence interval; Quad. = quadratic term; PA = positive affect; NA = negative affect. * p < .05, **p < .01, *** p < .001
(p < 0.001) and in the same direction as reported in Table 3: PA was associated with a 5%
increase in odds of obtaining an award (OR = 1.05, 95% CI [1.04, 1.07]), NA was associated with an 8% decrease in odds of obtaining an award (OR = 0.92, 95% CI [0.91, 0.93]),
and optimism was associated with a 3% increase in odds of obtaining an award (OR = 1.03,
95% CI [1.02, 1.04]). Statistically significant quadratic effects were detected for general
PA, general NA, and optimism, however, the linear effects hold over most of the 1 to 5
range of each well-being measure.
The results in Table 3 provide important evidence of external validity. Specifically, the
relation between affective well-being and award attainment can be generalized to general
PA, high arousal PA, low arousal PA, general NA, high arousal NA, low arousal PA, and
optimism.
5.3 Analyses by Type of Award
In the previous logistic regression analyses by type of well-being, the All Awards category was used as the outcome variable. To assess the generalizability of our findings
to specific types of awards, we examined the effects of general PA, general NA, and
13
Happy Soldiers are Highest Performers
Fig. 1 Predicted Probability of Receiving an Award Based on Levels of Three Types of Well-being. Note:
Numbers correspond to the scale value associated with the maximum probability of receiving an award.
Probabilities are calculated for enlisted, active duty, White, married, male soldiers with a high school education or lower, with no prior deployments or awards and who were at the mean for age, service length and
follow-up time
optimism on the attainment of a heroism award and the attainment of a performance
award. A total of 802 heroism awards and 113,641 performance awards were received
during the follow-up years. The results are summarized in Table 3.
5.3.1 Heroism Award
We observed a modest and statistically significant positive linear effect of general PA
on subsequent heroism award attainment, after controlling for demographic and military
covariates (OR = 1.13, 95% CI [1.02, 1.25], p < 0.05). We also observed a modest and statistically significant positive linear effect of optimism on subsequent heroism award attainment, after controlling for demographic and military covariates (OR = 1.14, 95% CI [1.04,
1.26], p < 0.01). NA was not significantly associated with receiving a heroism award.
5.3.2 Performance Award
We observed a modest and statistically significant positive linear effect of general PA on
subsequent performance award attainment, after controlling for demographic and military
covariates (OR = 1.12, 95% CI [1.11, 1.13], p < 0.001). We also observed a modest and
statistically significant positive linear effect of optimism on subsequent performance award
13
P. B. Lester et al.
attainment, after controlling for demographic and military covariates (OR = 1.10, 95% CI
[1.09, 1.11], p < 0.001). We observed a modest and statistically significant negative linear
effect of general NA on subsequent performance award attainment, after controlling for
demographic and military covariates (OR = 0.87, 95% CI [0.86, 0.88], p < 0.001). Statistically significant quadratic effects for general PA, optimism, and general NA were detected,
but the linear effects hold over most of the 1 to 5 range of each well-being measure.
5.4 Analyses by Demographic Subgroups
Additional analyses for All Awards were performed to assess the generality of the results
reported in Table 3 across several demographic subgroups. Interaction effects were added
to the logistic regression models to assess possible moderation effects of education, gender,
race/ethnicity, and rank. No statistically significant interaction effects were found for rank
or gender. Statistically significant but small interaction effects were detected for education
and race/ethnicity.
The size of a moderation effect for a particular demographic factor can be assessed by
comparing the odds ratios within each level of a demographic factor. Table 4 gives the
odds ratios within each level of education, gender, race/ethnicity, and rank. As Table 4
reveals, only very small differences in odds ratios were observed within the levels of each
demographic factor. For example, the largest difference in odds ratios was observed for the
education factor where the relation between general PA and award attainment was slightly
stronger for soldiers with high school education or less (OR = 1.14, 95% CI [1.13, 1.15],
p < 0.001) than soldiers with more than high school education (OR = 1.07, 95% CI [1.05,
Table 4 Odds Ratios (95% CI) and Quadratic Estimates for Associations Separately within Categories of
Education, Gender, Race/Ethnicity, and Rank
Subgroup
Positive Affect
Negative Affect
OR [95% CI]
Quad
OR [95% CI]
Quad
1.14 [1.13, 1.15]***
1.07 [1.05, 1.10]***
– 0.04***
– 0.03*
0.86 [0.85, 0.87]***
0.90 [0.88, 0.92]***
– 0.08***
– 0.05**
1.12 [1.11, 1.14]***
1.11 [1.08, 1.14]***
– 0.05***
– 0.02
0.87 [0.86, 0.88]***
0.90 [0.87, 0.93]***
– 0.08***
– 0.07***
1.12 [1.10, 1.15]***
1.15 [1.11, 1.18]***
1.12 [1.10, 1.13]***
– 0.04***
– 0.06***
– 0.04***
0.90 [0.87, 0.92]***
0.85 [0.82, 0.88]***
0.87 [0.86, 0.88]***
– 0.05**
– 0.08***
– 0.08***
1.13 [1.12, 1.14]***
1.10 [1.07, 1.13]***
– 0.04***
– 0.04**
0.87 [0.86, 0.88]***
0.89 [0.86, 0.92]***
– 0.08***
– 0.05**
Education
Up to a high school diploma
More than high school
Gender
Male
Female
Race/Ethnicity
Black
Hispanic
White, Non-Hispanic
Rank
Enlisted
Officer
All models adjust for gender, age, race/ethnicity, education level, marital status, military rank, prior deployment, Army component, military service length, prior award attainment, and follow-up length
OR odds ratio; CI confidence interval; Quad. quadratic term
*p < .05, ** p < .01, *** p < .001
13
Happy Soldiers are Highest Performers
1.10, p < 0.05). Our moderator analyses indicate that the basic findings reported in Table 3
for general PA and general NA can be generalized across all of the education, gender, race/
ethnicity, and rank subgroups in Table 4.
The probability plots in Figs. 2 and 3 provide additional information regarding the small
moderating effects of education, gender, race/ethnicity, and rank. Note that the probability
curves are approximately parallel for different levels of each demographic factor.
5.5 Strength of Associations
All of the linear effects reported in Table 3 for All Awards are statistically significant at
p < 0.001, but these small p-values are partially due to our large sample size. The odds
ratios reported in Table 3 provide important information regarding the size of the effects.
The odds ratios describe the change in the odds of award attainment associated with a
1-point increase in a well-being predictor variable. For example, OR = 1.12 for general PA
in Table 3 indicates that the odds of award attainment becomes 1.12 times larger for every
1-point increase in PA.
A probability ratio is another way to describe the strength of association between a wellbeing measure and award attainment. For example, the probability of award attainment at
PA = 5 (0.1364) is about two times larger than the probability of award attainment at PA = 1
(0.0632), and the probability of award attainment at NA = 1 (0.1374) is about two times
Fig. 2 Predicted probability of an award per unit increase in positive affect, by (a) education level, b gender,
c race/ethnicity, and d military rank. Note: HS = high school. Probabilities were calculated at the mean for
continuous covariates and at the reference category level (White, married, enlisted, active duty, male, high
school education or less, no prior deployments or awards) for categorical covariates
13
P. B. Lester et al.
Fig. 3 Predicted probability of an award per point increase in average NA, by (a) education level, b gender,
c race/ethnicity, and d military rank. Note: HS = high school. Probabilities were calculated at the mean for
continuous covariates and at the reference category level (White, married, enlisted, active duty, male, high
school education or less, no prior deployments or awards) for categorical covariates
larger than the probability of award attainment at NA = 5 (0.0557). Given the nonlinear
relation between the probability of award attainment and well-being illustrated in Fig. 1,
it is also informative to assess probability ratios for low, moderate, and high values for
well-being. For example, the probability of award attainment at PA = 3 is about 1.64 times
larger than the probability of award attainment at PA = 1, while the probability of award
attainment at PA = 5 is about 1.19 times larger than the probability of award attainment at
PA = 3.
5.6 The Combined Predictive Power of PA and NA
Thus far, the findings presented have highlighted the associations between individual
measures of well-being and subsequent award attainment. It is also important to examine the extent to which leveraging information about both PA and NA can enhance prediction of award attainment. Comparing the percent of soldiers who obtained an award
within specified ranges of well-being measures is one way to investigate this. For example,
we observed nearly a four-fold increase in the percent of soldiers who obtained an award
(3.70% versus 13.78%) when comparing the unhappiest soldiers (high NA [4–5] and low
PA [1–2]) to the happiest soldiers (low NA [1–1.5] and high PA [4.5–5]). This difference
in award attainment between the happiest and unhappiest soldiers translates into a large difference in outstanding performance.
13
Happy Soldiers are Highest Performers
6 Discussion
Several clear findings emerged from our examination of well-being and award attainment
in a large sample of Army personnel. First, most types of positive affective well-being,
both general dimensions and discrete emotions, predicted soldiers receiving both heroism
and performance awards. High PA, low NA, and optimism all uniquely predicted award
attainment, as did low and high arousal PA and discrete types of NA (sadness and hostility/
anger). Worry was a weak predictor. Although sadness and anger predicted fewer awards,
low levels of positive emotions also did so. This indicates that it is not just high negative
feelings that interfere with good performance, but that high positive feelings may boost
performance as well.
The effects we found were small but highly accurate. The three well-being measures are
moderately correlated and have some common overlapping associations with awards, but
each of the three types of well-being significantly predicted award attainment after controlling for the other well-being measures. Thus, our results suggest that low NA, high PA,
and high optimism each uniquely predict a greater odds of superior work performance,
and there was almost four times as many award recipients among soldiers very high versus
low in well-being. This difference is important and especially noteworthy considering that
receiving an Army award was rare, with a base rate of 12.6% across over 900,000 people.
High well-being was associated not only with long-term work performance, as signified by
the correlation with awards for performance, but also with awards for heroism, which are
based on an episode of noteworthy valor in the face of danger.
The predictive power of well-being was generalizable not only across types of wellbeing, but also across two different performance outcomes (performance awards and heroism awards) and a number of different populations (men and women, ethnic groups, more
and less educated soldiers, and officers and enlisted soldiers). Although our sample was
restricted to Army soldiers, it was very diverse in terms of ethnicity, gender, education,
age, and marital status. Thus, we have demonstrated that the predictive association between
well-being and good performance is not restricted to small samples of convenience.
Although a few interaction effects for demographic factors were detected, these effects
were very small and therefore we can make general claims regarding the predictive ability
of well-being on award attainment across all of the demographic factors we examined.
Importantly, in addition to finding that well-being predicts performance, we also found
that well-being most strongly predicts performance between unfavorable and moderate well-being. Within PA, for example, there was a greater increase in the probability of
attaining an award between low (1) and moderate (3) PA, compared to moderate (3) and
high (5) PA (1.64 vs. 1.19 times the probability of an award, respectively). Therefore, interventions targeting soldiers with low, rather than moderate, PA may yield the greatest benefit. Conversely, we observed a greater decrease in the probability of an award between high
(5) and moderate (3) NA, compared to moderate (3) and low (1) NA (0.47 vs. 0.83 times
the probability of receiving an award, respectively). Thus, affect is more strongly related
to award attainment when going from unfavorable (i.e., low PA or high NA) to moderate
affect, rather than moderate to favorable (i.e., high PA, low NA) affect. These patterns are
in accord with the suggestion that occasional NA might be adaptive and functional (e.g.,
Kashdan & Biswas-Diener, 2014; Oishi et al., 2007), and that extremely high PA and no
NA is not necessarily required for effective functioning. Thus, successful workers are substantially less likely to be unhappy individuals, but moderate happiness was sufficient in
our study to produce most of the benefits.
13
P. B. Lester et al.
6.1 Integration and Additional Contributions
We cannot firmly establish causality with certainty with the current data. However, the predictive temporal association of well-being with awards, with the relationships persisting in
spite of a number of statistical controls of other potential explanatory variables, increases
our confidence in the likelihood of the causal effect. Furthermore, many soldiers received
awards who had not previously done so, and this disconfirms the explanation that it is simply positive responses to awards that predict awards only, because soldiers who earn one
are more likely to earn another. However, strong confirmation of the causal influence moving from affective well-being to performance comes from other studies, recalling that the
major goal of the present study was to test the generality and nature of the association, not
causal direction.
Thus, it is important to consider the findings from the current study within the context of
other research. In the empirical literature, there are some experimental studies that indicate
causality moving from well-being to work performance (Bellet et al., 2019; Oswald et al.,
2015). Beyond experimental studies, there are also longitudinal studies suggesting that
well-being precedes work performance and income (Diener et al., 2002; Luhmann et al.,
2012). Likewise, several studies examine the “Why?”, or more specifically the sequences
within the causal relationship. For example, research shows that good work performance is
often preceded by certain affective states and behaviors (De Neve et al., 2013; Diener et al.,
2015; Lyubomirsky et al., 2005), such as good health (Diener et al., 2017a, 2017b; Pressman & Cohen, 2005), supportive social relationships (Diener & Seligman, 2002), creativity (Isen & Daubman, 1987), goal pursuit (Taquet et al., 2016) and prosocial behavior
(Kushlev et al., 2020). Thus, a variety of affective states and behavioral characteristics help
explain why happier workers tend to show better performance. Taken together, the present
study thematically reinforces much of this research, and does so at scale.
One of the more significant findings in the present study is the curvilinear relationship
between affective well-being and performance. Such curvilinear effects are often difficult
to establish because they require very large sample sizes to establish the effects with confidence. There are theoretical reasons why the most beneficial effects of affective well-being
might not occur at the highest levels of positive feelings in the absence of negative feelings.
Negative emotions can be adaptive in some situations, and in some cases, are even associated with better performance (Parrott, 2014). Tamir and Ford (2012) found that people who
wanted to feel more anger when it was useful reported higher well-being. Negative emotions can help people focus attention on a problem and conserve resources when needed,
for example. It follows that the greatest benefits might not come from very high PA with
virtually no NA. Instead, it might be that in many situations, moderate intensity affective
well-being is most beneficial.
Additionally, the present study offers important methodological implications when
studying the link between well-being and performance. As we have previously noted, the
large sample aides in establishing effect accuracy across several demographics and work
domains. Thus, the present study serves as a sampling and effects benchmark for future
research.
6.2 Limitations, Future Research Directions, and Implications for Practice
While this study helps to answer several lingering questions about well-being and optimism, there are important limitations that warrant mention. As previously described, while
13
Happy Soldiers are Highest Performers
the longitudinal nature of the data addresses temporal concerns, and the objectivity of
receiving an award negates concerns of single-source reporting bias common in psychological research, we cannot conclude from the current findings that well-being and optimism
caused deserving soldiers to receive an award. At best, we can say that high levels of wellbeing and optimism raise the likelihood that one would receive an award. While it does
not appear that the relationship between well-being and performance turns asymptotic, this
may be due to range restriction in the PANAS.
Future empirical research should examine these issues and others. For example, one
important area that should be more closely scrutinized is the relationship between wellbeing, optimism, and heroism. While it is true that our data suggest that there is a relationship between well-being, optimism, and heroism awards, we do not believe that positive emotions measured today would drive discrete heroic behavior observed a year from
now. Rather, perhaps positive emotions covary with deeper psychological constructs, virtues such as courage, that may later drive heroic behavior. Or, perhaps those with a high
degree of positive affect are seen in a different light by those making decisions about who
is nominated for and ultimately receives a heroism award. As highlighted earlier in the
paper, nominating a soldier for an award requires effort—and significant effort for heroism
awards—which raises the possibility that leaders are willing to go the extra mile to ensure
that positive and optimistic soldiers are recognized for their heroism, at least more so than
soldiers who display negative emotions and are generally pessimistic.
An important practical implication of this study’s findings is that organizations might
consider well-being in their hiring decisions. Prescreening potential workers’ well-being
could help employers rule out applicants with very low well-being. Seeking very, as
opposed to moderately happy workers, however, might not produce as many gains. Alternatively, enlightened companies may strive to create workplace conditions that produce
happy workers. Whatever the strategies used, high well-being appears to be conducive to
exemplary work performance.
7 Conclusion
The present study takes an important step forward in accurately depicting the strength of
relationship between well-being, optimism, and objective performance. Likewise, it does
so at scale and across several demographics, while also depicting how well-being and optimism depart from linearity when predicting performance. In sum, while there are many
factors that are influential in exceptional performance within a work context, this study
shows that well-being and optimism matter greatly.
Declarations
Conflicts of interest We have no conflicts of interest to disclose.
Ethical approval This research complied with all ethical standards and was approved by a university and a
U.S. Army Institutional Review Board. All data used in this study were from participants who consented to
allow their data to be used for research purposes.
13
P. B. Lester et al.
References
Bellet, C., De Neve, J-E., & Ward, G, Does (2019). Happiness have an Impact on Productivity? Saïd Business School WP 2019–13, Available at SSRN: https://ssrn.com/abstract=3470734 or https://doi.org/
10.2139/ssrn.3470734
Brown, J. D., & Marshall, M. A. (2001). Great expectations: Optimism and pessimism in achievement settings. In E. C. Chang (Ed.), Optimism & pessimism: Implications for theory, research, and practice
(pp. 239–255). American Psychological Association.
Bunderson, J. S., & Sutcliffe, K. M. (2003). Management team learning orientation and business unit performance. Journal of Applied Psychology, 88, 552–560.
Carpini, J. A., Parker, S. K., & Griffin, M. A. (2017). A look back and a leap forward: A review and synthesis of the individual work performance literature. Academy of Management Annals, 11(2), 825–885.
Carver, C., Scheier, M., Miller, C., & Fulford, D. (2009). Optimism. In C. Snyder & S. Lopez (Eds.), Oxford
handbook of positive psychology (pp. 303–311). Oxford University Press.
Carver, C. S., Scheier, M. F., & Segerstrom, S. C. (2014). Optimism. Clinical Psychology Review, 30(7),
879–889. https://doi.org/10.1016/j.cpr.2010.01.006
Cheong, M., Yammarino, F. J., Dionne, S. D., Spain, S. M., & Tsai, C. Y. (2019). A review of the effectiveness of empowering leadership. The Leadership Quarterly, 30(1), 34–58.
Choi, H., Diener, E., Sim, J. H., & Oishi, S. (2020). Happiness is associated with successful living across
cultures. Manuscript submitted for publication.
Darlington, R. B., & Hayes, A. F. (2017). Regression analysis and linear models: Concepts, applications
and implementation. Guilford.
De Neve, J-E., Diener, E., Tay, L., & Xuereb, C. (2013), The objective benefits of subjective well-being).
In J. Helliwell, R. Layard, & J. Sachs (Eds.). World Happiness Report 2013. UN Sustainable Development Solutions Network., Available at SSRN: https://ssrn.com/abstract=2306651
Diener, E., Nickerson, C., Lucas, R. E., & Sandvik, E. (2002). Dispositional affect and job outcomes. Social
Indicators Research, 59, 229–259.
Diener, E., Lucas, R. E., Oishi, S., Hall, N., & Donnellan, M. B. (2018). Advances and open questions in the
science of subjective well-being. Collabra: Psychology, 4(1).
Diener, E., Heintzelman, S. J., Kushlev, K., Tay, L., Wirtz, D., Lutes, L. D., & Oishi, S. (2017a). Findings
all psychologists should know from the new science on subjective well-being. Canadian Psychology/
psychologie Canadienne, 58, 87–104.
Diener, E., Kanazawa, S., Suh, E. M., & Oishi, S. (2015). Why people are in a generally good mood. Personality and Social Psychology Review, 19, 235–256. https://doi.org/10.1177/1088868314544467
Diener, E., Pressman, S., Hunter, J., & Delgadillo-Chase, D. (2017b). If, why, and when subjective wellbeing influences health, and future needed research. Applied Psychology: Health and Well-Being, 9(2),
133–167.
Diener, E., & Seligman, M. E. P. (2002). Very happy people. Psychological Science, 13, 81–84.
DiMaria, C. H., Peroni, C., & Sarracino, F. (2020). Happiness matters: Productivity gains from subjective
well-being. Journal of Happiness Studies, 21(1), 139–160.
Open Science Collaboration. (2015). Estimating the reproducibility of psychological science. Science.
https://doi.org/10.1126/science.aac4716
Flynn, F. J. (2003). How much should I give and how often? The effects of generosity and frequency of
favor exchange on social status and productivity. Academy of Management Journal, 46, 539–553.
Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden-and-build
theory of positive emotions. American Psychologist, 56, 218–226.
Frese, M., & Fay, D. (2001). Personal initiative: An active performance concept for work in the 21st century.
Research in Organizational Behavior, 23, 133–187.
Fujita, F., Diener, E., & Sandvik, E. (1991). Gender differences in negative affect and well-being: The case
for emotional intensity. Journal of Personality and Social Psychology, 61(3), 427–434.
Grant, A. M., & Schwartz, B. (2011). Too much of a good thing: The challenge and opportunity of the
inverted U. Perspectives on Psychological Science, 6(1), 61–76.
Greenhaus, J. H., & Parasuraman, S. (1993). Job performance attributions and career advancement prospects: An examination of gender and race effects. Organizational Behavior and Human Decision
Processes, 55(2), 273–297.
Haaga, D. A. F., & Stewart, B. L. (1992). Self-efficacy for recovery from a lapse after smoking cessation. Journal of Consulting and Clinical Psychology, 60, 24–28.
Hmieleski, K. M., & Baron, R. A. (2009). Entrepreneurs’ optimism and new venture performance: A
social cognitive perspective. Academy of Management Journal, 52(3), 473–488.
13
Happy Soldiers are Highest Performers
Iaffaldano, M. T., & Muchinsky, P. M. (1985). Job satisfaction and job performance: A meta-analysis.
Psychological Bulletin, 97, 251–273.
Isen, A. M., Daubman, K. A., & , G. P. . (1987). Positive affect facilitates creative problem solving.
Journal of Personality and Social Psychology, 52(6), 1122–1131.
Izard, C. E. (1997). Emotions and facial expressions: A perspective from Differential Emotions Theory. In J. A. Russell & J. M. Fernández-Dols (Eds.), Studies in emotion and social interaction, 2nd
series. The psychology of facial expression (p. 57–77). Cambridge University Press; Editions de la
Maison des Sciences de l’Homme. https://doi.org/10.1017/CBO9780511659911.005
Jensen, S. M., Luthans, K. W., Lebsack, S. A., & Lebsack, R. R. (2007). Optimism and employee performance in the banking industry. Journal of Applied Management and Entrepreneurship, 12(3),
57–72.
Judge, T. A., Piccolo, R. F., Podsakoff, N. P., Shaw, J. C., & Rich, B. L. (2010). The relationship between pay
and job satisfaction: A meta-analysis of the literature. Journal of Vocational Behavior, 77, 157–167.
Judge, T. A., Thoreson, C. J., Bono, J. E., & Patton, G. K. (2001). The job satisfaction-job performance
relationship: A qualitative and quantitative review. Psychological Bulletin, 127, 376–407. https://
doi.org/10.1037//0033-2909.127.3.376
Kaplan, S., Bradley, J. C., Luchman, J. N., & Haynes, D. (2009). On the role of positive and negative affectivity in job performance: A meta-analytic investigation. Journal of Applied Psychology,
94(1), 162–176.
Kashdan, T. B., & Biswas-Diener, R. (2014). The upside of the dark side. Hudson Street Press.
Kashdan, T. B., & Roberts, J. E. (2004). Trait and state curiosity in the genesis of intimacy: Differentiation from related constructs. Journal of Social and Clinical Psychology, 23, 792–816.
Kushlev, K., Heintzelman, S. J., Lutes, L. D., Wirtz, D., Kanippayoor, J. M., Leitner, D., & Diener, E.
(2020). Does happiness improve health? Evidence from a randomized controlled trial. Psychological Science, 31(7), 807–821.
Le, H., Oh, I. S., Robbins, S., Ilies, R., & Westrick, P. (2011). Too Much of a Good Thing: Curvilinear Relationships Between Personality Traits and Job Performance. Journal of Applied Psychology,
96(1), 113–133.
Lucas, R. E., & Diener, E. (2003). The happy worker: Hypotheses about the role of positive affect in
worker productivity. In M. R. Barrick & A. M. Ryan (Eds.), Personality and work: Reconsidering
the role of personality in organizations (pp. 30–59). Jossey Bass.
Luhmann, M., Lucas, R. E., Eid, M., & Diener, E. (2012). The prospective effect of life satisfaction on
life events. Social Psychological and Personality Science, 4(1), 39–45.
Luthans, K. W., Lebsack, S. A., & Lebsack, R. R. (2008). Positivity in healthcare: Relation of optimism
to performance. Journal of Health Organization and Management, 22(2), 178–188.
Lyubomirsky, S., King, L., & Diener, E. (2005). The benefits of frequent positive affect: Does happiness
lead to success? Psychological Bulletin, 131, 803–855. https://doi.org/10.1037/0033-2909.131.6.803
Meisenberg, G., & Woodley, M. A. (2015). Gender differences in subjective well-being and their relationships with gender equality. Journal of Happiness Studies, 16(6), 1539–1555.
Moon, H. (2001). The two faces of conscientiousness: Duty and achievement striving in escalation of
commitment dilemmas. Journal of Applied Psychology, 86, 533–540.
Oishi, S., Diener, E., & Lucas, R. E. (2007). The optimum level of well-being: Can people be too happy?
Perspectives on Psychological Science, 2(4), 346–360. https://doi.org/10.1111/j.1745-6916.2007.
00048.x
Oswald, A. J., Proto, E., & Sgroi, D. (2015). Happiness and productivity. Journal of Labor Economics,
33(4), 789–822.
Parrott, W. G. (2014). The positive side of negative emotions. Guilford Press.
Peterson, C., Park, N., & Castro, C. A. (2011). Assessment for the US Army Comprehensive Soldier Fitness
program: The Global Assessment Tool. American Psychologist. https://doi.org/10.1037/a0021658
Pierce, J. R., & Aguinis, H. (2013). The too-much-of-a-good-thing effect in management. Journal of
Management, 39(2), 313–338.
Pressman, S. D., & Cohen, S. (2005). Does positive affect influence health? Psychological Bulletin, 131,
925–971. https://doi.org/10.1037/0033-2909.131.6.925
Rasmussen, H., Scheier, M., & Greenhouse, J. (2009). Optimism and physical health: A meta-analytic
review. Annals of Behavioral Medicine, 37, 239–256.
Russell, J. A. (2003). Core affect and the psychological construction of emotion. Psychological Review,
110(1), 145–172. https://doi.org/10.1037/0033-295x.110.1.145
Scheier, M. F., Carver, C. S., & Bridges, M. W. (1994). Distinguishing optimism from neuroticism (and trait
anxiety, self-mastery, and self-esteem): A reevaluation of the Life Orientation Test. Journal of Personality and Social Psychology, 67, 1063–1078. https://doi.org/10.1037/0033-2909.131.6.925
13
P. B. Lester et al.
Seligman, M. E., & Schulman, P. (1986). Explanatory style as a predictor of productivity and quitting
among life insurance sales agents. Journal of Personality and Social Psychology, 50(4), 832–838.
Shockley, K. M., Ispas, D., Rossi, M. E., & Levine, E. L. (2012). A meta-analytic investigation of the relationship between state affect, discrete emotions, and job performance. Human Performance, 25(5),
377–411.
Srivastava, S., McGonigal, K. M., Richards, J. M., Butler, E. A., & Gross, J. J. (2006). Optimism in close
relationships: How seeing things in a positive light makes them so. Journal of Personality and Social
Psychology, 91(1), 143–153.
Sturman, M. C. (2003). Searching for the inverted U-shaped relationship between time and performance:
Meta-analyses of the experience/performance, tenure/performance, and age/performance relationships.
Journal of Management, 29, 609–640.
Tamir, M., & Ford, B. Q. (2012). Should people pursue feelings that feel good or feelings that do good?
Emotional preferences and well-being. Emotion, 12, 1061–1070. https://doi.org/10.1037/a0027223
Taquet, M., Quoidbach, J., Montjoye, Y., Desseilles, M., & Gross, J. J. (2016). Hedonism and the choice of
everyday activities. Proceedings of the National Academy of Sciences of the United States of America,
113(35), 9769–9773. https://doi.org/10.1073/pnas.1519998113
Tenney, E. R., Logg, J. M., & Moore, D. A. (2015). (Too) optimistic about optimism: The belief that optimism improves performance. Journal of Personality and Social Psychology, 108(3), 377–399.
Tenney, E. R., Poole, J. M., & Diener, E. (2016). Does positivity enhance work performance?: Why, when,
and what we don’t know. Research in Organizational Behavior, 36, 27–46. https://doi.org/10.1016/j.
riob.2016.11.002
Trevino, L. K., Hartman, L. P., & Brown, M. (2000). Moral person and moral manager: How executives
develop a reputation for ethical leadership. California Management Review, 42(4), 128–142.
U.S. Department of Defense (2020, August 18). U.S. military awards for valor—Top 3. https://valor.defen
se.gov/
Van Katwyk, P. T., Fox, S., Spector, P. E., & Kelloway, E. K. (2000). Using the job-related affective wellbeing scale (JAWS) to investigate affective responses to work stressors. Journal of Occupational
Health Psychology, 52, 219–230.
Vie, L. L., Scheier, L. M., Lester, P. B., Ho, T. E., Labarthe, D. R., & Seligman, M. E. P. (2015). The US
army person-event data environment: A military-civilian big data enterprise. Big Data, 3(2), 67–79.
https://doi.org/10.1089/big.2014.0055
Vie, L. L., Scheier, L. M., Lester, P. B., & Seligman, M. E. P. (2016). Initial validation of the US army
global assessment tool. Military Psychology, 28(6), 468–87. https://doi.org/10.1037/mil0000141
Vie, L. L., Griffith, K. N., Scheier, L. M., Lester, P. B., & Seligman, M. E. P. (2013). The Person-Event Data
Environment (PDE): Leveraging big data for studies of psychological strengths in soldiers. Frontiers in
Psychology, 4, 934. https://doi.org/10.3389/fpsyg.2013.00934
Waldman, D. A., & Avolio, B. J. (1991). Race effects in performance evaluations: Controlling for ability,
education, and experience. Journal of Applied Psychology, 76(6), 897–901.
Watson, D., & Clark, L.A. (1994). The PANAS-X: Manual for the Positive and Negative Affect ScheduleExpanded Form. University of Iowa.
Wright, T. A., Cropanzano, R., & Bonett, D. G. (2007). The moderating role of employee positive wellbeing on the relation between job satisfaction and job performance. Journal of Occupational Health
Psychology, 12, 93–104.
Youssef, C. M., & Luthans, F. (2007). Positive organizational behavior in the workplace: The impact of
hope, optimism, and resilience. Journal of Management, 33(5), 774–800.
Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and
institutional affiliations.
13
International Journal of
Environmental Research
and Public Health
Article
The Happy-Productive Worker Model and Beyond:
Patterns of Wellbeing and Performance at Work
José M. Peiró 1, * , Malgorzata W. Kozusznik 2 , Isabel Rodríguez-Molina 3
1
2
3
*
and Núria Tordera 3
IDOCAL (Institut d’Investigació en Psicologia del RRHH, del Desenvolupament Organitzacional i de la
Qualitat de Vida Laboral), Universitat de València & IVIE, Avda. Blasco Ibáñez 21, 46010 Valencia, Spain
Research Group for Work, Organizational and Personnel Psychology (WOPP), Katholieke Universiteit
Leuven, Dekenstraat 2, 3000 Leuven, Belgium; gosia.kozusznik@kuleuven.be
IDOCAL (Institut d’Investigació en Psicologia del RRHH, del Desenvolupament Organitzacional i de la
Qualitat de Vida Laboral), Universitat de València, Avda. Blasco Ibáñez 21, 46010 Valencia, Spain;
isabel.rodriguez@uv.es (I.R.-M.); nuria.tordera@uv.es (N.T.)
Correspondence: jose.m.peiro@uv.es; Tel.: +34-963-864-689
Received: 27 December 2018; Accepted: 3 February 2019; Published: 6 February 2019
!"#!$%&'(!
!"#$%&'
Abstract: According to the happy-productive worker thesis (HPWT), “happy” workers perform
better than “less happy” ones. This study aimed to explore the different patterns of relationships
between performance and wellbeing, synergistic (i.e., unhappy-unproductive and happy-productive)
and antagonistic (i.e., happy-unproductive and unhappy-productive), taking into account
different operationalizations of wellbeing (i.e., hedonic vs. eudaimonic) and performance
(i.e., self-rated vs. supervisors’ ratings). It also explored different demographic variables
as antecedents of these patterns. We applied two-step cluster analysis to the data of 1647
employees. The results indicate four different patterns—happy-productive, unhappy-unproductive,
happy-unproductive, and unhappy-productive—when performance is self-assessed, and three when
it is assessed by supervisors. On average, over half of the respondents are unhappy-productive or
happy-unproductive. We used multidimensional logistic regression to explain cluster membership
based on demographic covariates. This study addresses the limitations of the HPWT by including
both the hedonic and eudaimonic aspects of wellbeing and considering different dimensions and
sources of evaluation. The “antagonistic” patterns identify employees with profiles not explicitly
considered by the HPWT.
Keywords: occupational wellbeing; performance; happy-productive worker
1. Introduction
Wellbeing at work can be conceptualized from two distinct perspectives based on different
philosophical traditions: the hedonic view of pleasure and experience of positive affect [1] and
the eudaimonic view of wellbeing as personal growth and a sense of meaning [2]. Therefore,
wellbeing can be understood as having both pleasurable (or hedonic) and meaningful (or eudaimonic)
components [3–6]. However, the majority of the research has studied wellbeing from the hedonic
perspective, conceptualizing wellbeing as judgments and evaluations of satisfaction with some of life’s
facets (e.g., job satisfaction).
According to the happy-productive worker thesis, “happy” workers should have better
performance than “less happy” ones [7,8], and the quality of task performance can be influenced by
the coexisting affective states [9]. This thesis has produced a series of studies [10,11] and meta-analytic
research, often providing ambiguous and inconclusive results [8,12].
On the one hand, some research shows that wellbeing can predict performance. For example,
studies show that when people are more satisfied with their jobs, they show higher performance [13,14].
Int. J. Environ. Res. Public Health 2019, 16, 479; doi:10.3390/ijerph16030479
www.mdpi.com/journal/ijerph
Int. J. Environ. Res. Public Health 2019, 16, 479
2 of 20
In addition, higher positive affect has been shown to predict performance quality [15]. Furthermore,
when people are more satisfied with their jobs, they show higher productivity [16] over time.
People who feel better than usual at work have been found to make more effort on their tasks [17,18]
and achieve a higher level of task performance [19]. In this direction, feeling active and enthusiastic in
the morning has been shown to increase levels of creativity during the day [20]. Finally, positive affect
has been shown to predict performance quality [21]. All these results support the HPWT, which posits
that workers with higher levels of wellbeing also tend to show better performance at work, compared
to workers with lower levels of wellbeing.
On the other hand, empirical studies and meta-analyses have found the relationships between
performance and job satisfaction to be spurious [22] or weak [23]. Some scholars view the connections
between happiness and job performance as questionable [7], suggesting an apparently low and
non-significant satisfaction–performance relationship [24]. This can be reflected by the fact that most
studies that consider job satisfaction and job performance treat them as separate variables that are not
directly related to each other [24]. For example, Greenberger, Strasser, Cummings, and Dunham [25]
studied the causal relationship between personal control and job satisfaction, and between personal
control and job performance, but they did not assume or investigate the relationship between job
satisfaction and job performance [24]. There is a need to address this ambiguity in the research, and
for this reason we consider it necessary to revisit and expand the happy-productive worker thesis.
Some Limitations of the Happy-Productive Worker Thesis
The ambiguity in the studies on the HPWT can be explained in part by the limitations of these
studies [26]. First, they focus on hedonic constructs of wellbeing at the expense of eudaimonic
wellbeing. In fact, most of the research has studied wellbeing from the hedonic perspective,
understanding it as global evaluations of satisfaction (e.g., job satisfaction). More recently, valuable
studies have revisited the thesis of the happy and productive worker, studying the possibility of
expanding it conceptually to include affect [7] or alternative relationships between satisfaction
and performance [8] by evaluating affective wellbeing, both as a state and a trait [19]. However,
this thesis has not been extended to consider key wellbeing constructs, such as its eudaimonic
dimension, which involves purpose and personal growth. Wellbeing has also been conceptualized
as an eudaimonic experience of meaning at work and purpose in life [27]. This conceptualization of
subjective wellbeing can be reflected in the recent progress in its measures [28], which distinguish
between activities that people consider ‘pleasurable’ as opposed to the ‘worthwhileness’ or meaning at
work associated with these activities [2,29,30]. Although few studies have investigated the relationship
between eudaimonic wellbeing and performance [31], some research suggests that this relationship
exists. For example, Niessen et al. [32] demonstrated that, on days when employees had increased
perceived meaning at work, they reported being more focused on tasks and behaving in a more
exploratory way, compared to days when they evaluated their work as less meaningful to them.
A second limitation is that, in the study of the relationship between happiness and productivity,
little attention is paid to a precise operationalization of productivity, and even its operationalization
as job performance is far from systemic and comprehensive in terms of its dimensions or facets
(e.g., in-role performance, extra-role performance, creative performance). Job performance can be
understood as “a function of a person’s behavior and the extent to which that behavior helps an
organization to reach its goals” [33] (p. 187). However, there is considerable debate about what
work performance is. Koopmans and colleagues [34], in their systematic review, observe that,
according to different studies on work performance, it can be conceptualized using the following
broad dimensions: task performance, contextual performance, and counter-productive behavior.
Task or in-role performance is intrinsically related to the activities included in the job description.
Contextual performance refers to behaviors that are not directly related to the activities included in the
job description. Organizational citizenship overlaps with the definitions of contextual performance
and refers to helping others at work in the social and psychological context, thus promoting task
Int. J. Environ. Res. Public Health 2019, 16, 479
3 of 20
performance [35]. Counterproductive work behaviors include behaviors such as absenteeism, theft,
and substance abuse. Furthermore, creativity [36] and innovation [37] have been pointed out as
another important aspect of job performance. Several authors suggest conceptualizing job performance
using a broader theoretical framework, in order to mitigate error sources and find relationships
between performance and job satisfaction [38]. In the present study, we incorporate different aspects
of performance (in-role, organizational citizenship, and creative performance) in a global measure.
Performance evaluations may come from different sources (e.g., self-assessed, supervisor, peers,
customers, etc.). It is necessary to complement the employees’ self-rated performance assessment with
the supervisors’ evaluation of their performance in order to avoid employee leniency or self-deception
in self-ratings, which has been shown to be particularly prominent in overall or general performance
assessments [39]. By including supervisors’ evaluations of their employees’ performance levels, we
make sure that we are using evaluations that have been shown to have the highest mean reliability, as
found in a meta-analysis by Conway and Huffcutt [40]. Therefore, the present study, in addition to
employees’ self-ratings of their own performance, includes information about their performance from
their direct supervisors.
A third limitation lies in the fact that most organizational research has studied “happiness” as an
antecedent of “productivity”, and only a few studies have looked for the inverse relationship [24,31].
However, there is evidence suggesting that work performance can explain wellbeing indicators.
For example, evidence shows that self-rated performance predicts an increase in dedication and a
decrease in emotional exhaustion over time [41]. Moreover, performance [42,43] and the experience
of making progress toward one’s goals at work [44–46] have been shown to predict positive affective
states. Additionally, studies have shown that personal initiative is positively related to an increase in
work engagement over time [47]. Along the same lines, there is evidence that on days when employees
were strongly focused on tasks at work, they also exhibited more vitality and learning than on days
when they were weakly focused on their tasks [32].
A fourth limitation is that the studies from both the happy-productive and productive-happy
approaches have assumed positive linear relationships, although other patterns of relations may exist,
especially those that establish negative relationships between these two variables. These complex and
alternative relations between these constructs require taking into consideration different configurations
or patterns of these relationships, instead of analyzing them sequentially. In fact, the studies carried
out within the happy productive thesis emphasize the results that confirm this thesis. These studies
tend to especially explore the synergistic side of the model that produces a win-win situation for
employers and employees (happy and productive), while disregarding the antagonistic or win-lose
relations (happy and unproductive or unhappy and productive). However, some studies suggest that
we should pay more attention to these antagonistic relations, showing, for instance, that difficulty in
remembering information and poor task performance can be considered negative consequences of
being “happy” at work [48]. Furthermore, other authors provide evidence of the benefits of negative
affect on creative performance [49]. Based on this research, Peiró et al. [26] proposed the need to attend
to not only the synergetic relations between performance and wellbeing, but also to the antagonistic
ones, thus extending the propositions of the HWPW. They proposed the coexistence of four patterns of
relationships between performance and wellbeing: “happy-productive”, “unhappy-unproductive”,
“happy-unproductive”, and “unhappy-productive”. In fact, Ayala et al. [50] found support for these
different types of patterns when considering job satisfaction and innovative performance in young
employees. Moreover, they found that almost 15% of a sample of Spanish young employees fell
in the group of unhappy-productive (about 9%) or the group of happy-unproductive (more than
5%). Acknowledging that the correlations between happiness and productivity are moderated, it is
important to focus on the different groups of workers according to their profiles. In order “to learn
more about individuals who are outside the hypothesized pattern . . . , it is now desirable to investigate
additional measures of wellbeing and performance and identify situational and personal features
associated with membership in each cluster” [51] (p. 12).
Int. J. Environ. Res. Public Health 2019, 16, 479
4 of 20
In order to overcome the limitations of the research mentioned above, in the present study,
we address them by revisiting the happy-productive worker, incorporating both the hedonic and
eudaimonic components of wellbeing and considering different aspects of job performance as well
as different evaluation sources. In addition, in this study, we consider wellbeing and performance
simultaneously, instead of analyzing the sequence between these two constructs. To this end, we
study patterns of wellbeing and performance that serve to integrate these two constructs, taking into
account different operationalizations where neither of them is an antecedent of the other, in order to
identify different patterns of employees, both synergistic (i.e., happy-productive) and antagonistic
(i.e., unhappy-unproductive, happy-unproductive and unhappy-productive). In this way, we aim
to further advance our knowledge in the direction pointed out by Warr and Nielsen [51] when they
proposed identifying situational and personal features associated with membership in each cluster.
More specifically, we formulate the following research questions:
•
•
•
Research Question 1: Do employees show different patterns of relationships between
performance and wellbeing, synergistic (i.e., unhappy-unproductive and happy-productive) and
antagonistic (i.e., happy-unproductive and unhappy-productive), taking into account different
operationalizations of wellbeing (i.e., hedonic vs. eudaimonic) and performance (i.e., self-rated vs.
supervisor ratings)?
Research Question 2: Will the employees remain in the same profile of wellbeing and performance
in their different operationalizations?
Research Question 3: Are there any demographic variables that may play a role as antecedents of
the profiles in the different operationalizations of the “happy-productive” worker?
2. Materials and Methods
2.1. Sample and Procedure
The members of the research team contacted several organizations, inviting them to participate in
the project. Convenience sampling was used, focusing mainly on the services and production sector.
The first contact was made with the general manager or the director of human resources. In a first
meeting, the project, the objectives, the time required, and the procedure were explained to them.
Then, if they agreed, all the workers in the organizations were invited to participate by completing the
questionnaire voluntarily and confidentially.
The sample was composed of 1647 employees (52% women, 43% men, 5% information not
available) from the services (81%) and production/construction (19%) sectors, working in 239 work
units in different Spanish companies. With regard to age, 26% percent of participants were under
35 years old, 55% were between 35 and 50, and 16% were over 50 years old. The majority of the
sample had a university degree (46%) and high school or professional training (37%). The majority
were technicians/administrative workers (46%) and highly qualified professionals (24%). In addition,
62% were permanent workers, and 30% were temporary workers. The majority of the employees had
worked for more than 5 years in their current position (53%). Members of the research team informed
the participants on the purpose of the study, the guarantee of confidentiality and the willfulness of
their participation. Participants expressed their consent to participate. The research protocol was
approved by the Ethics Committee of the University of Valencia.
In this study, we used two types of informants to assess employee performance. First, we asked
the employees to self-evaluate their performance. These ratings were obtained for all the employees.
Second, we asked employees’ direct supervisors to rate the performance of their subordinates.
In this case, performance evaluated by the direct supervisor was only obtained for 915 employees.
Confidentiality of the data was guaranteed.
Int. J. Environ. Res. Public Health 2019, 16, 479
5 of 20
2.2. Measures
Hedonic wellbeing. Hedonic wellbeing was conceptualized as the employee’s job satisfaction,
and it was measured by a 10-item reduced version of the Job Satisfaction Scale (IJSS) by Cooper, Rout
and Faragher [52], referring to intrinsic job satisfaction and extrinsic job satisfaction, and one additional
item measuring general job satisfaction. The score for hedonic wellbeing was the global mean score for
the three types of job satisfaction. It includes items such as “Opportunity to use your skills”. The items
have a seven-point Likert response format, ranging from 1 (quite dissatisfied) to 7 (very satisfied).
Cronbach’s alpha for the global score of Hedonic Wellbeing was 0.87.
Eudaimonic wellbeing. Eudaimonic wellbeing was conceptualized as a feeling of meaning and
purpose at work, and it was measured by an 8-item reduced version of the scale constructed by
Ryff [53], with two subscales: purpose at work and personal growth. The score for eudaimonic
wellbeing was obtained by computing the global mean score for the two dimensions of the scale.
It includes items such as “For me, life has been a continuous process of learning, changing, and
growth”. The items have a seven-point Likert response format, ranging from 1 (strongly disagree) to 7
(strongly agree). Cronbach’s alpha for the global score of eudaimonic wellbeing was 0.72.
Performance—rated by the employee.
Employees’ self-rated work performance was
operationalized as in-role performance (carrying out tasks required by the job), extra-role performance
(carrying out tasks that are not required in the job description, e.g., helping others), and creative
performance (carrying out tasks that are both creative and useful at work). In-role performance was
measured by 3 items from a scale constructed by Williams and Anderson [54], extra-role performance
was measured by 3 items from a scale by Mackenzie and colleagues [55], and creative performance
was measured by a 3-item method constructed by Oldham and Cummings [36]. The composite
score for performance was obtained by calculating the global mean score for the in-role, extra-role,
and creative performance scales. It includes items such as: “I adequately complete assigned duties”
(in-role performance); “I do not hesitate to challenge the opinions of others who I feel are leading the
store/company in the wrong direction” (extra-role performance); and “How original and practical
am I in my work?” The items have a seven-point Likert response format, ranging from 1 (strongly
disagree) to 7 (strongly agree). Cronbach’s alpha for the global work performance score was 0.71.
Performance—rated by the supervisor. Employee work performance evaluated by the supervisor
was also operationalized as a general measure of performance quality. We measured these three aspects
using three items: “What is his/her performance like?”; “What is the quality of his/her work?”; and
“What was his/her level of goal achievement in the past year?” The items have a five-point Likert
response format, ranging from 1 (very bad) to 5 (very good). Cronbach’s alpha for the global work
Performance score was 0.89.
Demographic variables included.
Organization’s sector: dummy variable (0 service,
1 production/construction). Gender: dummy variable (0 female, 1 male). Age: under 35 years
old, between 35 and 50, and over 50 years old. The highest educational level achieved: no education or
compulsory education, professional training or high school, advanced university degree. Occupational
category: unqualified manual work, technician or administrative work, highly qualified professional,
manager. Type of contract: dummy variable (0 = temporary, 1 = permanent). Seniority in the position:
dummy variable (0 = less than 5 years, 1 = more than 5 years).
2.3. Statistical Analysis
The sample was divided into clusters using the two–step cluster analysis method developed by
Chiu and colleagues [56] in SPSS v.22 (IBM Corp., Armonk, NY, USA). The SPSS two-step cluster
method is a scalable cluster analysis algorithm designed to handle large datasets, such as those
analyzed in the present study. The algorithm is based on a two–stage approach: in the first stage, it
undertakes a similar procedure to the k-means algorithm. In the second step, based on these results,
a modified hierarchical agglomerative clustering procedure is carried out that combines the objects
sequentially to form homogenous clusters [57].
Int. J. Environ. Res. Public Health 2019, 16, 479
6 of 20
The two-step clustering algorithm output offers fit information, such as the Bayesian Information
Criterion (BIC), as well as information about the importance of each variable for the construction
of a specific cluster [57], which is an additional attractive feature of the two-step cluster method in
comparison with traditional clustering methods. Empirical results indicate that the two-step clustering
method shows a near-perfect ability to detect known subgroups and correctly classify individuals
into these subgroups [58]. Based on these analyses, the sample was classified into groups reflecting
different configurations of wellbeing and performance dimensions.
After finding cluster solutions for each of the combinations of variables of interest, we applied
multidimensional logistic regression to explain cluster membership based on the demographic
covariates described. Multinomial logistic regression is a statistical technique that specifies the
dependent variable as a categorical variable that can take more than two values (in our case, the
number of clusters). In multinomial logistic regression, one of the responses is chosen to serve
as reference. Switching the reference group allowed us to compare the effects on all the groups.
The independent variables are also categorical, with K categories. They are introduced in the model
coded as k-1 binary variables. When the variables have two categories, they have been introduced as
a dummy variable with a value of 0 or 1. In this case, the exponential beta coefficient represents the
change in the odds of the dependent variable, associated with a one-unit change in the corresponding
independent variable. When the variables have more than two categories, the coding system used is
deviation coding. In this case, because there is no clear reference category, the reference category is
coded as 1. This coding system compares the mean of the dependent variable for a given level to the
mean of the dependent variable for the other levels of the variable. The exponential beta coefficient
estimates the magnitude at which the probability of the occurrence of the event varies, comparing that
category to the average of all the subjects in the study. Because the analysis does not show results for
the reference group, we have repeated the analysis using the coding system with a different group as
reference. With this system, we can obtain the coefficients for all the categories, which are presented in
the results tables.
3. Results
3.1. Descriptive Analysis
The descriptive results are shown in Tables 1 and 2.
Table 1. Descriptive statistics (demographic variables).
Variables
%
Sector
service
production
81
19
Gender
female
male
52
43
<35 years
35–50 years
>50 years
26
55
16
Age
Educational level
No education or compulsory
Professional training or high school
University degree
14
37
46
Int. J. Environ. Res. Public Health 2019, 16, 479
7 of 20
Table 1. Cont.
Variables
%
Occupational category
Unqualified manual work
Technician or administrative
Highly qualified professional
Manager
10
46
24
Type of contract
temporary
permanent
30
62
Seniority in the position
<5 years
>5 years
40
53
Table 2. Descriptive statistics.
Feature
Mean
Standard Deviation (SD)
Hedonic wellbeing
Eudaimonic wellbeing
Performance rated by the employee
Performance rated by the supervisor
5.25
5.78
5.65
4.17
0.91
0.76
0.69
0.68
3.2. Cluster Analyses: Different Operationalizations of the Wellbeing-Performance Patterns.
As mentioned above, we used cluster analysis to find different patterns of relationships between
performance and wellbeing, taking into account different operationalizations of wellbeing (i.e., hedonic
vs. eudaimonic) and performance (i.e., self-rated vs. supervisor ratings). The results are shown below.
Models 1 and 2 consider self-rated performance by the employee (hedonic wellbeing in Model 1 and
eudaimonic wellbeing in Model 2). Models 3 and 4 consider performance evaluated by the supervisor
(hedonic wellbeing in Model 3 and eudaimonic wellbeing in Model 4).
When performance is evaluated by the employee, there are four clusters: (1) employees who are
high in both wellbeing and high performance; (2) employees who are medium low in wellbeing and
medium high in performance; (3) employees who are medium high in wellbeing and medium low in
performance; and (4) employees who are low in both wellbeing and performance.
When performance is evaluated by the supervisor, there are three clusters: (1) employees who
are high in both wellbeing and performance; (2) employees who are high in wellbeing and low in
performance; and (3) employees who are low both in both wellbeing and performance.
The results show that there are antagonistic patterns of wellbeing and performance (i.e.,
happy-unproductive, and in some cases, unhappy-productive). In fact, the results indicate that,
on average, over 50% of the respondents belong to these clusters.
3.2.1. Model 1: Hedonic Wellbeing vs. Self-Rated Performance (H-PE).
In Model 1, we consider two variables: hedonic wellbeing and self-rated composite performance
rated by the employee. The auto-clustering algorithm indicated a four–cluster solution as
the best model because it minimized the BIC value (BIC = 1060.892, BIC change from the
previous cluster = 228.184). The average silhouette measure of cohesion and separation was 0.5,
indicating fair to good cluster quality. The importance of both predictors was 1.00.
Four clusters emerged (see Figure 1): (1) employees high in hedonic wellbeing (M = 6.17, SD =
0.35) and high in self-reported performance (M = 6.29, SD = 0.36), i.e., “hH-hPE” (n = 411; 24,95%); (2)
employees medium low in hedonic wellbeing (M = 4.97, SD = 0.49) and medium high in self-reported
performance (M = 6.10, SD = 0.31), i.e., “mlH-mhPE” (n = 383; 23,25%); (3) employees medium high in
i.e., “lH-lPS” (n = 179, 20%).
3.2.4. Model 4: Eudaimonic Wellbeing vs. Performance Evaluated by the Supervisor (E-PS).
In Model 4, we consider two variables: eudaimonic wellbeing and performance evaluated by the
supervisor.
the auto-clustering
algorithm indicated a four–cluster solution as the best model,
Int. J. Environ. Although
Res. Public Health
2019, 16, 479
8 of 20
we decided to opt for a three-cluster solution to maintain a similar cluster structure to operationalization
3, and because the three-cluster solution also presented fair to good quality (BIC = 786.235, BIC change
hedonic
= 5.45,
SD = 0.46)average
and medium
low in
self-reported
performance
(M = 5.26,=SD
=
from thewellbeing
previous (M
cluster
= −242.320,
silhouette
measure
of cohesion
and separation
0.5).
0.34),
i.e., “mhH-mlPE”
= 578; 35,09%);
and (4) employees
low and
in hedonic
wellbeing
(M = 3.82,
=
The importance
of the(npredictors
of eudaimonic
wellbeing
performance
evaluated
bySD
the
0.71)
and low
in1.00
self-reported
performance (M = 4.88, SD = 0.69), i.e., “lH-lPE” (n = 274; 16,67%).
supervisor
was
and 0.81, respectively.
Figure 1. Four cluster analyses of different combinations of well-being dimensions and performance
for for
highhigh
level;level;
mH stands
for medium
high level;
stands
medium
from two
two sources.
sources.h stands
h stands
mH stands
for medium
highml
level;
mlfor
stands
for
low level;low
l stands
level.
Hedonic-Performance
(self-rated by the
Employee);
medium
level;forl low
stands
forH-Pe
low stands
level. for
H-Pe
stands for Hedonic-Performance
(self-rated
by
E-PeEmployee);
stands for E-Pe
Eudaimonic-Performance
(self-rated by the
Employee);
H-Ps
stands for
Hedonicthe
stands for Eudaimonic-Performance
(self-rated
by the
Employee);
H-Ps
stands
Performance
(evaluated by(evaluated
the Supervisor);
stands for
Eudaimonic-Performance
(evaluated by
for
Hedonic-Performance
by theE-Ps
Supervisor);
E-Ps
stands for Eudaimonic-Performance
the Supervisor);
A Supervisor);
and B inside A
theand
arrows
denote
comparisons
can be made
(evaluated
by the
B inside
thedifferent
arrows types
denoteofdifferent
typesthat
of comparisons
among
different
operationalizations
of well-beingofand
performance
within thewithin
“happythat
can the
be made
among
the different operationalizations
well-being
and performance
the
“happy-productive”
worker framework.
productive” worker framework.
3.2.2. Model 2: Eudaimonic Wellbeing vs. Self-Rated Performance (E-PE).
In Model 2, we consider the following variables: eudaimonic wellbeing and self-rated
performance. Although the auto-clustering algorithm indicated a two-cluster solution as the best model,
we decided to opt for a four-cluster solution to maintain a similar cluster structure to Operationalization
1, and because the four-cluster solution also presented fair to good quality (BIC = 1067.114, BIC change
from the previous cluster = 197.159, average silhouette measure of cohesion and separation = 0.5).
The importance of both predictors was 1.00.
Four clusters emerged (see Figure 1): (1) employees high in eudaimonic wellbeing (M = 6.39,
SD = 0.41) and high in self-reported performance (M = 6.27, SD = 0.34), i.e., “hE-hPE” (n = 596,
36%); (2) employees medium low in eudaimonic wellbeing (M = 5.10, SD = 0.40) and medium high in
self-reported performance (M = 5.63, SD = 0.43), i.e., “mlE-mhPE” (n = 425, 26%); (3) employees medium
high in eudaimonic wellbeing (M = 6.02, SD = 0.35) and medium low in self-reported performance
(M = 5.28, SD = 0.36), i.e., “mhE-mlPE” (n = 474, 29%); and (4) employees low in eudaimonic wellbeing
Int. J. Environ. Res. Public Health 2019, 16, 479
9 of 20
(M = 4.60, SD = 0.61) and low in self-reported performance (M = 4.38, SD = 0.45), i.e., “lE-lPE” (n = 152,
9%).
3.2.3. Model 3: Hedonic Wellbeing vs. Performance Evaluated by the Supervisor (H-PS).
In Model 3, we consider two variables: hedonic wellbeing and performance assessed by the
supervisor. The auto-clustering algorithm indicated a three-cluster solution as the best model
because it minimized the BIC value (807.301, BIC change from the previous cluster = 172.428).
The average silhouette measure of cohesion and separation was 0.5, indicating fair to good cluster
quality. The importance of the predictors of hedonic wellbeing and performance evaluated by the
supervisor is 1.00 and 0.91, respectively.
Three clusters emerged (see Figure 1): (1) employees high in hedonic wellbeing (M = 5.76,
SD = 0.57) and high performance evaluated by the supervisor (M = 4.80, SD = 0.26), i.e., “hH-hPS”
(n = 334, 37%); (2) employees high in hedonic wellbeing (M = 5.46, SD = 0.56) and low in performance
evaluated by the supervisor (M = 3.86, SD = 0.36), i.e., “hH-lPS” (n = 402, 44%); and (3) employees
low in hedonic wellbeing (M = 3.91, SD = 0.83) and low in performance evaluated by the supervisor
(M = 3.67, SD = 0.86), i.e., “lH-lPS” (n = 179, 20%).
3.2.4. Model 4: Eudaimonic Wellbeing vs. Performance Evaluated by the Supervisor (E-PS).
In Model 4, we consider two variables: eudaimonic wellbeing and performance evaluated by
the supervisor. Although the auto-clustering algorithm indicated a four–cluster solution as the
best model, we decided to opt for a three-cluster solution to maintain a similar cluster structure to
operationalization 3, and because the three-cluster solution also presented fair to good quality (BIC
= 786.235, BIC change from the previous cluster = 242.320, average silhouette measure of cohesion
and separation = 0.5). The importance of the predictors of eudaimonic wellbeing and performance
evaluated by the supervisor was 1.00 and 0.81, respectively.
The three clusters identified are (see Figure 1): (1) employees high in eudaimonic wellbeing
(M = 6.14, SD = 0.52) and high performance evaluated by the supervisor (M = 4.92, SD = 0.14), i.e.,
“hE-hPS” (n = 240, 26%); (2) employees high in eudaimonic wellbeing (M = 6.19, SD = 0.45) and low in
performance evaluated by the supervisor (M = 3.75, SD = 0.56), i.e., “hE-lPS” (n = 416, 46%); and (3)
employees low in eudaimonic wellbeing (M = 4.93, SD = 0.52) and low in performance evaluated by
the supervisor (M = 4.14, SD = 0.55), i.e., “lE-lPS” (n = 259, 28%).
3.3. Profiles of (un)Happy-(un)Productive Workers in Different Operationalizations of Wellbeing and
Performance
In the following section, we try to reveal on whether it is helpful to obtain different profiles
of (un)happy–(un)productive workers on the basis of different operationalizations of wellbeing and
performance. If the individuals remain in the same or an equivalent category regardless of the variables
considered to create the groups, it would be sufficient to consider only one operationalization. In order
to analyze this, we compare Models 1 and 2 (both with four clusters) and Models 3 and 4 (both with
three clusters). Other comparisons do not make sense because the number of clusters is different.
In fact, a different number of clusters depending on the performance measure (self-rated or evaluated
by the supervisor) would mean that this operationalization is important.
In order to shed light on this issue, we present the results of the analysis of how many individuals
belonging to a specific cluster in one operationalization (e.g., hH-hPE) belong to the same cluster in a
different operationalization (e.g., hE-hPE), as well as how many participants belonging to one cluster
in one operationalization (e.g., hH-hPS) belong to a different cluster in another operationalization (e.g.,
hE-lPS). The clusters found with the four types of operationalizations of the variables (dimensions
of wellbeing and two sources of information about performance) can be found in the Figure 1.
The results show that a large number of employees do not belong to analogous clusters in different
Int. J. Environ. Res. Public Health 2019, 16, 479
10 of 20
operationalizations of wellbeing and performance. This result means that some employees are classified
as both unhappy in a hedonic way and, simultaneously, happy in an eudaimonic way (and vice-versa).
3.3.1. Comparison A (Model 1–Model 2): Hedonic–Employee-Rated Performance (H-PE) vs.
Eudaimonic–Employee-Rated Performance (E-PE).
If the whole sample is considered, 50.6% of the respondents belong to a homologous cluster
in both the H-PE and E-PE models. This means that about half of the employees had comparable
wellbeing and performance profiles in both models. They have similar profiles in terms of both kinds
of wellbeing. Interestingly, the other half of the employees (49.4%) do not belong to homologous
clusters, which means that they belong to a cluster that suggests that they are unhappy in a hedonic
way and, simultaneously, to a cluster that suggests that they are happy in an eudaimonic way, or
vice versa.
3.3.2. Comparison B (Model 3–Model 4): Hedonic–Supervisor-Rated Performance (H-PS) vs.
Eudaimonic–Supervisor-Rated Performance (E-PS)
Almost two thirds of the respondents (63.9%) belong to a homologous cluster in the H-PS and
E-PS models, whereas 36.1% of the respondents belong to clusters with different profiles depending
of the operationalization of wellbeing. This means that almost a third of the participants could be
simultaneously happy in a hedonic way and unhappy in an eudaimonic way, or vice-versa, at a certain
level of performance evaluated by the supervisor.
3.4. Demographic Variables as Significant Antecedents of the Wellbeing—Performance Classification.
As indicated previously, we used multidimensional logistic regression to explain cluster
membership based on the demographic covariates. The odds ratios for all the models are displayed
in Tables 3–6. An odds ratio greater than 1 implies that a person in a given category has greater
odds of belonging to a cluster than a person in the reference category (in the case of variables with
2 categories) or than the average of all the subjects in the study (in the case of variables with more
than 2 categories). An odds ratio below 1 suggests reduced odds. We identified different demographic
predictors when different operationalizations of wellbeing (hedonic-eudaimonic) and performance
(self- or supervisor-evaluated) are considered.
Int. J. Environ. Res. Public Health 2019, 16, 479
OR (95%
CI)
3
OR (95%
CI)
4
OR (95%
CI)
1
(Cluster
1)
0.55 **
(0.37–0.82)
0.73 *
(0.52–1.01)
0.61 *
(0.39–0.96)
1.61 **
(1.11–2.31)
1.59 **
(1.13–2.23)
3
OR (95%
CI)
4
OR (95%
CI)
1
2.03 ***
(1.38–3.01)
OR (95%
CI)
2
(Cluster
3)
OR (95%
CI)
1.8 **
(1.22–2.67)
(Cluster
2)
0.49 ***
(0.33–0.73)
1.59 **
(1.17–2.16)
0.54 **
(0.34–0.85)
1.44 *
(1.00–2.08)
0.63 **
(0.46–0.85)
1.52 *
(1.08–2.14)
1
OR (95%
CI)
2
OR (95%
CI)
3
11 of 20
4
OR (95%
CI)
(Cluster
4)
OR (95%
CI)
1.5 **
(1.14–1.95)
0.62 **
(0.44–0.87)
0.72 *
(0.51–1.01)
1.85 **
(1.17–2.91)
0.69 *
(0.48–1.00)
1.83 ***
(1.39–2.43)
1.64 *
(1.04–2.58)
0.62 **
(0.43–0.90)
1.62 **
(1.15–2.28)
1.4 *
(0.99–1.96)
1.68 **
(1.22–2.32)
0.42 ***
(0.30–0.59)
0.74 **
(0.58–0.94)
0.46 ***
(0.36–0.60)
3.07 **
(1.48–6.38)
1.36 **
(1.07–1.72)
0.49 ***
(0.37–0.65)
1.96 **
(1.23–3.13)
1.63 ***
(1.23–2.17)
2.37 ***
(1.69–3.32)
1.89 **
(1.16–3.07)
0.67 **
(0.51–0.87)
2.16 ***
(1.67–2.80)
0.33 **
(0.16–0.68)
0.54 ***
(0.41–0.72)
2.04 ***
(1.55–2.69)
0.51 **
(0.32–0.81)
0.61 ***
(0.46–0.82)
0.53 **
(0.32–0.86)
1.37 *
(0.99–1.91)
OR (95%
CI)
2
Table 3. Multinomial logistic regression analysis of factors associated with the clusters. Model 1: Hedonic (H) Performance employee (PE).
Predictors
Sector (0 service / 1 production)
Gender (0 female / 1 male)
Educational level
Seniority (0 < 5 years / 1 > 5 years)
No education or compulsory
Professional training or high school
University degree
Occupational category
Unqualified manual work
Technician or administrative
Highly qualified professional
Manager
Reference cluster is in brackets. Cluster 1: h H- h PE; Cluster 2: ml H-mh PE; Cluster 3: mh H-ml PE; Cluster 4: l H-l PE; OR: odds ratio; CI: confidence interval; * p 0.05, ** p 0.01,
*** p 0.001.
Int. J. Environ. Res. Public Health 2019, 16, 479
OR (95%
CI)
4
1
1
3
4
(Cluster
2)
3
OR (95%
CI)
OR (95%
CI)
OR (95%
CI)
OR (95%
CI)
OR (95%
CI)
OR (95%
CI)
1.75 **
(1.22–2.50)
0.67 **
(0.49–0.91)
0.47 *
(0.24–0.90)
0.57 **
(0.40–0.82)
1.6 **
(1.11–2.30)
0.64 **
(0.48–0.86)
(Cluster
1)
4
OR (95%
CI)
1
2.14 *
(1.11–4.13)
OR (95%
CI)
2
1.96 *
(1.01–3.78)
0.62 *
(0.40–0.95)
OR (95%
CI)
3
12 of 20
2
OR (95%
CI)
3.42 ***
(1.81–6.46)
0.59 **
(0.39–0.90)
(Cluster
4)
OR (95%
CI)
0.51 *
(0.26–0.99)
1.61 *
(1.05–2.48)
0.75 *
(0.60–0.95)
1.49 **
(1.10–2.03)
(Cluster
3)
Table 4. Multinomial logistic regression analysis of factors associated with the clusters. Model 2: Eudaimonic (E) Performance employee (PE).
Predictors
2
Sector (0 service / 1 production)
0.29 ***
(0.15–0.55)
1.69 **
(1.11–2.58)
1.32 *
(1.05–1.68)
0.55 **
(0.37–0.80)
0.73 *
(0.54–0.98)
1.56 *
(1.04–2.35)
0.54 **
(0.37–0.80)
1.44 ***
(1.10–1.89)
0.59 **
(0.41–0.85)
1.37 *
(1.02–1.84)
0.64 *
(0.43–0.96)
1.82 **
(1.24–2.68)
0.69 **
(0.43–0.96)
1.84 **
(1.25–2.71)
0.71 **
(0.55–0.92)
1.7 **
(1.17–2.46)
0.58 **
(0.39–0.88)
1.52 **
(1.09–2.12)
0.64 *
(0.43–0.96)
0.76 *
(0.59–0.98)
2.76 *
(1.10–6.91)
1.66 **
(1.19–2.33)
0.54 **
(0.36–0.80)
0.77 *
(0.60–0.98)
2.22 **
(1.35–3.65)
1.7 ***
(1.23–2.35)
1.71 **
(1.14–2.58)
2.15 **
(1.33–3.46)
0.66 **
(0.47–0.92)
1.56 *
(1.04–2.34)
1.31 *
(1.02–1.69)
0.36 *
(0.14–0.91)
0.60 **
(0.43–0.84)
1.85 **
(1.24–2.76)
1.3 *
(1.01–1.67)
0.45 **
(0.27–0.74)
0.59 ***
(0.43–0.81)
0.47 **
(0.29–0.75)
1.4 **
(1.08–1.82)
0.62 **
(0.43–0.90)
1.56 **
(1.16–2.10)
Age
Gender (0 female / 1 male)
< 35 years
35-50 years
> 50 years
Educational level
No education or compulsory
Professional training or high school
University degree
Occupational category
Unqualified manual work
Technician or administrative
Highly qualified professional
Manager
Reference cluster is in brackets; Cluster 1: h E- h PE; Cluster 2: ml E-mh PE; Cluster 3: mh E-ml PE; Cluster 4: l E-l PE; OR: odds ratio; CI: confidence interval; * p 0.05, ** p 0.01,
*** p 0.001.
Int. J. Environ. Res. Public Health 2019, 16, 479
2
OR (95% CI)
1
OR (95% CI)
3
OR (95% CI)
1
OR (95% CI)
2
13 of 20
3
(Cluster 3)
OR (95% CI)
(Cluster 2)
Table 5. Multinomial logistic regression analysis of factors associated with the clusters. Model 3: Hedonic (H) Performance supervisor (PS).
OR (95% CI)
1.6 * (1.03–2.48)
0.62 * (0.40–0.97)
0.61 * (0.39–0.94)
1.7 * (0.99–2.93)
0.39 *** (0.23–0.65)
0.65 * (0.44–0.96)
1.68 * (1.08–2.63)
2.36 * (1.03–5.41)
0.55 *** (0.38–0.79)
2.59 *** (1.55–4.35)
1.53 * (1.04–2.25)
0.59 * (0.38–0.93)
0.42 * (0.18–0.97)
(Cluster 1)
Predictors
1.82 *** (1.26–2.62)
0.59 * (0.34–1.01)
1.65 * (1.06–2.57)
Contract (0 temporary / 1 permanent)
Occupational category
Unqualified manual work
Technician or administrative
Highly qualified professional
Manager
2
OR (95% CI)
3
1
OR (95% CI)
3
OR (95% CI)
1
1.76 * (1.07–2.92)
0.52 *** (0.35–0.77)
OR (95% CI)
2
(Cluster 3)
OR (95% CI)
2.18 ** (1.23–3.86)
0.64 * (0.41–1.00)
1.46 * (1.07–2.00)
0.6 * (0.39–0.94)
0.48 ** (0.30–0.77)
1.47 ** (1.10–1.95)
0.38 *** (0.22–0.67)
0.45 *** (0.30–0.69)
0.68 * (0.50–0.93)
1.66 * (1.07–2.58)
0.53 * (0.31–0.90)
2.28 * (1.13–4.63)
1.39 * (1.04–1.86)
0.57 * (0.34–0.94)
1.93 *** (1.30–2.86)
(Cluster 2)
Table 6. Multinomial logistic regression analysis of factors associated with the clusters. Model 4: Eudaimonic (E) Performance supervisor (PS).
OR (95% CI)
(Cluster 1)
Predictors
0.46 ** (0.26–0.81)
1.56 * (1.00–2.44)
0.68 ** (0.51–0.91)
2.63 *** (1.50–4.63)
1.83 * (1.01–3.34)
2.06 ** (1.29–3.28)
1.89 * (1.11–3.20)
0.44 * (0.22–0.89)
0.72 * (0.54–0.96)
0.55 * (0.30–0.99)
2.2 *** (1.46–3.31)
Sector (0 service / 1 production)
Gender (0 female / 1 male)
Contract (0 temporary / 1
permanent)
Age
< 35 years
35-50 years
> 50 years
Occupational category
Unqualified manual work
Technician or administrative
Highly qualified professional
Manager
Reference cluster is in brackets; Cluster 1: h E- h PE; Cluster 2: h E-l PE; Cluster 3: l E-l PE; OR: odds ratio; CI: confidence interval; * p 0.05, ** p 0.01, *** p 0.001.
Int. J. Environ. Res. Public Health 2019, 16, 479
14 of 20
3.4.1. Multidimensional Logistic Regression: Model 1 (H-PE)
The multinomial logistic regression analyses identified five predictors that explain cluster
membership: the organization’s sector, gender, seniority in the position, educational level,
and occupational category (see Table 3). The results show that the model has a good fit ( 2 log
LR = 679.06, X2 = 129.83, df = 24, p 0.001) (with LR being the likelihood ratio). The probability of
having high wellbeing and high performance is greater in the production sector and for managers.
The probability of having medium low wellbeing and medium high performance is greater in the
production sector, for people with more than 5 years of seniority, and for technicians/administrative
work. The probability of having medium high wellbeing and medium low performance is greater in
the services sector, for people with less than 5 years of seniority, with professional training or high
school, and for technicians/administrative workers. Finally, the probability of having low wellbeing
and low performance is greater in the services sector, for men, with no education or compulsory
education, and for technicians/administrative work.
Comparing Clusters 1 (high levels) and 4 (low levels), the production sector, women, people with
a university degree, and managers are more likely to be in Cluster 1, whereas the services sector, men,
people with no education or compulsory education, and technicians/administrative workers are more
likely to be in Cluster 4.
3.4.2. Multidimensional Logistic Regression: Model 2 (E-PE)
The multinomial logistic regression analyses identified five predictors that explain cluster
membership: the organization’s sector, gender, age, educational level, and occupational category
(see Table 4). The results show that the model has a good fit ( 2 log LR = 777.45, X2 = 99.68,
df = 27, p 0.001) The probability of having high wellbeing and high performance is greater in
the production sector, women, and managers. The probability of having medium low wellbeing
and medium high performance is greater for men, people over 50 years old, and unqualified
manual workers or technicians/administrative workers. The probability of having medium high
wellbeing and medium low performance is greater for women, and for unqualified manual workers
or technicians/administrative workers. Finally, the probability of having low wellbeing and low
performance is greater for the services sector, men, people with no education or compulsory education,
and technicians/administrative workers.
Comparing Clusters 1 (high levels) and 4 (low levels), results are similar to those in
Operationalization 1. The production sector, women, people with university degrees, and managers
are more likely to be in Cluster 1, whereas the services sector, men, people with no education or
compulsory education, and technicians/administrative workers are more likely to be in Cluster 4.
3.4.3. Multidimensional Logistic Regression: Model 3 (H-PS)
The multinomial logistic regression analyses identified two predictors that explain cluster
membership: type of contract and occupational category (see Table 5). The results show that the
model has a good fit ( 2 log LR = 68.14, X2 = 38.70, df = 8, p 0.001). The probability of having
high wellbeing and high performance is greater for people with a temporary contract and for highly
qualified professionals or managers. The probability of having high wellbeing and low performance is
greater for people with a permanent contract and people who do unqualified manual work. Finally,
the probability of having low wellbeing and low performance is greater for people with a temporary
contract and for unqualified manual workers or technicians/administrative workers.
Comparing Clusters 1 (high levels) and 3 (low levels), highly qualified professionals or managers
are more likely to be in Cluster 1, whereas unqualified manual workers or technicians/administrative
workers are more likely to be in Cluster 3.
Int. J. Environ. Res. Public Health 2019, 16, 479
15 of 20
3.4.4. Multidimensional Logistic Regression: Model 4 (E-PS)
The multinomial logistic regression analyses identified five predictors that explain cluster
membership: the organization’s sector, gender, type of contract, age, and occupational category
(see Table 6). The results show that the model has a good fit ( 2 log LR = 358.37, X2 = 60.39, df = 16,
p 0.001). The probability of having high wellbeing and high performance is greater in the production
sector, women, people between 35-50 years old, people with a temporary contract, and managers.
The probability of having high wellbeing and low performance is greater in the production sector,
women, people under 35 years old, with a permanent contract, and who do unqualified manual work.
Finally, the probability of having low wellbeing and low performance is greater for the services sector,
men, people over 50 years old, with a permanent contract, and who do unqualified manual work.
Comparing Clusters 1 (high levels) and 3 (low levels), the production sector, women, people
with a temporary contract, between 35–50 years old, and managers are more likely to be in Cluster 1,
whereas the services sector, men, people with a permanent contract, over 50 years old, and who do
unqualified manual work are more likely to be in Cluster 3.
4. Discussion
The aim of the present study was to revisit the happy productive worker model, extending
it to consider not just the synergies between happiness and productivity, but also the antagonistic
relations between these two constructs. Moreover, we aimed to clarify the implications of different
operationalizations of relevant theoretically-based constructs for the model. Finally, we aimed to
identify demographic antecedents for each cluster solution. In this way, this work has addressed
important limitations of the happy-productive worker model by incorporating both the hedonic and
eudaimonic components of wellbeing, considering different aspects of job performance as well as their
different sources of evaluation, and focusing not just on the synergies between the two constructs
(happiness and productivity), but also on the antagonistic relations, an issue that has hardly been
considered in the research based on the model.
The results support a different way to specify and expand the happy-productive worker model.
Indeed, by analyzing the relationships between different constructs, we are not taking a positive
relationship that leads to being a “happy-productive” or “unhappy-unproductive” worker for granted.
The present research has also contemplated a negative relationship between constructs that would
appear on a daily basis and that would lead to being “happy-unproductive” or “unhappy-productive”
at work. In this study, we provide an affirmative response to Research Question 1, which asks
whether “employees show different patterns considering the antagonist relation beyond the traditional
synergetic relation between performance and wellbeing (i.e., happy-productive)”. In fact, we have
found antagonist patterns of wellbeing and performance (i.e., happy-unproductive and, in some
cases, unhappy-productive) that are well represented in our sample. We found these alternative
patterns by taking into account different operationalizations of wellbeing (i.e., hedonic, eudaimonic)
and performance (i.e., self-rated, evaluated by the supervisor). In fact, the results indicate that, on
average, over 50% of the respondents belong to the unhappy-productive/happy-unproductive clusters,
which suggests that it is important to consider the antagonistic patterns of wellbeing and performance
when re-defining the happy-productive worker thesis. Thus, we contribute to filling the gap identified
by Warr and Nielsen [51], who pointed out that it is important to learn more about individuals
who are outside the happy-productive pattern by considering additional measures of performance
and wellbeing.
In fact, Research Question 2 asks whether the same employees belong to the same patterns of
wellbeing and performance in their different operationalizations. The results show that a large number
of employees do not belong to analogous clusters in different operationalizations of wellbeing and
performance, which means that some employees are classified as unhappy in a hedonic way and,
simultaneously, happy in an eudaimonic way (and vice-versa). This result draws our attention to
the complexity of the phenomenon of wellbeing and the importance of considering both the hedonic
Int. J. Environ. Res. Public Health 2019, 16, 479
16 of 20
and eudaimonic dimensions in studies on wellbeing. It clearly shows that merely considering the
hedonic aspect of wellbeing provides only half the picture. We believe future research should more
thoroughly investigate the antecedents and outcomes for “hedonically-happy” and “eudaimonically
unhappy” employees.
In addition, the results suggest that employees’ self-rated performance is often not reflected
in their supervisor’s evaluation of their performance. This draws our attention to the importance
of considering more than one source of evaluation of work performance in order to obtain valid
information about the employees’ task performance, extra-role performance, and creativity. It is
possible that the disparity in the evaluation of the employees’ performance level is due to the fact that
employees might be more lenient when self-rating their general performance [38]. It is also possible
that, when assessing their own performance, employees’ responses reflect not only their past behavior,
but also their expectations of current and future behavior [58]. We think it would be interesting to
investigate more in depth the reasons for the differences between employees’ ratings of their own
performance and the ratings given by their direct supervisors.
Finally, the results provide an affirmative response to Research Question 3 about whether there are
any demographic variables that play a role as antecedents of the clusters in different operationalizations
of the “happy-productive” worker. The existence of differences in the demographic variables between
clusters provides yet another way to validate the clusters and the different operationalizations of
wellbeing and performance. This means that it is reasonable to expand the study of employees and
their different outcomes at work to different patterns of wellbeing and performance, and include
alternative configurations of “happy-unproductive” and “unhappy-productive” clusters.
Following the recommendations of Warr and Nielsen [51], we identified a number of situational
and personal features associated with membership in each profile when additional measures of
wellbeing and performance are considered. Our study examines whether personal features, such
as gender, age, and educational level, and situational features, such as sector, type of contract,
occupational category, and seniority in the position, play a predictor role in the different profiles
obtained, based on the operationalizations of wellbeing (hedonic-eudaimonic) and performance
(self- or supervisor- evaluated) considered. The exploratory results provide relevant information
showing that occupational category is the only variable with a predictor role in the four models
studied. Moreover, another situational variable (sector) and a personal variable (gender) significantly
predict the profiles in three of the four models studied. Interestingly, the type of contract is a significant
antecedent in the two models in which the supervisors’ performance assessment is considered, whereas
the educational level is a significant antecedent in the two models where self-assessed performance is
considered. More specifically, women, workers in the production sector, and management or highly
qualified professionals are more likely to be included in the happy-productive profile, whereas men,
workers in the services sector, employees with a low education level, and technicians/administrative
workers are more likely to be included in the unhappy-unproductive cluster.
We also identified the main features of employees included in the happy-unproductive profiles.
These features differ across the four models studied. The “high hedonic/low performance (self-rated)”
pattern is populated more by employees from the services sector with professional training and
technician-administrative jobs. In the case of the “high eudaimonic/low performance (self-rated)”
pattern, it is mostly composed of women and employees in unqualified or technician/administrative
jobs. It is interesting to note that, when we look at the two similar profiles generated using supervisor
ratings of performance, the employees with a higher probability of belonging to these patterns (both
hedonic and eudaimonic) have permanent contracts and are employed in unqualified or manual jobs.
Finally, it is interesting to identify the features that more often characterize employees included in
the unhappy/productive profiles. The employees included in the “low hedonic/high performance
(self-rated)” profile work in the production sector, have seniority (>5 years) and professional education,
and work in technician-administrative jobs. The employees included in the “low eudaimonic/high
performance (self-rated)” profile are mostly men over 50 years old working in unqualified-manual
Int. J. Environ. Res. Public Health 2019, 16, 479
17 of 20
or technician-administrative jobs. Considering this complex picture of personal and situational
characteristics associated with the different profiles obtained with different types of wellbeing and
performance, we can conclude that the different models are not redundant, and different types
of wellbeing and different sources of performance need to be considered to better understand the
happy-productive worker model. Further research is needed to confirm the predictive power of the
variables studied and extend the study by including other personal and situational variables, in order
to better describe the employees in each profile.
In sum, the present study addresses a number of limitations of the happy productive worker
thesis, and it sheds light on a number of issues that may clarify the previous inconsistencies of
the model. First, this study included both the hedonic and eudaimonic aspects of wellbeing,
coinciding with recent conceptualizations of wellbeing as having both pleasurable and meaningful
components [3–5]. The identification of the hedonic “happy-productive” and “unhappy-unproductive”
patterns coincides with studies indicating that there is a positive relationship between hedonic
wellbeing and performance [13–18]. The identification of the “unhappy-productive” pattern agrees
with research that shows a negative relationship between positive affect and the dimensions
of performance [48]. Simultaneously, the identification of the eudaimonic “happy-productive”
pattern supports research that suggests a synergetic relationship between eudaimonic wellbeing
and performance [31]. These patterns support previous research showing that daily increases in
perceived meaning at work were related to employees’ increased focus on tasks and greater exploratory
behavior [31]. Second, this study considers different dimensions and sources of evaluation of
employees’ performance. On the one hand, we operationalize job performance as consisting of different
facets or dimensions (i.e., in-role performance, extra-role performance, creative performance) that can
help to capture its manifestations. On the other hand, we consider two sources of information about
performance: self-rated performance and performance rated by the direct supervisor. Third, the present
research analyzes alternative configurations that have not been considered in the happy-productive
worker thesis. It shows the importance of these alternative configurations, reflected by the number of
employees who belong to the “happy-unproductive” and “unhappy-productive” clusters (over 50%
on average), suggesting that the work reality is built on these antagonistic patterns, as well as on the
synergetic ones. Thus, antagonistic patterns should not be neglected in future research. Finally, this
study has identified a number of individual and situational features that significantly distinguish the
different profiles in each of the operationalizations of the happy-productive worker model.
Limitations
The current paper’s findings should be interpreted cautiously in light of several potential
limitations. A limitation of the study is that most of the sample belonged to the services sector, although
some of the sample is from the production sector, including areas such as construction. This limitation
questions the representativeness of the results of underrepresented sectors. Services and production
sectors could certainly vary in their different types of procedures and practices, such as performance
evaluation or health and wellbeing promotion. The sample is more balanced in terms of gender, age,
job category, or type of contract. In any case, this study represents a first approach to understanding
the diversity in the patterns of relationships between performance and wellbeing in organizations.
A second limitation is the fact that self-rated performance and performance rated by supervisors
were not assessed with the same scale, due to the difficulties in obtaining responses from supervisors
about all their subordinates (in fact, we had a high reduction in the sample when gathering data).
This situation can raise some doubts about the reasons for the differences in performance-wellbeing
patterns when each of the measurement methods is used. Thus, these differences could be due to
different performance measures rather than to different informants. However, both measures can
be considered global performance measures. Self-rated performance is a composite measure that
includes the basic components of performance [34]. Performance rated by the supervisor measures
Int. J. Environ. Res. Public Health 2019, 16, 479
18 of 20
global performance considering three global indicators: general performance, quality, and achievement
of objectives.
5. Conclusions
This study shows that the relationship between wellbeing and performance is more complex than
the HPWT proposes. Different operationalizations of these constructs need to be considered. Moreover,
we found that a large percentage of respondents are grouped under the happy-unproductive or the
unhappy-productive profiles. The results also indicate that employees can be unhappy in a hedonic
way and, simultaneously, happy in an eudaimonic way (and vice versa). Finally, we show that there
are several significant antecedents of the patterns, in terms of demographic variables, in different
operationalizations of wellbeing and performance.
Future studies on the antecedents and consequences of these patterns of wellbeing and
performance can be relevant for organizational practice because they might help to identify a broader
scope of employees’ profiles regarding their performance and wellbeing and the circumstances in
which they experience synergies and antagonisms between these two important constructs.
In conclusion, the results of this study draw our attention to the fact that there can be different
typologies of “happy-productive” workers that may take into account both hedonic and eudaimonic
dimensions of wellbeing, as well as two different informants about the employees” work performance.
As we can see, a large percentage of workers do not pertain to the conventional “happy-productive”
or “unhappy-unproductive” patterns, but rather to the antagonistic quadrants of “unhappy but
productive” and “happy but unproductive”.
Author Contributions: Conceptualization, J.M.P, N.T., I.R.-M. and M.W.K.; data gathering and databases, N.T.
and I.R.-M.; methodology, J.M..P, M.W.K. and I.R.-M.; formal analysis, M.W.K. and I.R.-M.; writing—original draft
preparation, M.W.K. and I.R.-M.; writing—review and editing, J.M.P. and N.T.; funding acquisition, J.M.P. and
N.T.
Funding: The present study was funded by the MINECO/FEDER Research agencies: project PSI2012-36557
funded by DGICYT and the project PSI2015-64862-R (MINECO/FEDER)
Conflicts of Interest: The authors declare no conflicts of interest.
References
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Diener, E. Subjective well-being. The science of happiness and a proposal for a national index. Am. Psychol.
2000, 55, 34–43. [CrossRef] [PubMed]
Ryff, C.D. Psychological well-being in adult life. Curr. Dir. Psychol. Sci. 1995, 4, 99–104. [CrossRef]
Dolan, P. Happiness by Design; Hudson Street Press: New York, NY, USA, 2014.
Keyes, C.L.M.; Shmotkin, D.; Ryff, C.D. Optimizing well-being: The empirical encounter of two traditions.
J. Pers. Soc. Psychol. 2002, 82, 1007–1022. [CrossRef] [PubMed]
Linley, P.A.; Maltby, J.; Wood, A.M.; Osborne, G.; Hurling, R. Measuring happiness: The higher order factor
structure of subjective and psychological well-being measures. Pers. Individ. Differ. 2009, 47, 878–884.
[CrossRef]
Ryan, R.M.; Deci, E.L. On happiness and human potentials: A review of research on hedonic and eudaimonic
well-being. Annu. Rev. Psychol. 2001, 52, 141–166. [CrossRef] [PubMed]
Cropanzano, R.; Wright, T.A. When a “happy” worker is really a “productive” worker: A review and
further refinement of the happy-productive worker thesis. Consult. Psychol. J. Pract. Res. 2001, 53, 182–199.
[CrossRef]
Wright, T.A.; Cropanzano, R.; Bonett, D.G. The moderating role of employee positive well being on the
relation between job satisfaction and job performance. J. Occup. Health Psychol. 2007, 12, 93–104. [CrossRef]
[PubMed]
Beal, D.J.; Weiss, H.M.; Barros, E.; Macdermid, S.M. An Episodic Process Model of Affective Influences on
Performance. J. Appl. Psychol. 2005, 90, 1054–1068. [CrossRef]
Baptiste, N.R. Tightening the link between employee wellbeing at work and performance—A new dimension
for HRM. Manag. Decis. 2008, 46, 284–309. [CrossRef]
Int. J. Environ. Res. Public Health 2019, 16, 479
11.
12.
13.
14.
15.
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
32.
33.
34.
35.
36.
37.
19 of 20
Schulte, P.; Vainio, H.M.D. Well-being at work—Overview and perspective. Scand. J. Work Environ. Health
2010, 36, 422–429. [CrossRef] [PubMed]
Wright, T.; Cropanzano, R. Psychological well-being and job satisfaction as predictors of performance.
J. Occup. Health Psychol. 2000, 5, 84–94. [CrossRef] [PubMed]
Mofoluwake, A.; Oluremi, A. Job satisfaction, organizational stress and employee performance: A study of
NAPIMS. IFE Psychol. 2013, 21, 75–82.
Fogaça, N.; Junior, F.A.C. Is “Happy Worker” More Productive. Manag. Stud. 2016, 4, 149–160.
Hosie, P.; Willemyns, M.; Sevastos, P. The impact of happiness on managers’ contextual and task performance.
Asia Pac. J. Hum. Resour. 2012, 50, 268–287. [CrossRef]
Böckerman, P.; Ilmakunnas, P. The job satisfaction-productivity nexus: A study using matched survey and
register data. Ind. Labor Relat. Rev. 2010, 65, 244–262. [CrossRef]
Foo, M.-D.; Uy, M.A.; Baron, R.A. How do feelings influence effort? An empirical study of entrepreneurs’
affect and venture effort. J. Appl. Psychol. 2009, 94, 1086–1094. [CrossRef] [PubMed]
Seo, M.-G.; Bartunek, J.M.; Feldman Barret, L. Conceptual Model. J. Organ. Behav. 2010, 31, 951–968.
[PubMed]
Zelenski, J.M.; Murphy, S.A.; Jenkins, D.A. The happy-productive worker thesis revisited. J. Happiness Stud.
2008, 9, 521–537. [CrossRef]
Binnewies, C.; Wörnlein, S.C. What makes a creative day? A diary study on the interplay between affect, job
stressors, and job control. J. Organ. Behav. 2011, 32, 589–607. [CrossRef]
Rothbard, N.P.; Wilk, S.L. Waking up on the right or wrong side of the bed: Start-of-workday mood, work
events, employee affect, and performance. Acad. Manag. J. 2011, 54, 959–980. [CrossRef]
Bowling, N.A. Is the job satisfaction-job performance relationship spurious? A meta-analytic examination.
J. Vocat. Behav. 2007, 71, 167–185. [CrossRef]
Iaffaldano, M.T.; Muchinsky, P.M. Job satisfaction and job performance: A meta-analysis. Psychol. Bull. 1985,
97, 251–273. [CrossRef]
Judge, T.A.; Thoresen, C.J.; Bono, J.E.; Patton, G.K. The job satisfaction-job performance relationship: A
qualitative and quantitative review. Psychol. Bull. 2001, 127, 376–407. [CrossRef] [PubMed]
Greenberger, D.B.; Strasser, S.; Cummings, L.L.; Dunham, R.B. The impact of personal control on performance
and satisfaction. Organ. Behav. Hum. Decis. Process. 1989, 43, 29–51. [CrossRef]
Peiró, J.M.; Ayala, Y.; Tordera, N.; Lorente, L.; Rodríguez, I. Sustainable wellbeing at work: A review and
reformulation. Pap. Psicólogo 2014, 35, 7–16.
Rosso, B.D.; Dekas, K.H.; Wrzesniewski, A. On the meaning of work: A theoretical integration and review.
Res. Organ. Behav. 2010, 30, 91–127. [CrossRef]
OECD. OECD Guidelines on Measuring Subjective Well-Being; OECD Publishing: Paris, France, 2013.
Dolan, P.; Layard, R.; Metcalfe, R. Measuring Subjective Wellbeing for Public Policy; Office for National Statistics:
Newport, UK, 2011.
White, M.P.; Dolan, P. Accounting for the richness of daily activities. Psychol. Sci. 2009, 20, 1000–1008.
[CrossRef]
Sonnentag, S. Dynamics of well-being. Annu. Rev. Organ. Psychol. Organ. Behav. 2015, 2, 261–293. [CrossRef]
Niessen, C.; Sonnentag, S.; Sach, F. Thriving at work—A diary study. J. Organ. Behav. 2012, 33, 468–487.
[CrossRef]
Ford, M.T.; Cerasoli, C.P.; Higgins, J.A.; Decesare, A. Relationships between psychological, physical, and
behavioural health and work performance: A review and meta-analysis. Work Stress 2011, 25, 185–204.
[CrossRef]
Koopmans, L.; Bernaards, C.M.; Hildebrandt, V.H.; Schaufeli, W.B.; de Vet, H.C.W.; van der Beek, A.J.
Conceptual frameworks of individual work performance: A systematic review. J. Occup. Environ. Med. 2011,
53, 856–866. [CrossRef] [PubMed]
LePine, J.A.; Erez, A.; Johnson, D.E. The nature and dimensionality of organizational citizenship behavior: A
critical review and meta-analysis. J. Appl. Psychol. 2002, 87, 52–65. [CrossRef] [PubMed]
Oldham, G.R.; Cummings, A. Employee creativity: Personal and contextual factors at work. Acad. Manag. J.
1996, 39, 607–634.
Länsisalmi, H.; Kivimäki, M.; Elovainio, M. Is underutilization of knowledge, skills, and abilities a major
barrier to innovation? Psychol. Rep. 2004, 94, 739–750. [CrossRef] [PubMed]
Int. J. Environ. Res. Public Health 2019, 16, 479
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
55.
56.
57.
58.
20 of 20
Hosie, P.J.; Sevastos, P. Does the “happy-productive worker” thesis apply to managers? Int. J. Work
Health Manag. 2009, 2, 131–160. [CrossRef]
Heidemeier, H.; Moser, K. Self-other agreement in job performance ratings: A meta-analytic test of a process
model. J. Appl. Psychol. 2009, 94, 353–370. [CrossRef] [PubMed]
Conway, J.M.; Huffcutt, A.I. Psychometric properties of multisource performance ratings: A meta-analysis
of subordinate, supervisor, peer, and self-ratings. Hum. Perform. 1997, 10, 331–360. [CrossRef]
Akkermans, J.; Brenninkmeijer, V.; Van den Bossche, S.N.J.; Blonk, R.W.B.; Schaufeli, W.B. Young and going
strong? A longitudinal study on occupational health among young employees of difference educational
levels. Career Dev. Int. 2013, 18, 416–435. [CrossRef]
Fisher, C.D.; Noble, C.S. A within-person examination of correlates of performance and emotions while
working. Hum. Perform. 2004, 17, 145–168. [CrossRef]
Seo, M.; Ilies, R. Organizational Behavior and Human Decision Processes The role of self-efficacy, goal,
and affect in dynamic motivational self-regulation. Organ. Behav. Hum. Decis. Process. 2009, 109, 120–133.
[CrossRef]
Harris, C.; Daniels, K.; Briner, R.B. A daily diary study of goals and affective well-being at work. J. Occup.
Organ. Psychol. 2003, 76, 401–410. [CrossRef]
Hoppmann, C.A.; Klumb, P.L. Daily management of work and family goals in employed parents.
J. Vocat. Behav. 2012, 81, 191–198. [CrossRef]
Scott, B.A.; Colquitt, J.A.; Paddock, E.L.; Judge, T.A. A daily investigation of the role of manager empathy on
employee well-being. Organ. Behav. Hum. Decis. Process. 2010, 113, 127–140. [CrossRef]
Hakanen, J.J.; Perhoniemi, R.; Toppinen-Tammer, S. Positive gain spirals at work: From job resources to work
engagement, personal initiative and work-unit innovativeness. J. Vocat. Behav. 2008, 73, 78–91. [CrossRef]
Baron, R.A.; Hmieleski, K.M.; Henry, R.A. Entrepreneurs’ dispositional positive affect: The potential benefits
and potential costs of being “up”. J. Bus. Ventur. 2012, 27, 310–324. [CrossRef]
Bledow, R.; Rosing, K.; Frese, M. A dynamic perspective on affect and creativity. Acad. Manag. J. 2013, 56,
432–450. [CrossRef]
Ayala, Y.; Peiró, J.M.; Tordera, N.; Lorente, L.; Yeves, J. Job satisfaction and innovative performance in young
Spanish employees: Testing new patterns in the Happy-Productive Worker Thesis. A discriminant study.
J. Happiness Stud. 2017, 18, 1377–1401. [CrossRef]
Warr, P.; Nielsen, K. Wellbeing and work performance. In Handbook of Well-Being; Diener, E., Oishi, S., Tay, L.,
Eds.; DEF Publishers: Salt Lake City, UT, USA, 2018.
Cooper, C.L.; Rout, U.; Faragher, B. Mental health, job satisfaction, and job stress among general practitioners.
Br. Med. J. 1989, 298, 366–370. [CrossRef]
Ryff, C.D. Happiness is everything, or is it? explorations on the meaning of psychological well-being.
J. Personal. Soc. Psychol. 1989, 57, 1069–1081. [CrossRef]
Williams, L.; Anderson, S. Job Satisfaction and Organizational Commitment as Predictors of organizational
citizenship and in-role behaviors. J. Manag. 1991, 17, 601–617. [CrossRef]
Mackenzie, S.B.; Podsakoff, P.M.; Podsakoff, N.P. Challenge oriented organizational citizenship behaviors
and organizational effectiveness: Do challenge-oriented behaviors really have an impact on the organization’s
bottom line. Pers. Psychol. 2011, 64, 559–592. [CrossRef]
Chiu, T.; Fang, D.; Chen, J.; Wang, Y.; Jeris, C. A robust and scalable clustering algorithm for mixed type
attributes in large database environment. In Proceedings of the 7th ACM SIGKDD International Conference
in Knowledge Discovery and Data Mining, Association for Computing Machinery, San Francisco, CA, USA,
26–29 August 2001; pp. 263–268.
Mooi, E.; Sarstedt, M. Cluster analysis. In A Concise Guide to Market Research; Mooi, E., Sarstedt, M., Eds.;
Springer: Heidelberg, Germany, 2010; pp. 237–284.
Kent, P.; Jensen, R.K.; Kongsted, A. A comparison of three clustering methods for finding subgroups in MRI,
SMS or clinical data: SPSS TwoStep Cluster analysis, Latent Gold and SNOB. BMC Med. Res. Methodol. 2014,
14, 113. [CrossRef] [PubMed]
© 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
ORIGINAL RESEARCH
published: 18 April 2019
doi: 10.3389/fpsyg.2019.00865
Personal Values and Innovative
Behavior of Employees
Ewelina Purc and Mariola Laguna*
The John Paul II Catholic University of Lublin, Lublin, Poland
Edited by:
Igor Portoghese,
University of Cagliari, Italy
Reviewed by:
Francesco Montani,
International University of Monaco,
Monaco
Juan Antonio Moriano,
National University of Distance
Education (UNED), Spain
*Correspondence:
Mariola Laguna
laguna@kul.pl
Specialty section:
This article was submitted to
Organizational Psychology,
a section of the journal
Frontiers in Psychology
Received: 26 November 2018
Accepted: 02 April 2019
Published: 18 April 2019
Citation:
Purc E and Laguna M (2019)
Personal Values and Innovative
Behavior of Employees.
Front. Psychol. 10:865.
doi: 10.3389/fpsyg.2019.00865
Frontiers in Psychology | www.frontiersin.org
Innovations are based on the good ideas of individuals; therefore, it is very important to
better understand the role that individuals and their personal characteristics play in
innovative initiatives. The aim of the current study was to test the relationships between
employees’ personal values and their innovative behavior. It was hypothesized that these
relationships are mediated by an employee’s job autonomy. We integrated Schwartz’s
basic human values theory with the notion that job autonomy is an important job
characteristic that can be redesigned to better fit employees’ preferences. The study
results (obtained from 263 employees in different branches) showed that openness to
change and self-enhancement values are positively related to job autonomy, whereas
conservation and self-transcendence values are negatively related to job autonomy, which
confirms that personal values are important in explaining autonomy in the workplace. In
addition, employees’ self-enhancement values are positively related to their innovative
behavior, while conservation and self-transcendence values are negatively related to
innovative behavior. Mediation analysis with a bias-corrected bootstrapping method
showed that job autonomy is a significant mediator of the relationships between employees’
personal values (except for openness to change) and their innovative behavior. Our
research extends the theory of basic human values, showing that values serve as a
personal basis for innovative behavior. Our results also contribute to the innovation research
by demonstrating the importance of personal values and job autonomy for innovative
behavior in organizations.
Keywords: values, innovation, innovative behavior, job autonomy, employees
INTRODUCTION
Innovation is widely recognized as important for the effectiveness and success of organizations
(Yuan and Woodman, 2010; Anderson et al., 2014; Razmus and Laguna, 2018). Due to the
growing demands and expectations of customers and the global expansion of markets, innovation
has become important for companies (Anderson et al., 2018). The importance of innovation
has also been noted by scientists, and research concerning innovation and creativity has garnered
much attention from scholars in the last 20–30 years (de Jong and den Hartog, 2010). Although
there is a significant amount of empirical evidence regarding the antecedents of innovative
behavior in organizations, there is still a need for more research on predictors (Hammond
et al., 2011). It is particularly important to better recognize the psychological mechanisms
that are conducive to employee innovation, extending the knowledge gained from management
1
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
research investigating organizational variables. In their recent
review, Anderson et al. (2018) called for more research to
broaden our understanding of individual innovation in
organizations. Addressing this gap in the literature, we explain
employees’ innovative behavior in our study.
Employees are the individuals who create and implement
innovative solutions in organizations; therefore, their behaviors
are critical to organizational innovation. The literature provides
evidence of some individual innovation antecedents (for a
review, see West, 2002; Anderson et al., 2004, 2014, 2018;
Hammond et al., 2011); however, only recently has research
started to investigate the role of personal values in explaining
innovation. Because personal values are the guiding principles
in people’s lives, affecting their goals and actions (Schwartz,
1992), it is important to study their roles in employees’
innovation (Anderson et al., 2014). It is particularly promising
because values are postulated as being important drivers of
actions in organizational settings (Meglino and Ravlin, 1998;
Sagiv et al., 2011a). However, empirical studies concerning
these relationships are scarce.
Responding to this literature gap, the present study applies
Schwartz’s theory of basic human values (Schwartz, 1992) to
explain which factors foster innovative behavior in employees.
We also postulate the potential mechanism, testing job autonomy
as a mediator in the relationships between personal values
and innovative behavior. In addition, we propose a new approach
to job autonomy as an individual perception of a workplace
setting that can be fostered by an employee’s personal values.
In the subsequent sections, detailed explanations concerning
all relationships that are considered in this study will
be presented.
The study contributes to the literature by providing new
insight into Schwartz’s theory of basic human values (Schwartz,
1992), job characteristics theory (Hackman and Oldham, 1976),
and the innovation literature. Namely, it extends these theories
by testing whether personal values motivate people to shape
their work conditions and stimulate their innovative behavior
in the workplace. Moreover, whereas most of the previous
research has focused on the organizational level of innovation
(see meta-analyses: Damanpour, 1991; Rosenbusch et al., 2011),
our research proposes a conceptual model of a mechanism
stimulating employees’ workplace innovation, combining both
individual and contextual factors. Based on this approach,
we answer the recent call in the innovation literature to reveal
the mechanisms through which innovation can be driven
(Hammond et al., 2011; Anderson et al., 2014, 2018).
daily challenges at work (Amabile, 1988; Camisón-Zornoza
et al., 2004; Weinberger et al., 2018). The small-scale innovations
manifesting themselves in everyday innovative behavior are
based on creative ideas (Weinberger et al., 2018). However,
innovative behavior includes not only generating ideas (which
is specific for creativity; Amabile, 1988) but also implementing
them in organizations (Scott and Bruce, 1994). As creativity
is considered a first step toward innovation (West and Farr,
1992; Amabile, 1996; Anderson et al., 2014), in the subsequent
sections, we utilize both the creativity and innovation literature
to build our arguments and hypotheses concerning the
relationship between employees’ personal values and
innovative behavior.
The theory of basic human values proposed by Schwartz
(1992) is currently considered to be the most comprehensive
and empirically grounded approach to human values (Sagiv
et al., 2011a; Cieciuch, 2013). Schwartz argued that values are
“desirable transsituational goals, varying in importance, that
serve as guiding principles in the life of a person or other
social entity” (Schwartz, 1994, p. 21). Values have motivational
power by providing direction and emotional intensity to action
and by being acquired through socialization, in the context of
dominant group values, as well as through individual learning
(Schwartz, 1994). The central assumption of the theory is that
basic values form a universal, circular continuum and are
organized in accordance with the motivation that they express.
Relationships between motivations can be compatible, conflictual,
or irrelevant to one another (Schwartz, 1992). Due to its structure,
the value continuum can be partitioned in different manners
(Sagiv and Roccas, 2017). Ten initially described basic values
can be structured into the following two bipolar dimensions:
(1) openness to change (self-direction and stimulation) versus
conservation (tradition, conformity, and security) and (2) selftranscendence (universalism and benevolence) versus selfenhancement (power and achievement); hedonism values share
aspects of both dimensions (Schwartz, 1992). A distinction
between the four higher-order values representing the endpoints
of these two dimensions (i.e., openness to change, conservation,
self-enhancement, and self-transcendence) is frequently used in
research (e.g., Vecchione et al., 2015; Cieciuch et al., 2016) and
will be applied in our study.
Personal values are closely related to motivation and thus
help explain behavior (Cieciuch, 2017). Behavior, which expresses
people’s individual values, enables them to attain their goals and
personal aspirations (Sagiv and Schwartz, 2000; Bardi and Schwartz,
2003). People are motivated to behave in accordance with their
values because they look for a sense of consistency between
their beliefs and actions (Rokeach, 1973). Employees are therefore
willing to rely on their personal values in making decisions,
choosing actions, and justifying their behavior (Arieli and TenneGazit, 2017). The inability to implement and realize individual
values in the workplace has been found to be positively related
to job burnout (Retowski and Podsiadły, 2016) and negatively
related to job satisfaction (Amos and Weathington, 2008).
Personal values, being guiding principles in life, can also
affect people’s creativity and innovative behavior (Anderson
et al., 2014). Indeed, some studies have shown such relationships
Relationships Between Employees’
Personal Values and Innovative Behavior
Innovation, defined as the generation or adoption of useful
and novel ideas that are effectively introduced in organizations
(Amabile, 1988; Verhees and Meulenberg, 2004; Rosenbusch
et al., 2011), is important for their business success (Rosenbusch
et al., 2011). Innovation in organizations includes the introduction
not only of big ideas that significantly change existing practices
but also of small, incremental improvements in coping with
Frontiers in Psychology | www.frontiersin.org
2
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
Hypothesis 1a. Employees’ openness to change values
are positively related to their innovative behavior.
(Rice, 2006; Dollinger et al., 2007; Kasof et al., 2007; Lipponen
et al., 2008; Sousa and Coelho, 2011). Nevertheless, this evidence
is relatively scarce and is partially derived from student samples
(e.g., Dollinger et al., 2007; Kasof et al., 2007). Therefore, there
is a need to systematically examine how exactly personal values
are related to innovative behavior in the workplace, a point
that has been recently emphasized by scholars (Anderson et al.,
2014, 2018). Bardi and Schwartz (2003), p. 5, stated that “the
natural way to pursue important values is to behave in ways
that express them or promote their attainment.” Therefore,
we expect some values to foster innovative behavior in employees
and others to be negatively related to it. As very little empirical
research investigating such relationships has been conducted,
our hypotheses are based mostly on theoretical assumptions
derived from Schwartz’s values theory (Schwartz, 1992) and
on research findings concerning creativity.
The higher-order value of openness to change comprises
self-direction and stimulation (Schwartz, 1992). According to
the theory of basic human values, the motivational goals of
openness to change are a willingness to choose, create, and
explore and a preference for novelty (Schwartz, 1992) and
change (Ros et al., 1999). Self-direction has been argued to
be the value that is the most important for creativity for at
least two reasons (Dollinger et al., 2007). First, creativity was
one of the specific values used by Schwartz (1992) to capture
self-direction. Second, because the motivational goal of selfdirection involves independence in thought and action, selfdirection can be reflected through exploration and free choice
in following individual interests, which are perceived to be crucial
for creative individuals (Helson, 1990; Barron, 1997). Because
self-directed people prefer to be independent both in thought
and in action, this value seems to be conducive not only to
the generation of creative ideas but also to innovation
implementation. The motivational goal of stimulation in
Schwartz’s theory (Schwartz, 1992) involves seeking novelty,
excitement and challenges in life. Therefore, the value of
stimulation also seems to promote innovative behavior as a
method of attaining these goals. These characteristics allow us
to suppose that openness to change values will be the most
favorable to innovative behavior among all other higher-order
values. Indeed, researchers have reasoned that due to their
motivational meanings, openness to change values are associated
with innovation and creativity (Arieli and Tenne-Gazit, 2017),
and previous empirical research has confirmed the relationships
between these constructs. Kasof et al. (2007) found that both
self-direction and stimulation are positively related to individual
creative performance. Another study showed that openness to
change values positively predict creativity (Dollinger et al.,
2007). Employees who ranked low on openness to change
were found to be less creative (Sousa and Coelho, 2011), and
self-direction was positively related to employee creative behavior
(Rice, 2006). Based on Schwartz’s (1992) theory, we can expect
that when employees strongly value novelty, experimentation,
and exploration (typical for people with openness to change
values), they will be willing to behave innovatively. Because
of these theoretical assumptions and previous research findings,
we developed the following hypothesis.
Frontiers in Psychology | www.frontiersin.org
In contrast, conservation values, which include conformity,
security, and tradition (Schwartz, 1992), seem to have a negative
effect on employees’ innovativeness. Such values predispose an
individual to accept customary behavior and established
procedures and ideas, which are undoubtedly not conducive
to innovativeness (Schwartz and Bardi, 2001; Schwartz, 2006;
Sousa et al., 2012). Because the motivational goal of conformity
is to restrain actions, inclinations, and impulses to avoid
upsetting or violating social norms and expectations (Schwartz,
1992), employees who attribute high importance to this value
may avoid undertaking innovative initiatives because it may
produce changes that are not easily welcomed by others in
their organizations. Employees’ security values also do not seem
to be favorable for innovative behavior because they focus on
stability, safety, and harmony, whereas implementing innovations
in companies often requires breaking the status quo and
disrupting established organizational conventions, norms, and
procedures. Tradition values emphasize the acceptance of
imposed, traditional customs and ideas (Schwartz, 1992).
Innovative activities are not congruent with such an approach,
and employees who want their innovative ideas to
be implemented in organizations should definitely take the
initiative on their own and strive for idea realization, which
sometimes requires substantial effort. These theoretical
expectations are somewhat supported by previous research
findings. Dollinger et al. (2007) confirmed the negative
relationship between conservation values and creative
accomplishments. A study conducted by Lipponen et al. (2008)
revealed that employees who emphasized conservation versus
openness to change values suggested fewer new initiatives for
change in the workplace. In addition, employees who ranked
high on conservation values tended to be less creative than
those who ranked high on openness to change values (Sousa
and Coelho, 2011), and employees who prioritized conformity
were less creative than those who instead preferred self-direction
(Rice, 2006). Moreover, Kasof et al. (2007) found that all three
conservation components – tradition, conformity, and security –
were negatively related to creative performance. Based on these
premises, we expect that an employee who is not willing to
introduce novelty and rejects alternative, unfamiliar methods
and new perspectives (which is typical for those who hold
conservation values) will not be willing to behave innovatively
(including idea generation, promotion and implementation)
because it may potentially disturb the status quo. Thus,
we developed the following hypothesis.
Hypothesis 1b. Employees’ conservation values are
negatively related to their innovative behavior.
Self-enhancement values are reflected in power and
achievement (Schwartz, 1992), both of which focus on social
esteem. Power reflects the goals of prestige, social status
attainment, and control or dominance over people and resources.
Implementing innovative ideas in the workplace can be a
3
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
potential method of attaining such goals because employees
who behave innovatively can be appreciated by managers who
strive for innovative performance at their firms (Janssen et al.,
2004). An employee can also perceive innovative behavior as
a means to obtain social prestige in an organization and to
have a leading, distinguished position among others. Furthermore,
the central goal of the value of achievement is personal success,
which is accomplished by demonstrating competence, in
accordance with social standards (Schwartz, 1992). Innovative
activities can help to achieve such a goal because an innovative
employee may attain a distinguished position among co-workers
and can be perceived as being successful. An employee’s
innovative behavior may also be appreciated by supervisors,
leading to benefits such as financial bonuses or promotions,
which may indicate prestige and status. Nevertheless, previous
research findings concerning relationships between selfenhancement values and creativity are not consistent. On the
one hand, Dollinger et al. (2007) found that power values had
a negative effect on creativity. On the other hand, Sousa and
Coelho (2011) found that bank employees who attributed high
importance to self-enhancement values were more creative in
their work. In addition, Taştan and Davoudi (2017) demonstrated
that both power and achievement values had a positive effect
on organizational innovativeness among employees in managerial
positions. These results seem to correspond with the finding
that power motivation is important for creative personality
(Helson, 1996), and the notion that strong achievement
orientation is demonstrated by creative people (Mumford, 2000;
Sousa and Coelho, 2011). Attaining goals related to power
and achievement values may be possible when people promote
and implement their creative ideas. These activities can help
employees gain prestige, increase their organizational status,
and be perceived as successful by co-workers and supervisors.
In conclusion, we postulate that employees who attribute high
importance to self-enhancement values are more willing to
behave innovatively.
Although there is some empirical evidence concerning the
relationship between self-transcendence and creativity, we do
not consider it to be sufficient to postulate a specific hypothesis
about how these values are related to innovative behavior in
the workplace as an activity that includes idea generation,
promotion, and implementation. The lack of sufficient evidence
is due to some inconsistencies in previous research and –
above all – the lack of clear theoretical premises on the potential
relationship direction between these variables.
Relationships Between Employees’
Personal Values and Autonomy
Personal values are considered to be the core of personality,
affecting attitudes, evaluations, and decisions (Feather, 1988)
and acting as a guiding force to peoples’ perceptions and
actions (Schwartz, 1994). Therefore, values can also be related
to employees’ job autonomy. We propose that a specific set
of values can predispose people to proactively strive for
autonomy in their work, while other values may not motivate
such a pursuit.
Autonomy is known to be one of the most frequently studied
phenomena in work and organizational settings (Morgeson and
Humphrey, 2006). It is a motivational tool (Sarros et al., 2002;
Biron and Bamberger, 2010) leading to positive work outcomes,
such as innovation and creativity (Hammond et al., 2011; Liu
et al., 2011; De Spiegelaere et al., 2014), job satisfaction, internal
work motivation (see Humphrey et al., 2007) and work
engagement (Halbesleben, 2010). In most of these studies,
autonomy is conceptualized, following Hackman and Oldham’s
(1976) job characteristics theory, which classifies autonomy as
one of the core job characteristics and defines it as the degree
of freedom and independence provided by a job. Such freedom
can be reflected in making decisions, scheduling work, and
determining work methods and procedures applied in an
organization. Another meaningful theoretical approach is selfdetermination theory (Ryan and Deci, 2000), which considers
autonomy as one of the three basic psychological needs and
suggests that the satisfaction of these needs is necessary for
people to flourish (Deci and Ryan, 2000). In this context,
autonomy is known to be supported by supervisors and their
human resource practices (Park and Jang, 2015), whereas in
job characteristics theory (Hackman and Oldham, 1976, 1980),
autonomy is acknowledged as an objective task characteristic
that can also be provided by the job itself. To integrate these
approaches and to extend them using insights from new theories
explaining employees’ proactive functioning (Wrzesniewski and
Dutton, 2001; Tims and Bakker, 2010), we propose another
perspective to capture employee job autonomy. We suggest that
(1) job autonomy is, to some extent, dependent on the work
environment and supervisor actions, such as human resource
practices, as postulated by the job characteristics theory (Hackman
and Oldham, 1976, 1980); however, (2) to some extent, job
autonomy can also be shaped by the employee on his/her
own. This argument aligns with the conception of proactive
actions as “the physical and cognitive changes individuals
make in the task or relational boundaries of their work”
Hypothesis 1c. Employees’ self-enhancement values are
positively related to their innovative behavior.
Self-transcendence values consist of universalism and
benevolence (Schwartz, 1992). They reflect an individual’s basic
need to establish social relations with other people (Arieli and
Tenne-Gazit, 2017). Being the most abstract among values,
they seem to be the most unrelated to the work context (Sousa
et al., 2012). However, there is some empirical evidence showing
that they can be related to creativity. Gump (2007) found that
universalism positively predicts creativity among college students.
Similarly, Kasof et al. (2007) showed that universalism is
positively correlated with undergraduate students’ creative
performance. In the study conducted by Dollinger et al. (2007),
higher self-transcendence values predicted both higher creative
accomplishments and more creative products. Nevertheless,
these studies were conducted using student samples. Conversely,
Sousa and Coelho (2011) found that frontline bank employees
who attributed high importance to self-transcendence were less
creative than those who had stronger self-enhancement values.
Frontiers in Psychology | www.frontiersin.org
4
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
(Wrzesniewski and Dutton, 2001, p. 179). Employees make
such self-initiated changes in their job features to customize
them to fit their strengths, passions, and motives (Berg et al.,
2008). Traditional job design theories, such as job characteristics
theory (Hackman and Oldham, 1976), consider managers as
job crafters because they design tasks for their subordinates
and, therefore, can change their motivations and satisfaction
(Wrzesniewski and Dutton, 2001). However, employees are able
to proactively redesign their jobs on their own, and such selfinitiated changes made in an employee’s own job demands
and job resources are postulated to help them attain or optimize
their work goals (Tims et al., 2012). Indeed, research has shown
that employees who participated in job redesign initiatives
experienced increases in job autonomy after 2 months (Tims
et al., 2013). Therefore, there is support for the theoretical
postulates that job autonomy can be influenced not only by
managers through top-down processes but also by employees
on their own. In this manner, we define job autonomy by
integrating existing theoretical conceptions.
As noted by Morgeson and Humphrey (2006), autonomy
has a central place in motivational work approaches. In addition
to being the most widely studied job characteristic, it is also
the most influential (Humphrey and Morgeson, 2008). Moreover,
job autonomy is the job characteristic related to innovative
behavior (e.g., Liu et al., 2011; De Spiegelaere et al., 2014;
Orth and Volmer, 2017), and it also seems to be related to
personal values. Thus, we concentrate on job autonomy in
our study.
We assume that an individual can strive to have more
autonomy at work when it is congruent with his/her personal
values. As personal values have been proven to develop in
the early stages of life and then be relatively stable across
time (Vecchione et al., 2015, 2016; Cieciuch et al., 2016), and
as job autonomy is more likely to change in relation to the
organizational context, the job itself, and the relationship between
the supervisor and the subordinate (Hackman and Oldham,
1976, 1980), we treat values as predictors of job autonomy.
Based on Schwartz’s (1992) theory, we expect that employees
can be more or less disposed toward seeking autonomy in
their work based on the basic personal values they prefer. A
person can be highly motivated to have an opportunity to
make decisions and feel independent at work because it is of
central significance to him/her, while another person might
focus on other attributes of the job and not strive for autonomy
because he/she does not consider it to be important for his/
her work functioning. As noted by Sagiv and Roccas (2017),
p. 4, values “represent desirable goals and reflect what people
consider important and worthy.” For instance, when an employee
attributes high importance to openness to change values, which
focuses on autonomy in thought and action, novelty, and
challenge, we can expect that he/she will pursue the highest
possible job autonomy. However, when an employee emphasizes
conservation values, the core of which is to maintain the status
quo and to follow norms and rules, he/she will be not as
motivated to strive for autonomy at work. Certainly, the fact
that a job is autonomous is also, to some extent, determined
by other factors, such as the nature of the job itself
Frontiers in Psychology | www.frontiersin.org
(e.g., artistic professions will be naturally more autonomous
than receptionist or cashier jobs), or by managers, who may
or may not allow their subordinates to make decisions, schedule
their work, or choose work methods on their own. Nevertheless,
drawing on the basic human values theory (Schwartz, 1992),
we expect job autonomy to be predicted by employees’ personal
values. Below, we formulate hypotheses related to each of the
four higher-order values.
Schwartz’s (1992) theory characterizes openness to change
values, which includes self-direction and stimulation, as being
focused on “independent action, thought and feeling, and
readiness for new experience” (Schwartz, 2003a, p. 269). The
central goal of self-direction is the person’s independence, both
in thinking and in acting. Schwartz states that self-direction
is based on the organismic needs for, on the one hand, control
and mastery and, on the other hand, requirements of autonomy
and independence (Schwartz, 1992). Stimulation is described
as being focused on novelty, challenge, and excitement. This
value type is derived from a need for stimulation and variety
to maintain an optimal level of activation (Schwartz, 1992).
These theoretical assumptions concerning self-direction and
stimulation, which constitute the openness to change values,
suppose that these values are particularly conducive to job
autonomy in employees. Sagiv and Schwartz (2004) argued
that among career counseling clients, self-direction is relevant
to initiating actions, self-reliance, and independence of thought
in making career decisions. Indeed, their findings confirmed
that the priority clients gave to self-direction was positively
correlated with their independent behavior, as assessed by career
counselors. There is also some evidence concerning the role
of personal values in professional choice. A stronger emphasis
on openness to change values predicts artistic and investigative
careers (Sagiv, 2002; Knafo and Sagiv, 2004) and entrepreneurial
career intentions (Gorgievski et al., 2017). Based on these
theoretical and empirical premises, we expect that the importance
that employees attribute to openness to change values is positively
related to their work autonomy.
Hypothesis 2a. Employees’ openness to change values
are positively related to their job autonomy.
Conservation values, which include the values of conformity,
security, and tradition, are in conflict with openness to change.
Conformity values are focused on self-restraint, including selfrestraint of actions, impulses, and inclinations, which are reflected
in everyday interactions with close others (Schwartz, 1992).
Valuing security motivates the maintenance of harmony, stability,
and safety of the self and relationships with others and society.
The tradition value emphasizes the respect and acceptance of
imposed traditional ideas and customs. Together, the conservation
values encourage status quo maintenance, resistance to change
and self-restriction to avoid violating social norms (Schwartz,
2003a). These characteristics do not seem to be conducive to
pursuing autonomy in the workplace. An employee who attributes
high importance to conservation values may accept the existing
situation and not strive to enhance his/her job autonomy
because it can be harmful for organizational rules and norms.
5
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
He/she may be afraid that attempts to increase work autonomy
could be negatively perceived by superiors or other co-workers.
There is some empirical evidence that can shed some light
on the potential relationship direction between an employee’s
conservation values and his/her work autonomy. In a study
conducted by Sagiv and Schwartz (2004), clients’ emphasis on
conformity values was found to be negatively related to their
independent behavior, which they expressed in the career
counseling process. Moreover, an emphasis on conservation
values predisposes individuals to engage in rather conventional
professions, such as accountants, administrative managers, or
receptionists, and to hold vocational interests that demand
following well-defined instructions and rules, systematic
operations, and obeying norms (Sagiv, 2002; Knafo and Sagiv,
2004). Because peoples’ professional choices affect the types
of behavior in which they are willing to engage in the workplace
(Holland, 1997; Arieli and Tenne-Gazit, 2017), we expect that
people who attribute great importance to conservation values
do not strive to enhance their job autonomy because it is not
congruent with their values. Therefore, we developed the
following hypothesis.
the welfare of all people, as well as nature (Schwartz, 1992).
The motivational goal of benevolence involves concern for
people who are relatively close, and this concern is expressed
in everyday interactions. As previously stated, selftranscendence is the most abstract higher-order value, and
it has been argued that it is not as strongly related to work
context as other values (Sousa et al., 2012). Nevertheless,
there is some empirical evidence concerning the effects of
the self-transcendence values on work-related issues. These
values were found to be positively related to altruistic and
pro-social behaviors at work, in contrast to the self-enhancement
values (Sosik et al., 2009; Schwartz, 2010). Moreover, in a
study that used social dilemma games, Sagiv et al. (2011b)
found that the participants who attributed high importance
to self-transcendence were more willing to cooperate with
others than those who emphasized self-enhancement. However,
there is no empirical evidence on the relationship between
self-transcendence and work autonomy. Based on theoretical
assumptions, we can expect that striving for autonomy is
not highly important to employees who emphasize selftranscendence. Instead, these employees are likely focused
on cooperating with co-workers, showing their concern for
others and being tolerant of all people. Nevertheless, theoretical
and empirical evidence does not seem to be sufficient to
postulate a direct relationship between employees’ selftranscendence and autonomy.
Hypothesis 2b. Employees’ conservation values are
negatively related to their job autonomy.
The higher-order value of self-enhancement includes power
and achievement (Schwartz, 1992). Power is focused on attaining
prestige, social status, dominant position, and control over
people and resources. The value of achievement is concentrated
on personal success, which can be attained through competence
demonstration. The theoretical assumption is that employees
who attribute high importance to self-enhancement values
will strive to have more autonomy in their workplaces. Feeling
autonomous and independent at work seems to be crucial to
attaining dominance and control over other co-workers and
to developing self-interest goals. An employee who is selfconfident and autonomous can express his/her competence
in the workplace. Thus, the motivational goals of selfenhancement can be attained. A highly autonomous job is
more challenging and creates feelings of personal responsibility
and control of outcomes at work (Hackman and Oldham,
1980; Sousa et al., 2012). Mumford (2000) argued that power
and achievement are strong motives for people who tend to
be independent. In addition, career counseling clients’
achievement values were found to be positively related to
their independent behavior (rated by counselors) (Sagiv and
Schwartz, 2004), and higher self-enhancement values predicted
entrepreneurial career intentions in students from different
countries (Gorgievski et al., 2017). Based on these premises,
we expect that employees’ self-enhancement values are positively
related to their autonomy at work.
Job Autonomy and Innovative Behavior
Job autonomy is known to be an important contextual antecedent
of creativity and innovation (Amabile et al., 1996; Hammond
et al., 2011; Anderson et al., 2014). In the meta-analysis
conducted by Hammond et al. (2011), job characteristics,
including job autonomy, were found to be the strongest predictors
of creativity and innovation among all predictors evaluated
in their study. Having freedom in performing their work,
employees are able to find and develop working methods that
fit them optimally (De Spiegelaere et al., 2015). Such “space”
is necessary for creativity and innovative behavior because
these actions are focused on experimenting and developing
the best approaches to solve problems (De Spiegelaere et al.,
2015). Accordingly, Dierdorff and Morgeson (2013), p. 694,
argued that “by having freedom in the work role (autonomy),
individuals are able to take the initiative and perform in a
creative manner because they are less constrained in their
role performance.”
A number of studies have confirmed that autonomy is
positively related to creativity and innovation. Job autonomy
was found to be positively related to employees’ innovative
behavior at work (Axtell et al., 2000; Ramamoorthy et al.,
2005; De Spiegelaere et al., 2014, 2015, 2016) and to job
creativity (Liu et al., 2011). In line with job characteristics
theory (Hackman and Oldham, 1976, 1980) and the selfdetermination theory (Deci et al., 1989; Ryan and Deci, 2000),
which emphasize the motivational role of job autonomy, and
based on the previous research findings, we postulate that job
autonomy is positively related to employees’ innovative behavior.
Hypothesis 2c. Employees’ self-enhancement values are
positively related to their job autonomy.
The higher-order value of self-transcendence encompasses
universalism and benevolence. Universalism is focused on
Frontiers in Psychology | www.frontiersin.org
6
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
Hypothesis 3. Employees’ job autonomy is positively
related to their innovative behavior.
Hypothesis 4. Employees’ job autonomy mediates the
relationships between openness to change (H4a),
conservation (H4b), self-enhancement (H4c), selftranscendence (H4d) values, and innovative behavior.
Job Autonomy as a Mediator Between
Personal Values and Innovative Behavior
Although personal values have been examined as predictors of
creativity and innovation in several studies (Dollinger et al.,
2007; Kasof et al., 2007; Sousa and Coelho, 2011), it is still
uncertain exactly how these relationships occur. For example,
in a study conducted by Choi (2004), there was no confirmation
of the mechanism proposing that innovative organizational
culture is related to innovation-use behavior through innovative
values. Therefore, it is necessary to seek other mechanisms
explaining individual innovation. Hence, responding to this
need, we not only postulate direct relationships between employees’
personal values and their innovative behavior but also propose
that job autonomy can mediate these relationships (Figure 1).
It should be mentioned that some previous studies have
treated job autonomy as a moderator, rather than a mediator,
of relationships between personal values and work outcomes
(e.g., Sousa et al., 2012; Sousa and Coelho, 2013). However,
we propose to go beyond this pattern and verify whether job
autonomy can play a mediating role. We base our expectation
on an understanding of job autonomy as not only “given” by
managers or derived from the job itself, as postulated by the
traditional job design framework (Hackman and Oldham, 1976,
1980), but also strengthened by employees on their own, which
is consistent with the proactivity conceptions (Wrzesniewski
and Dutton, 2001; Berg et al., 2008; Tims and Bakker, 2010).
Morgeson and Humphrey (2008) admit that managers are often
responsible for designing or redesigning their subordinates’
work and frequently must even customize the work design to
their employees’ individual competencies. Nevertheless, they
stress that workers also play the role of proactive ‘crafters’ of
their work, dynamically redesigning work to be more suitable
to their specific capabilities, interests, or to the situation
(Morgeson and Humphrey, 2008). We agree with this argument
and expect that employees’ pursuit of job autonomy is predicted
by their personal values, which are cognitive representations
of their basic motivations and, therefore, affect their choices,
decisions, and behaviors (Arieli and Tenne-Gazit, 2017; Sagiv
and Roccas, 2017). Thus, we propose testing whether job
autonomy mediates the relationship between personal values
and employees’ innovative behavior.
MATERIALS AND METHODS
Procedure
Private sector employees who worked in micro-, small-, and
medium-sized enterprises operating in Poland that employ
1–250 employees were invited to participate in the study.
Employees working for larger companies or corporations and
in the public sector were not asked to participate, as their
work may be regulated by stricter company rules (Frant, 1993).
The data were gathered through direct contact with the
participants using a paper-and-pencil questionnaire. Participation
in the study was voluntary, and the participants did not receive
any reward. Confidentiality and anonymity were ensured.
Participants
A total of 263 employees (including 138 women) participated
in this study. They ranged in age from 19 to 74 years (M = 33.88,
SD = 10.62). Concerning work contracts, 155 (55.6%) of the
participants were employed under full-time permanent contracts,
49 (18.6%) had temporary contracts, and 59 (25.8%) had
another type of work contract. Concerning education, 44.1%
of the respondents had a master’s degree, 10.3% had a bachelor’s
degree, 34.6% had finished high school, and only 8.7% had
graduated from vocational school; six participants (2.3%) did
not provide information about their education. The participants’
overall work tenure ranged from 2 months to 46 years
(M = 11.43 years, SD = 10.22). Their tenure in their present
company ranged from 1 month to 32 years (M = 5.63 years,
SD = 6.51). The companies at which they worked employed,
on average, approximately 56 people (M = 54.94, SD = 61.73,
Me = 20.00). The participants represented seven types of
occupations classified according to the International Standard
Classification of Occupations (ISCO-08, 2012): professionals
(36.9%), craft and related trade workers (19.8%), service workers
and shop sales workers (18.3%), technicians and associate
professionals (13.7%), clerks (4.9%), plant and machine operators
and assemblers (3.0%), and elementary occupations (1.9%).
Measures
Personal Values
To measure the personal values of the employees, the 21-item
Portrait Values Questionnaire (PVQ-21) was used (Schwartz,
2003a). The measure is not cognitively challenging and is
appropriate even for people with little or no formal schooling
(Cieciuch, 2013; Roccas et al., 2017). The measure includes
21 statements that provide a verbal portrait of different people
(i.e., their goals, aspirations, or wishes), implicitly indicating
the significance of different value types (Schwartz, 2003a).
Sample items include the following: Thinking up new ideas
and being creative is important to him. He likes to do things
FIGURE 1 | Conceptual model of the relationships tested in the study.
Frontiers in Psychology | www.frontiersin.org
7
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
in his own original way; It is important to him to show his
abilities. He wants people to admire what he does. Using a
6-point scale ranging from 1 = very much like me to 6 = not
like me at all, for each item, the participants answered the
question, “How much like you is this person?” The participants’
responses were recoded so that a higher score reflected a
greater importance of the value. Particular items reflect basic
types of values, which can be structured into four higherorder values, namely openness to change, conservation, selfenhancement, and self-transcendence. Because hedonism is
a component of both self-enhancement and openness to
change values (Schwartz, 2003a), we decided to exclude it
from all further analyses, following previous research (e.g.,
Huysentruyt et al., 2015). Schwartz (2003a) claims that people
can differ in their tendencies to respond to value measures
when using the response scale (e.g., some people are likely
to use only one part of the response scale). Therefore, in
most statistical analyses, it is critical to control for such
individual differences (Schwartz, 2003b). Following this
recommendation, we centered raw scores by computing each
person’s mean score for all 21 items (i.e., the MRAT), and
then, we calculated the corrected scores by subtracting the
MRAT from the individual mean score for each value. In
the current study, the internal consistency of the scale was
evaluated using Cronbach’s alpha, with the following results:
0.56 for openness to change, 0.67 for conservation, 0.68 for
self-enhancement, and 0.72 for self-transcendence. Such
relatively low reliability results are typical for this measure
because of the structure of the questionnaire (i.e., different
components of the values are included in each higher-order
value) and because every higher-order value was composed
of a relatively small number of items (Schwartz, 2003a).
Therefore, the reliability results should not be treated as a
measurement weakness nor should they be considered
problematic for the research results. To verify the factorial
structure of the measure, confirmatory factor analysis (CFA)
using AMOS software (Arbuckle, 2005; Brown, 2006) was
performed. When assessing the model fit, CFI values higher
than 0.90 indicate an acceptable model fit, and for the RMSEA
and SRMR indices, values below 0.05 indicate a good model
fit and values below 0.08 (and up to 0.10) indicate an acceptable
fit; the lower the AIC index is, the better the model fits the
data (Brown, 2006). According to previous recommendations
(Cieciuch and Davidov, 2012), a one-factor model was tested
separately for each of four higher-order values. Concerning
openness to change, the factorial model showed good fit to
the data (χ2(2) = 0.089, p = 0.956, CFI = 1.00, AIC = 16.089,
RMSEA = 0.000, SRMR = 0.005). In the case of conservation, the
model also showed good fit to the data (χ2(9) = 23.666,
p = 0.005, CFI = 0.922, AIC = 47.666, RMSEA = 0.077,
SRMR = 0.047). When testing the self-enhancement model, the
analysis revealed that it had acceptable fit (χ2(8) = 6.343,
p = 0.042, CFI = 0.975, AIC = 22.343, RMSEA = 0.088,
SRMR = 0.032). Finally, when we analyzed the selftranscendence model, it also showed acceptable fit to the
data (χ2(5) = 16.039, p = 0.007, CFI = 0.954, AIC = 36.039,
RMSEA = 0.089, SRMR = 0.038).
Frontiers in Psychology | www.frontiersin.org
Job Autonomy
The autonomy experienced by employees at work was measured
with four items of the autonomy scale from the Work Design
Questionnaire (Morgeson and Humphrey, 2006). Each item of
the scale is a statement (e.g., My job allows me to make a lot
of decisions on my own; The job gives me a chance to use my
personal initiative or judgment in carrying out the work) to
which the participants should respond using a five-point answer
scale that ranges from 1 = strongly disagree to 5 = strongly
agree. In the present study, Cronbach’s alpha for the autonomy
scale was 0.90, which implies very good scale reliability.
We conducted CFA, and the one-factor model showed good
fit to the data (χ2(1) = 0.249, p = 0.617, CFI = 1.00, AIC = 36.039,
RMSEA = 0.000, SRMR = 0.003).
Innovative Behavior
The participants’ innovative behavior was measured using the
Innovative Behavior Questionnaire (Scott and Bruce, 1994).
The questionnaire includes six items (e.g., I generate creative
ideas; I develop adequate plans and schedules for the
implementation of new ideas). For each statement, the participants
answered how frequently they behaved as described in the
statement, using a five-point scale ranging from 1 = never to
5 = very often. In the present study, the scale reliability was
0.85, which indicates good internal consistency. CFA, which
was conducted following Purc and Laguna’s (2017)
recommendations, confirmed the one-factor structure of the
measure. The present study confirmed that such a model fits
well with the data (χ2(6) = 7.089, p = 0.313, CFI = 0.998,
AIC = 37.089, RMSEA = 0.026, SRMR = 0.015).
Data Analysis Strategy
The first step was to examine whether the data suffered from
the common method variance problem. Therefore, Harman’s
single factor test was employed (Podsakoff et al., 2012). This
technique is currently considered to be the most effective and
simplest method of testing common method variance (Fuller
et al., 2016). It can be applied by conducting exploratory factor
analysis (Razmus and Mielniczuk, 2018). If the one-factor
solution reveals that the percent of its explained variance
exceeds 50–60%, then the results suffer from the common
method variance (Fuller et al., 2016).
In the next step, descriptive statistics and correlations between
study variables were analyzed. Previous studies have suggested
that creativity and innovative behavior can be affected by sex
and age (Slagter, 2009; Alsos et al., 2013; Smith et al., 2016;
Hollanders and Es-Sadki, 2017). Therefore, we conducted a
hierarchical multivariate regression analysis to test whether
there were statistically significant effects of sex and age on
innovative behavior and, consequently, whether it was necessary
to control for these variables in further analyses.
The fundamental part of the data analysis was testing
the postulated hypotheses. To test the hypotheses, particularly
to verify whether job autonomy mediates the relationships
between personal values and innovative behavior, Model 4 in
the PROCESS macro (Hayes, 2013) for SPSS was applied.
8
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
The use of this macro allows the estimation of an indirect
effect by using a bootstrapping technique. Bias-corrected and
accelerated bootstrapping with 5,000 repetitions (5,000 samples
randomly generated from the whole sample) was applied in
the present analyses. In terms of interpreting the results, if
the confidence interval does not include zero, it indicates a
statistically significant mediation (indirect) effect. The hypotheses
concerning direct relationships were also verified based on the
PROCESS macro results.
behavior. Sex was coded as a dichotomous variable (0 = male
and 1 = female). The regression analysis results showed that
neither sex nor age was significant predictors of innovative
behavior (β = 0.04, p = 0.531; β = −0.02, p = 0.785, respectively).
Thus, we did not control for these variables in further analyses.
Hypotheses Testing
Mediation analyses were performed using the PROCESS
macro (Model 4, Hayes, 2013). All direct and indirect effects
were estimated based on these bootstrapped samples. For
each of the analyses, direct effects (a, b, and c, as shown
in Figure 1), an indirect effect (c′) with the bootstrapped
standard error (SEB), and 95% confidence intervals (CIs)
are reported in Table 2.
First, direct effects were examined to verify hypotheses
H1a–H1c. The analysis showed that two of the four higherorder values were related to innovative behavior. Openness to
change values were not found to be a significant predictor of
employee innovative behavior (B = 0.08, SEB = 0.06, p = 0.187).
Therefore, hypothesis H1a is rejected. Conservation values
showed a significant negative effect on innovative behavior
(B = −0.20, SEB = 0.07, p = 0.004), which supports hypothesis
H1b. Self-enhancement values were also revealed to be directly
related to innovative behavior. As expected, the higher the
importance that employees attributed to self-enhancement
values, the higher their innovative behavior (B = 0.17,
SEB = 0.06, p = 0.005). Thus, hypothesis H1c is supported.
When investigating the relationship between self-transcendence
values and innovative behavior, no statistically significant effect
was detected (B = 0.002, SEB = 0.07, p = 0.973). We also
examined whether employees’ personal values have a direct
relationship with their job autonomy, which was postulated
in hypotheses H2a–H2c. The results showed that all four
higher-order values were statistically significant predictors of
employees’ job autonomy. Openness to change values were
found to be a positive predictor of autonomy (B = 0.18,
SEB = 0.09, p = 0.046), which allows hypothesis H2a to
be accepted. Conservation values were negatively related to
perceived employees’ job autonomy (B = −0.22, SEB = 0.10,
p = 0.024), confirming hypothesis H2b. Self-enhancement values
were also shown to be a significant predictor of job autonomy,
and this effect was positive (B = 0.30, SEB = 0.09, p < 0.001).
This result indicates that hypothesis H2c is supported. Selftranscendence values were found to negatively predict employees’
RESULTS
Common Method Variance Test
To examine whether the data gathered in the study suffer
from the common method variance, Harman’s single factor
test was applied (Podsakoff et al., 2003; Fuller et al., 2016).
All items of all measures used in the study were loaded into
an exploratory factor analysis. An unrotated solution was used.
The results showed that a single factor that accounted for
most of the covariance among measures did not appear. A
three-factor solution was obtained, and the first factor explained
43.93% of the variance, which did not exceed 50% of the
variance explained (Fuller et al., 2016). Therefore, it was not
necessary to control for common method variance in
further analyses.
Descriptive Statistics and Correlations
Between the Study Variables
Descriptive statistics and Pearson’s correlations are reported in
Table 1. In terms of personal values, the correlations between
both bipolar dimensions are statistically significant and negative,
which reflect their opposite positions on the motivational value
continuum and aligns with Schwartz’s values theory (Schwartz,
1992). Openness to change values were negatively correlated
with conservation (r = −0.69, p < 0.001), and self-enhancement
values were negatively correlated with self-transcendence values
(r = −0.54, p < 0.001).
Control Variables
A hierarchical multivariate regression analysis was applied to
test whether there was a statistically significant effect of sex
and age on innovative behavior. Therefore, these two variables
were entered into the model as predictors explaining innovative
TABLE 1 | Means, standard deviations, and correlations between study variables (N = 263).
Variables
1
2
3
4
5
6
Openness to change
Conservation
Self-enhancement
Self-transcendence
Autonomy
Innovative behavior
M
SD
1
2
3
4
5
−0.02
0.09
−0.42
0.51
3.37
3.33
0.67
0.61
0.69
0.59
0.99
0.76
−0.69***
0.10
−0.28***
0.12*
0.08
−0.48***
0.12
−0.14*
−0.22***
−0.54***
0.21**
0.25***
−0.20**
−0.09
0.49***
Note: Pearson’s r correlations are reported. Openness to change, conservation, self-enhancement, and self-transcendence were centered. ***p < 0.001; **p < 0.01; *p < 0.05
(two tailed).
Frontiers in Psychology | www.frontiersin.org
9
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
TABLE 2 | Results of mediation analyses.
Direct effects
Indirect effect
Predictor
Openness to change
Conservation
Self-enhancement
Self-transcendence
a
b
c
c′
SEB
95% CI
0.18*
−0.22*
0.30***
−0.33**
0.37***
0.36*
0.35***
0.38***
0.08
−0.20**
0.17**
0.002
0.07
−0.08
0.10
−0.13
0.04
0.04
0.03
0.04
−0.01, 0.16
−0.17, −0.01
0.04, 0.18
−0.21, −0.05
Note: a = personal values – autonomy direct effect; b = autonomy – innovative behavior direct effect; c = personal values – innovative behavior direct effect; c′ = indirect effect of
autonomy. SEB = bootstrapped standard error; 95% CI = 95% confidence interval. For a, b, c and c′ effects, unstandardized B coefficients are reported. ***p < 0.001; **p < 0.01;
*p < 0.05.
job autonomy (B = −0.33, SEB = 0.10, p = 0.001). Therefore,
we can conclude that there is a significant negative relationship
between self-transcendence values and job autonomy in employees.
Hypothesis H3 aimed to test the potential positive relationship
between employees’ job autonomy and their innovative behavior.
The examination of a direct effect of autonomy on innovative
behavior confirms this hypothesis; job autonomy was a significant
predictor of innovative behavior, and this relationship was
positive in each of the four equations, including different
personal values (for openness to change, B = 0.37, SEB = 0.04,
p < 0.001; for conservation, B = 0.36, SEB = 0.04, p < 0.001;
for self-enhancement, B = 0.35, SEB = 0.04, p < 0.001; and
for self-transcendence, B = 0.38, SEB = 0.04, p < 0.001).
Next, indirect bootstrapped effects were analyzed to
verify hypotheses H4a–H4d. Hypothesis H4a postulated that
the relationship between openness to change values and
innovative behavior is mediated by job autonomy. The mediation
analysis showed that the indirect effect was nonsignificant
(B = 0.07, SEB = 0.04, 95% CI [−0.01, 0.16]) because the
95% CI included zero. Therefore, hypothesis H4a is not accepted.
The indirect effect of job autonomy on the relationship between
conservation values and innovative behavior was found to
be significant (B = −0.08, SEB = 0.04, 95% CI [−0.17, −0.01]),
thereby confirming hypothesis H4b. Hypothesis H4c is
supported as well – job autonomy was found to be a
significant mediator of the relationship between selfenhancement values and innovative behavior (B = 0.10,
SEB = 0.03, 95% CI [0.04, 0.18]). Finally, there was also a
significant indirect effect of job autonomy in the relationship
between self-transcendence values and innovative behavior
(B = −0.13, SEB = 0.04, 95% CI [−0.21, −0.05]). Thus, this
result indicates that hypothesis H4d is also confirmed. In
summary, three of the four specific mediation hypotheses are
supported. We can conclude that job autonomy is a significant
mediator of the relationships between personal values (i.e.,
conservation, self-enhancement, and self-transcendence, but
not openness to change) and employees’ innovative behavior.
their innovative behavior, on the one hand, and their job
autonomy, on the other hand. We also expected that job
autonomy mediates the relationships between values and
innovative behavior. The study results confirmed most of
our expectations.
Regarding the relationship between personal values and
employees’ innovative behavior, our results revealed the effects
of two of the four higher-order values, namely conservation
and self-enhancement values. As expected, employees who
attributed high importance to conservation values, which
involve maintaining the status quo and being resistant to change,
are less willing to behave innovatively at work. This result
supports the postulates derived from Schwartz’s (1992) theory,
which states that accepting established procedures, norms,
and customary manners of behavior, which are typical for
conservation values, is not conducive to innovative behavior
(Schwartz and Bardi, 2001; Schwartz, 2006; Sousa et al., 2012).
This result is also consistent with previous research demonstrating
negative relationships between conservation values and creativity
(Rice, 2006; Dollinger et al., 2007; Kasof et al., 2007; Lipponen
et al., 2008; Sousa and Coelho, 2011).
Our results also showed that self-enhancement values
positively predict employees’ innovative behavior. We postulated
that being innovative can help to attain personal success and
achieve a dominant position among other co-workers, which
are the central goals of self-enhancement values (Schwartz,
1992). Employees who strongly preferred this set of higherorder values were found to be more innovative, which is
consistent with previous research findings obtained by Sousa
and Coelho (2011) and Taştan and Davoudi (2017). Nevertheless,
our results are contradictory to those found by Dollinger
et al. (2007), who found that power is negatively related to
creativity. However, in their study, creativity was measured
by applying methods, such as drawing creative products,
developing creative stories or photo essays, which focused
on the artistic aspect of creativity of university students.
Therefore, the research context of this previous study differs
substantially from that in the present study, in which the
sample consisted of employees, and aims to investigate not
creativity but innovative behavior, which is strongly grounded
in the work context.
Our results also showed that there is no significant relationship
between employees’ self-transcendence values and innovative
behavior. This result aligns with the notion suggested by
DISCUSSION
The present study aimed to investigate the relationships between
personal values, job autonomy, and innovative behavior of
employees. We tested whether employees’ personal values predict
Frontiers in Psychology | www.frontiersin.org
10
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
Sousa et al. (2012), who argued that self-transcendence values
do not seem to be more strongly related to the work context
than other higher-order values. However, Arieli and TenneGazit (2017) recently proposed that universalism can be related
to creativity and innovation, and other research findings showed
that prosocial motivation may encourage idea development in
employees (Grant and Berry, 2011). Therefore, more research
concerning this issue is needed. Future research should
particularly test such relationships among employees and explain
not only idea generation (creativity) but also idea implementation
(innovative behavior). It may also be valuable for future research
to take into account prosocial motivation and include the
context of social relationships in organizations.
Job autonomy was found to be predicted by all four higherorder values. As we expected, employees who attribute high
importance to openness to change values (self-direction and
stimulation) experience more autonomy in their work. This
result aligns with Schwartz’s theory, which postulates that
openness to change values are focused on independent action
and thought and willingness to new experiences (Schwartz,
2003a). Our results confirmed that such motivation in employees
is accompanied by striving for more autonomy in their workplace.
Similarly, when employees value highly self-enhancement (power
and achievement), they also experience more autonomy in
their work. This result corresponds with the theory of basic
human values because people who attribute high importance
to self-enhancement values aim to attain success, prestige, and
a dominant position over other people and demonstrate
competence (Schwartz, 1992). These goals seem to be impossible
to attain without having a substantial level of autonomy at
work. This result is also consistent with Mumford’s arguments
that power and achievement are strong motives of independent
people (Mumford, 2000).
Employees’ conservation values were found to be negatively
related to job autonomy, which supports our expectations
[derived from Schwartz’s value theory (Schwartz, 1992)]. This
result also aligns with the results obtained by Sagiv and Schwartz
(2004), who demonstrated that career counseling clients who
attributed high importance to conformity values behaved less
independently during the counseling process. In sum, people
who attribute high importance to conservation values (conformity,
security and tradition), which focus on maintaining the status
quo, self-restriction, and resistance to change, are not strongly
predisposed to strive for job autonomy because it is potentially
disturbing to established social organizational norms.
Our results also revealed that employees’ self-transcendence
values are negatively related to their autonomy at work. It
seems that people for whom these values are of great importance
are not as focused on themselves but instead care about other
people and the environment (Schwartz, 1992). They are more
concentrated on pro-social and altruistic behaviors at work
(Sosik et al., 2009; Schwartz, 2010) and on cooperating with
others (Sagiv et al., 2011b) than on increasing their own job
autonomy, which can be harmful for the autonomy of their
co-workers or managers.
In summary, the results of the present study confirmed
our expectations that employees’ personal values are important
Frontiers in Psychology | www.frontiersin.org
predictors of their job autonomy. The results seem to support
the argument that jobs may be proactively redesigned by
employees to be more convergent with their preferences and
characteristics, such as their personal values (Wrzesniewski
and Dutton, 2001; Berg et al., 2010). Nonetheless, it should
be noted that, according to the traditional approach to job
design (Hackman and Oldham, 1976, 1980), employee
job autonomy is usually treated as a rather objective job
characteristic, which depends on the nature of the job itself
and on supervisors (Park and Jang, 2015). Thus, job autonomy
is often considered to be a contextual moderator in explaining
organizational phenomena (e.g., Molleman and van den Beukel,
2007; Sousa et al., 2012). However, we conducted an additional
analysis of differences between various occupations1, and
no significant differences in job autonomy were revealed
(F(6, 251) = 1.29, p = 0.261). Therefore, the level of job autonomy
does not depend on the occupation type. This result supports
our approach and suggests that the fact that different people
have different levels of job autonomy may be a result of
their own efforts; some people are motivated to strive for
job autonomy (because it is congruent with their personal
values), whereas others are not (when their values do not
foster being autonomous). It is not only the nature of a job
(assuming that some jobs are more autonomous than others)
but also the personal characteristics of an employee that can
shape the level of job autonomy that he/she experiences at
work. This notion is in line with job crafting theory, which
emphasizes that employees are proactive crafters of their work
environment – their role is not reduced to working under
the conditions imposed by their managers, as they can also
actively shape their jobs to make them better fit their
expectations and preferences (Wrzesniewski and Dutton, 2001;
Berg et al., 2010). Future studies may examine behaviors that
help to craft a job in terms of job autonomy to fit employees’
personal value preferences.
In the present study, we did not find a significant relationship
between employees’ openness to change values and their
innovative behavior. Schwartz’s (1992) theory allows us to
postulate that these values are positively related to creativity
and innovation. Motivational goals of openness to change
(i.e., the willingness to create, choose, explore, preference
for novelty, and change) seem to encourage people to behave
in innovative ways. Indeed, previous research findings have
shown that there are positive relationships between openness
to change values and creativity (Rice, 2006; Dollinger et al.,
2007; Kasof et al., 2007; Sousa and Coelho, 2011). However,
in the present study, the relationship between openness to
change and innovative behavior was not statistically significant.
We consider several potential reasons for this result. First,
some previous studies that found a positive association between
openness to change values and creativity were conducted
with student samples (Dollinger et al., 2007; Kasof et al.,
2007). Second, because of a lack of research examining the
role of individuals’ personal values on their innovative behavior,
Occupations were differentiated according to the International Standard
Classification of Occupations (ISCO-08, 2012).
1
11
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
our expectations were primarily based on theoretical
contributions and previous research on creativity. However,
although creativity and innovative behavior are similar
constructs, they are not equivalent (Anderson et al., 2014;
Purc et al., 2015). Innovative behavior includes not only idea
generation but also seeking support for the idea and its
implementation (Scott and Bruce, 1994; Amabile, 1997; West,
2002; Anderson et al., 2004; Hammond et al., 2011), which
demands cooperation with others within an organization.
This again raises the issue of social relationships between
managers and employees as well as among employees, which
may be considered in future studies.
The present study aimed to explain the mechanism through
which the personal values of employees relate to their innovative
behavior. Our results revealed that job autonomy was a significant
mediator of the relationships between three among four higherorder values (conservation, self-enhancement, and selftranscendence) and innovative behavior. The relationship between
openness to change and innovative behavior was not mediated
by job autonomy. Future research is needed to find other
mechanisms through which such a relationship may occur.
The mediation analysis results generally support our postulations
that personal values not only motivate the pursuit of job
autonomy but also are indirectly associated with innovative
behavior. In addition, our study supports other findings indicating
that job autonomy predicts innovative behavior (Axtell et al.,
2000; Ramamoorthy et al., 2005; De Spiegelaere et al., 2014,
2015, 2016). We can conclude that employees’ personal values
serve as a predisposition for functioning in the workplace
and, together with other variables, such as job autonomy, relate
to innovative behavior.
Another limitation that should be addressed is that we used
self-reports to measure study variables. Self-report measures
seem to be the most appropriate solution to assess personal
values because values are subjective motivational goals (Roccas
et al., 2017). Similarly, the measurement of job autonomy seems
to be necessarily subjective because the most important aspect
is how an employee perceives autonomy in his/her work, not
how others observe it. Objective measures of autonomy are
difficult to obtain and may not refer to an employee’s actual
feeling of being independent at work. Thus, self-report measures
seem to be the best solution to capture perceived job autonomy.
Innovative behavior was subjectively rated by employees as
well, which may not reflect their actual behavior, and responses
can be biased due to social desirability (Zacher et al., 2016).
However, it was found that there is a significant positive
correlation between the self-ratings of innovative behavior and
the objective measure of invention disclosures (Scott and Bruce,
1994). In addition, Janssen (2000, 2001) found that employees’
self-ratings of innovative behavior were correlated with their
supervisors’ ratings. Some researchers have also argued that
employees are a good source of information about their own
creativity and innovative performance (Organ and Konovsky,
1989; Janssen, 2000, 2004; Shalley et al., 2009) because it is
a rather discretionary behavior, and the ratings of other people
(e.g., managers or co-workers) may miss subtle, less visible
innovative activities, capturing only those that are designed
to make an impression. Future research should consider such
problems, and researchers may use other measures.
Our study was performed in a single country, namely Poland.
Because cultural differences at the societal level (Hofstede,
1980) have been considered important with respect to innovation
(Rosenbusch et al., 2011), these differences may also influence
the relationships between values and innovative behavior.
Therefore, future cross-cultural research and/or research in
other cultural contexts is encouraged.
Limitations
When testing the mediation mechanism, we should remember
that the present study is cross-sectional, and thus, no causal
conclusions can be drawn, which constitute a limitation of
this study. Nevertheless, as personal values develop in childhood
(Vecchione et al., 2015, 2016; Cieciuch et al., 2016), job
autonomy is relatively changeable because it is dependent
on the organizational context (Hackman and Oldham, 1976,
1980) and because innovative behavior based on creative
ideas is performed during daily work duties (Weinberger
et al., 2018), which justifies the direction of variables included
in our model. However, further research concerning the
relationships between employees’ personal values, job autonomy,
and innovative behavior employing a longitudinal or
experimental design is needed to discover the interplay
between these variables over time.
In the current study, we concentrated on the role of job
autonomy as a central motivational work characteristic
(Morgeson and Humphrey, 2006). However, job autonomy is
only one of the job features described by Hackman and
Oldham’s (1976) job characteristics theory. Therefore, future
studies should investigate the role of other job characteristics
in relation to personal values and in stimulating innovative
behavior in organizations.
Frontiers in Psychology | www.frontiersin.org
Practical Implications
The results of the study have some practical implications, which
can be useful for managers or human resource specialists.
First, it is very important to better understand the predictors
of innovative behavior in organizations because innovation is
one of the sources of organizational success and competitiveness
(Woodman et al., 1993). Personal values are relatively stable
characteristics (Schwartz, 1992), and as such, it is not easy to
adapt them to specific situations. Therefore, knowing which
of employees’ values are positively related to their innovative
behavior, human resource departments can use this knowledge
in the selection and recruitment process as well as in job
design initiatives. Employing and retaining employees with high
levels of self-enhancement values may increase the innovativeness
of an organization. Moreover, entrepreneurs and managers may
support employees’ innovative behavior by providing them with
more autonomy at work and, in this way, building a more
innovation-friendly job environment. It is also possible to
develop innovativeness through training programmes stimulating
creativity and teamwork that increase competencies to shape
12
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
an environment that promotes innovation and cooperate in
introducing changes (Białoń, 2010).
values perspective to examine antecedents of job autonomy
brings new insights to both basic human values theory and
job design theory.
CONCLUSIONS
ETHICS STATEMENT
Despite some limitations, our study offers valuable empirical
evidence that allows for theory development. The results provide
insight into the relationships between employees’ personal
values, job autonomy, and innovative behavior, which have
not been studied to date. Thus, they constitute a new perspective
in innovation research, extending insights from Schwartz’s
(1992) theory of basic human values to a new context. Namely,
our results show that personal values can stimulate innovative
behavior in the workplace. In addition, the present study
investigated not only the direct relationships between personal
values and innovative behavior but also the mediation
mechanism. Thus, we attempted to respond to the call to
reveal the mechanisms through which innovation can be driven,
which was recently emphasized in the innovation literature
(Hammond et al., 2011; Anderson et al., 2014, 2018). Moreover,
we also addressed suggestions that personal values, as well as
contextual factors, can explain behavior (Sousa et al., 2012;
Arieli and Tenne-Gazit, 2017), considering job autonomy as
an indicator of work context. Therefore, applying a personal
All procedures performed in this study were in accordance
with the ethical standards. Informed consent was obtained
from all individual participants included in the study.
Participation in the study was voluntary and the participants
did not receive any reward. Respondents were asked to fill in
a set of questionnaires. They were able to withdraw from the
study at each moment. The confidentiality and anonymity were
ensured. The study received the approval from the Ethical
Committee of The John Paul II Catholic University of Lublin,
Institute of Psychology.
AUTHOR CONTRIBUTIONS
EP and ML were involved in formulating the research question,
designing the study, writing the article, and drafting and
approving the final manuscript. EP was responsible for collecting
and analyzing the data.
REFERENCES
and implementation of ideas. J. Occup. Organ. Psychol. 73, 265–385.
doi: 10.1348/096317900167029
Bardi, A., and Schwartz, S. H. (2003). Values and behavior: strength and
structure of relations. Personal. Soc. Psychol. Bull. 29, 1207–1220. doi:
10.1177/0146167203254602
Barron, F. (1997). “Introduction” in Creators on creating: Awakening and cultivating
the imaginative mind. eds. F. Barron, A. Montuori, and A. Barron (New
York: Tarcher Perigee), 1–21.
Berg, J. M., Dutton, J. E., and Wrzesniewski, A. (2008). What is job crafting
and why does it matter? (Ann Arbor, MI: University of Michigan Ross
School of Business). Available at: http://www.bus.umich.edu/Positive/POSTeaching-and-Learning/ListPOS-Cases.htm [Access: 9 April 2019].
Berg, J. M., Grant, A. M., and Johnson, V. (2010). When callings are calling:
crafting work and leisure in pursuit of unanswered occupational callings.
Organ. Sci. 21, 973–994. doi: 10.1287/orsc.1090.0497
Białoń, L. (2010). Zarządzanie działalnością innowacyjną. 1st edn. (Warszawa:
Wydawnictwo PLACET).
Biron, M., and Bamberger, P. (2010). The impact of structural empowerment
on individual well-being and performance: taking agent preferences, selfefficacy and operational constraints into account. Hum. Relat. 63, 163–191.
doi: 10.1177/0018726709337039
Brown, T. A. (2006). Confirmatory factor analysis for applied research. (New
York: Guilford Press).
Camisón-Zornoza, C., Lapiedra-Alcamí, R., Segarra-Ciprés, M., and
Boronat-Navarro, M. (2004). A meta-analysis of innovation and organizational
size. Organ. Stud. 25, 331–361. doi: 10.1177/0170840604040039
Choi, J. N. (2004). Individual and contextual dynamics of innovation-use behavior
in organizations. Hum. Perform. 17, 397–414. doi: 10.1207/s15327043hup1704_3
Cieciuch, J. (2013). Kształtowanie się systemu wartości od dzieciństwa do wczesnej
dorosłości. (Warszawa: Wydawnictwo Liberi Libri).
Cieciuch, J. (2017). “Exploring the complicated relationship between values
and behaviour” in Values and behavior: Taking a cross-cultural perspective.
eds. S. Roccas, and L. Sagiv (Berlin: Springer), 237–248.
Cieciuch, J., and Davidov, E. (2012). A comparison of the invariance properties
of the PVQ-40 and the PVQ-21 to measure human values across German
Alsos, G. A., Ljunggren, E., and Hytti, U. (2013). Gender and innovation: state
of the art and a research agenda. Int. J. Gend. Entrep. 5, 236–256. doi:
10.1108/IJGE-06-2013-0049
Amabile, T. M. (1988). A model of creativity and innovation in organizations.
Res. Organ. Behav. 10, 123–167.
Amabile, T. M. (1996). Creativity in context: Update to “the social psychology
of creativity”. (Boulder, CO, US: Westview Press).
Amabile, T. M. (1997). Motivating creativity in organizations: on doing what you
love and loving what you do. Calif. Manag. Rev. 40, 39–58. doi: 10.2307/41165921
Amabile, T. M., Conti, R., Coon, H., Lazenby, J., and Herron, M. (1996).
Assessing the work environment for creativity. Acad. Manag. J. 39, 1154–1184.
doi: 10.2307/256995
Amos, E. A., and Weathington, B. L. (2008). An analysis of the relation between
employee-organization value congruence and employee attitudes. J. Psychol.
142, 615–631. doi: 10.3200/JRLP.142.6.615-632
Anderson, N., De Dreu, C. K. W., and Nijstad, B. A. (2004). The routinization
of innovation research: a constructively critical review of the stateof-the-science. J. Organ. Behav. 25, 147–173. doi: 10.1002/job.236
Anderson, N., Potočnik, K., Bledow, R., Hülsheger, U. R., and Rosing, K. (2018).
“Innovation and creativity in organizations” in The SAGE Handbook of
Industrial, Work and Organizational Psychology. Vol. 3. Second edn. eds. D.
S. Ones, N. Anderson, H. K. Sinangil, and C. Viswesvaran. (London: SAGE
Publications). doi: 10.4135/9781473914964
Anderson, N., Potočnik, K., and Zhou, J. (2014). Innovation and creativity in
organizations: a state-of-the-science review, prospective commentary, and
guiding framework. J. Manag. 40, 1297–1333. doi: 10.1177/0149206314527128
Arbuckle, J. (2005). Amos 6.0 user’s guide. (Spring House, PA: Amos
Development Corporation).
Arieli, S., and Tenne-Gazit, O. (2017). “Values and behavior in a work environment:
taking a multi-level perspective” in Values and behavior. Taking a crosscultural perspective. eds. S. Roccas, and L. Sagiv (Berlin: Springer), 115–141.
Axtell, C. M., Holman, D. J., Unsworth, K. L., Wall, T. D., and
Waterson, P. E. (2000). Shopfloor innovation: facilitating the suggestion
Frontiers in Psychology | www.frontiersin.org
13
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
and Polish samples. Surv. Res. Method. 6, 37–48. doi: 10.18148/srm/2012.
v6i1.5091
Cieciuch, J., Davidov, E., and Algesheimer, R. (2016). The stability and change
of value structure and priorities in childhood: a longitudinal study. Soc.
Dev. 25, 503–527. doi: 10.1111/sode.12147
Damanpour, F. (1991). Organizational innovation: a meta-analysis of effects
of determinants and moderators. Acad. Manag. J. 34, 555–590. doi:
10.2307/256406
de Jong, J. P. J., and den Hartog, D. (2010). Measuring innovative work behaviour.
Creat. Innov. Manag. 19, 23–36. doi: 10.1111/j.1467-8691.2010.00547.x
De Spiegelaere, S., Gyes, G., and Hootegem, G. (2016). Not all autonomy is
the same. Different dimensions of job autonomy and their relation to work
engagement and innovative work behavior. Hum. Factor. Ergon. Manuf. Serv.
Ind. 26, 515–527. doi: 10.1002/hfm.20666
De Spiegelaere, S., Van Gyes, G., De Witte, H., Niesen, W., and Van Hootegem, G.
(2014). On the relation of job insecurity, job autonomy, innovative work
behaviour and the mediating effect of work engagement. Creat. Innov. Manag.
23, 318–330. doi: 10.1111/caim.12079
De Spiegelaere, S., Van Gyes, G., De Witte, H., and Van Hootegem, G. (2015).
Job design, work engagement and innovative work behavior: a multi-level
study on Karasek’s learning hypothesis. Manag. Rev. 26, 123–137. doi: 10.1688/
mrev-2015-02-DeSpiegelaere
Deci, E. L., Connell, J. P., and Ryan, R. M. (1989). Self-determination in a
work organization. J. Appl. Psychol. 74, 580–590. doi: 10.1037/0021-9010.74.4.580
Deci, E. L., and Ryan, R. M. (2000). The ‘what’ and ‘why’ of goal pursuits:
human needs and the self-determination of behavior. Psychol. Inq. 11:227.
doi: 10.1207/S15327965PLI1104_01
Dierdorff, E. C., and Morgeson, F. P. (2013). Getting what the occupation
gives: exploring multilevel links between work design and occupational
values. Pers. Psychol. 66, 687–721. doi: 10.1111/peps.12023
Dollinger, S. J., Burke, P. A., and Gump, N. W. (2007). Creativity and values.
Creat. Res. J. 19, 91–103. doi: 10.1080/10400410701395028
Feather, N. T. (1988). From values to actions: recent applications of the
expectancy-value model. Aust. J. Psychol. 40, 105–124. doi:
10.1080/00049538808259076
Frant, H. (1993). Rules and governance in the public sector: The case of civil
service. Am. J. Pol. Sci. 37, 990–1007. doi: 10.2307/2111540
Fuller, C. M., Simmering, M. J., Atinc, G., Atinc, Y., and Babin, B. J. (2016).
Common methods variance detection in business research. J. Bus. Res. 69,
3192–3198. doi: 10.1016/j.jbusres.2015.12.008
Gorgievski, M. J., Stephan, U., Laguna, M., and Moriano, J. A. (2017). Predicting
entrepreneurial career intentions: values and the theory of planned behavior.
J. Career Assess. 26, 457–475. doi: 10.1177/1069072717714541
Grant, A. M., and Berry, J. W. (2011). The necessity of others is the mother
of invention: intrinsic and prosocial motivations, perspective taking, and
creativity. Acad. Manag. J. 54, 73–96.
Gump, N. W. (2007). Creativity and self knowledge: Predicting creativity with
values and vocational interests measures. (US: ProQuest Information & Learning).
Hackman, J. R., and Oldham, G. R. (1976). Motivation through the design of
work: test of a theory. Organ. Behav. Hum. Perform. 16, 250–279. doi:
10.1016/0030-5073(76)90016-7
Hackman, J. R., and Oldham, G. R. (1980). Work redesign. (Reading, MA:
Addison-Wesley).
Halbesleben, J. R. B. (2010). “A meta-analysis of work engagement: relationships
with burnout, demands, resources, and consequences” in Work engagement:
A handbook of essential theory and research. ed. A. B. Bakker (New York,
NY, US: Psychology Press), 102–117.
Hammond, M. M., Neff, N. L., Farr, J. L., Schwall, A. R., and Zhao, X. (2011).
Predictors of individual-level innovation at work: a meta-analysis. Psychol.
Aesthet. Creat. Arts 5, 90–105. doi: 10.1037/a0018556
Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional
process analysis: A regression-based approach (1 edition). (New York: The
Guilford Press).
Helson, R. (1990). “Creativity in women: outer and inner views over time” in
Sage focus editions. eds. M. A. Runco, and R. S. Albert, Vol. 115. Theories
of creativity (Thousand Oaks, CA, US: SAGE Publications), 46–58.
Helson, R. (1996). In search of the creative personality. Creat. Res. J. 9,
295–306. doi: 10.1207/s15326934crj0904_1
Frontiers in Psychology | www.frontiersin.org
Hofstede, G. (1980). Culture’s consequences: International differences in workrelated values. (Beverly Hills, CA: Sage).
Holland, J. L. (1997). Making vocational choices: A theory of vocational personalities
and work environments (Subsequent edition). (Odessa, Florida: Psychological
Assessment Resources).
Hollanders, H., and Es-Sadki, N. (2017). European Innovation Scoreboard 2017.
(Luxembourg: European Comission).
Humphrey, S. E., Nahrgang, J. D., and Morgeson, F. P. (2007). Integrating
motivational, social, and contextual work design features: a meta-analytic
summary and theoretical extension of the work design literature. J. Appl.
Psychol. 92, 1332–1356. doi: 10.1037/0021-9010.92.5.1332
Huysentruyt, M., Stephan, U., and Vujić, S. (2015 March). CEO’s values,
management style and firm performance: Evidence from social enterprise
in Europe. Available at: http://chaire-eppp.org/files_chaire/huysentruyt_
stephan_and_vujic_march_2015.pdf [Access: 9 April 2019].
ISCO-08 (2012). International standard classification of occupations. Volume 1:
Structure, group definitions and correspondence tables. (Geneva: International
Labour Office). Available at: http://www.ilo.org/public/english/bureau/stat/
isco/docs/publication08.pdf [Access: 9 April 2019].
Janssen, O. (2000). Job demands, perceptions of effort-reward fairness and
innovative work behaviour. J. Occup. Organ. Psychol. 73, 287–302. doi:
10.1348/096317900167038
Janssen, O. (2001). Fairness perceptions as a moderator in the curvilinear
relationships between job demands, and job performance and job satisfaction.
Acad. Manag. J. 44, 1039–1050. doi: 10.2307/3069447
Janssen, O. (2004). How fairness perceptions make innovative behavior more
or less stressful. J. Organ. Behav. 25, 201–215. doi: 10.1002/job.238
Janssen, O., van de Vliert, E., and West, M. (2004). The bright and dark sides
of individual and group innovation: a special issue introduction. J. Organ.
Behav. 25, 129–145. doi: 10.1002/job.242
Kasof, J., Chen, C., Himsel, A., and Greenberger, E. (2007). Values and creativity.
Creat. Res. J. 19, 105–122. doi: 10.1080/10400410701397164
Knafo, A., and Sagiv, L. (2004). Values and work environment: mapping 32
occupations. Eur. J. Psychol. Educ. 19, 255–273. doi: 10.1007/BF03173223
Lipponen, J., Bardi, A., and Haapamäki, J. (2008). The interaction between
values and organizational identification in predicting suggestion-making at
work. J. Occup. Organ. Psychol. 81, 241–248. doi: 10.1348/096317907X216658
Liu, D., Chen, X.-P., and Yao, X. (2011). From autonomy to creativity: a
multilevel investigation of the mediating role of harmonious passion.
J. Appl. Psychol. 96, 294–309. doi: 10.1037/a0021294
Meglino, B. M., and Ravlin, E. C. (1998). Individual values in organizations:
concepts, controversies, and research. J. Manag. 24, 351–389. doi: 10.1016/
S0149-2063(99)80065-8
Molleman, E., and van den Beukel, A. (2007). Worker flexibility and its perceived
contribution to performance: The moderating role of task characteristics.
Hum. Factors Man. 17, 117–135. doi: 10.1002/hfm.20069
Morgeson, F. P., and Humphrey, S. E. (2006). The Work Design Questionnaire
(WDQ): developing and validating a comprehensive measure for assessing
job design and the nature of work. J. Appl. Psychol. 91, 1321–1339. doi:
10.1037/0021-9010.91.6.1321
Morgeson, F. P., and Humphrey, S. E. (2008). “Job and team design: toward
a more integrative conceptualization of work design” in Research in personnel
and human resources management. ed. J. J. Martocchio, Vol. 27 (Emerald
Group Publishing Limited), 39–91.
Mumford, M. D. (2000). Managing creative people: strategies and tactics for
innovation. Hum. Resour. Manag. Rev. 10, 313–351. doi: 10.1016/
S1053-4822(99)00043-1
Organ, D. W., and Konovsky, M. (1989). Cognitive versus affective determinants
of organizational citizenship behavior. J. Appl. Psychol. 74, 157–164. doi:
10.1037/0021-9010.74.1.157
Orth, M., and Volmer, J. (2017). Daily within-person effects of job autonomy
and work engagement on innovative behaviour: The cross-level moderating
role of creative self-efficacy. Eur. J. Work Organ. Psychol. 26, 601–612. doi:
10.1080/1359432X.2017.1332042
Park, R., and Jang, S. J. (2015). Mediating role of perceived supervisor support
in the relationship between job autonomy and mental health: moderating
role of value–means fit. Int. J. Hum. Resour. Manag. 28, 703–723. doi:
10.1080/09585192.2015.1109536
14
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., and Podsakoff, N. P. (2003).
Common method biases in behavioral research: a critical review of the
literature and recommended remedies. J. Appl. Psychol. 88:879. doi:
10.1037/0021-9010.88.5.879
Podsakoff, P. M., MacKenzie, S. B., and Podsakoff, N. P. (2012). Sources of
method bias in social science research and recommendations on how to
control it. Annu. Rev. Psychol. 63, 539–569. doi: 10.1146/annurevpsych-120710-100452
Purc, E., and Laguna, M. (2017). Factorial structure and measurement invariance
of the Innovative Behavior Questionnaire. J. Creat. Behav. 1–7. doi: 10.1002/
jocb.215
Purc, E., Wałachowska, K., Żaliński, A., Mielniczuk, E., Patynowska, E., and
Łaguna, M. (2015). Innowacja w organizacji: Sposoby ujmowania i przegląd
uwarunkowań. Zag. Naukozn. 4, 425–445.
Ramamoorthy, N., Flood, P. C., Slattery, T., and Sardessai, R. (2005). Determinants
of innovative work behaviour: development and test of an integrated model.
Creat. Innov. Manag. 14, 142–150. doi: 10.1111/j.1467-8691.2005.00334.x
Razmus, W., and Laguna, M. (2018). Dimensions of entrepreneurial success:
a multilevel study on stakeholders of micro-enterprises. Front. Psychol. 9:791.
doi: 10.3389/fpsyg.2018.00791
Razmus, W., and Mielniczuk, E. (2018). Błąd wspólnej metody w badaniach
kwestionariuszowych. Pol. Forum Psychol. 23, 277–290. doi: 10.14656/
PFP20180204
Retowski, S., and Podsiadły, M. J. (2016). Gdy nasza praca pasuje do naszych
wartości. Ocena zgodności wartości własnych i organizacji a wypalenie
zawodowe. Psychol. Społecz. 11, 56–68. doi: 10.7366/1896180020163605
Rice, G. (2006). Individual values, organizational context, and self-perceptions
of employee creativity: evidence from Egyptian organizations. J. Bus. Res.
59, 233–241. doi: 10.1016/j.jbusres.2005.08.001
Roccas, S., Sagiv, L., and Navon, M. (2017). “Methodological issues in studying
personal values” in Values and behavior: Taking a cross-cultural perspective.
eds. S. Roccas, and L. Sagiv (Berlin: Springer), 15–50.
Rokeach, M. (1973). The nature of human values. (New York: Free Press).
Ros, M., Schwartz, S. H., and Surkiss, S. (1999). Basic individual values, work
values, and the meaning of work. Appl. Psychol. 48, 49–71. doi: 10.1111/
j.1464-0597.1999.tb00048.x
Rosenbusch, N., Brinckmann, J., and Bausch, A. (2011). Is innovation always
beneficial? A meta-analysis of the relationship between innovation and
performance in SMEs. J. Bus. Ventur. 26, 441–457. doi: 10.1016/j.
jbusvent.2009.12.002
Ryan, R. M., and Deci, E. L. (2000). Self-determination theory and the facilitation
of intrinsic motivation, social development, and well-being. Am. Psychol.
55, 68–78. doi: 10.1037/0003-066X.55.1.68
Sagiv, L. (2002). Vocational interests and basic values. J. Career Assess. 10,
233–257. doi: 10.1177/1069072702010002007
Sagiv, L., and Roccas, S. (2017). “What personal values are and what they are
not: taking a cross-cultural perspective” in Values and behavior: Taking a
cross cultural perspective. eds. S. Roccas, and L. Sagiv (Berlin: Springer), 3–13.
Sagiv, L., and Schwartz, S. H. (2000). Value priorities and subjective well-being:
direct relations and congruity effects. Eur. J. Soc. Psychol. 30, 177–198. doi:
10.1002/(SICI)1099-0992(200003/04)30:2<177::AID-EJSP982>3.0.CO;2-Z
Sagiv, L., and Schwartz, S. H. (2004). Values, intelligence and client behavior
in career counseling: a field study. Eur. J Psychol. Educ.-EJPE 19, 237–254.
doi: 10.1007/BF03173222
Sagiv, L., Schwartz, S. H., and Arieli, S. (2011a). “Personal values, national culture
and organizations: insights applying the Schwartz value framework” in The
handbook of organizational culture and climate. Second edn. eds. N. N. Ashkanasy,
C. Wilderom, and M. F. Peterson. (Newbury Park, CA: SAGE), 515–537.
Sagiv, L., Sverdlik, N., and Schwarz, N. (2011b). To compete or to cooperate?
Values’ impact on perception and action in social dilemma games. Eur. J.
Soc. Psychol. 41, 64–77. doi: 10.1002/ejsp.729
Sarros, J. C., Tanewski, G. A., Winter, R. P., Santora, J. C., and Densten, I. L.
(2002). Work alienation and organizational leadership. Br. J. Manag. 13,
285–304. doi: 10.1111/1467-8551.00247
Schwartz, S. H. (1992). “Universals in the content and structure of values:
theoretical advances and empirical tests in 20 countries” in Advances in
experimental social psychology. ed. M. P. Zanna, Vol. 25 (San Diego, CA,
US: Academic Press), 1–65.
Frontiers in Psychology | www.frontiersin.org
Schwartz, S. H. (1994). Are there universal aspects in the structure and contents
of human values? J. Soc. Issues 50, 19–45. doi: 10.1111/j.1540-4560.1994.
tb01196.x
Schwartz, S. H. (2003a). A proposal for measuring value orientations across
nations. Questionnaire Development Report of ESS, 259–290.
Schwartz, S. H. (2003b). Computing scores for the 10 human values (European
Social Survey). (The Hebrew University of Jerusalem). Available at: http://
ess.nsd.uib.no/ess/doc/ess1_human_values_scale.pdf [Access: 9 April 2019].
Schwartz, S. H. (2006). Basic human values: theory, measurement, and applications.
Rev. Fr. Sociol. 47, 929–968. doi: 10.3917/rfs.474.0929
Schwartz, S. H. (2010). “Basic values: how they motivate and inhibit prosocial
behavior” in Prosocial motives, emotions, and behavior: The better angels of
our nature. eds. M. Mikulincer, P. R. Shaver, M. Mikulincer, and P. R. Shaver
(Washington, DC, US: American Psychological Association), 221–241.
Schwartz, S. H., and Bardi, A. (2001). Value hierarchies across cultures: taking
a similarities perspective. J. Cross-Cult. Psychol. 32, 268–290. doi:
10.1177/0022022101032003002
Scott, S. G., and Bruce, R. A. (1994). Determinants of innovative behavior: a
path model of individual innovation in the workplace. Acad. Manag. J. 37,
580–607. doi: 10.2307/256701
Shalley, C. E., Gilson, L. L., and Blum, T. C. (2009). Interactive effects of
growth need strength, work context, and job complexity on self-reported
creative performance. Acad. Manag. J. 52, 489–505. doi: 10.5465/
AMJ.2009.41330806
Slagter, F. (2009). HR practices as predictors for knowledge sharing and innovative
behaviour: a focus on age. Intern. J. Hum. Resour. Dev. Manag. 9, 223–249.
doi: 10.1504/IJHRDM.2009.023454
Smith, R. M., Sardeshmukh, S. R., and Combs, G. M. (2016). Understanding
gender, creativity, and entrepreneurial intentions. Educ. Train. 58, 263–282.
doi: 10.1108/ET-06-2015-0044
Sosik, J. J., Jung, D., and Dinger, S. L. (2009). Values in authentic action:
examining the roots and rewards of altruistic leadership. Group Org. Manag.
34, 395–431. doi: 10.1177/1059601108329212
Sousa, C. M. P., and Coelho, F. (2011). From personal values to creativity:
evidence from frontline service employees. Eur. J. Mark. 45, 1029–1050.
doi: 10.1108/03090561111137598
Sousa, C. M. P., and Coelho, F. (2013). Exploring the relationship between
individual values and the customer orientation of front-line employees.
J. Mark. Manag. 29, 1653–1679. doi: 10.1080/0267257X.2013.798674
Sousa, C. M. P., Coelho, F., and Guillamon-Saorin, E. (2012). Personal values,
autonomy, and self-efficacy: evidence from frontline service employees. Int.
J. Sel. Assess. 20, 159–170. doi: 10.1111/j.1468-2389.2012.00589.x
Taştan, D. D. S., and Davoudi, S. M. M. (2017). The relationship between
organisational climate and organisational innovativeness: testing the moderating
effect of individual values of power and achievement. Internat. J. Bus. Innov.
Res. 12, 465–483. doi: 10.1504/IJBIR.2017.10003335
Tims, M., and Bakker, A. B. (2010). Job crafting: towards a new model of individual
job redesign. SAJIP: S. Afr. J. Ind. Psychol. 36, 12–20. doi: 10.4102/sajip.v36i2.841
Tims, M., Bakker, A. B., and Derks, D. (2012). Development and validation
of the job crafting scale. J. Vocat. Behav. 80, 173–186. doi: 10.1016/j.
jvb.2011.05.009
Tims, M., Bakker, A. B., and Derks, D. (2013). The impact of job crafting on
job demands, job resources, and well-being. J. Occup. Health Psychol. 18,
230–240. doi: 10.1037/a0032141
Vecchione, M., Döring, A. K., Alessandri, G., Marsicano, G., and Bardi, A.
(2015). Reciprocal relations across time between basic values and valueexpressive behaviors: a longitudinal study among children. Soc. Dev. 25,
528–547. doi: 10.1111/sode.12152
Vecchione, M., Schwartz, S. H., Alessandri, G., Döring, A. K., Castellani, V.,
and Caprara, M. G. (2016). Stability and change of basic personal values
in early adulthood: an 8-year longitudinal study. J. Res. Pers. 63, 111–122.
doi: 10.1016/j.jrp.2016.06.002
Verhees, F. J. H. M., and Meulenberg, M. T. G. (2004). Market orientation,
innovativeness, product innovation, and performance in small firms. J. Small
Bus. Manag. 42, 134–154. doi: 10.1111/j.1540-627X.2004.00102.x
Weinberger, E., Wach, D., Stephan, U., and Wegge, J. (2018). Having a creative
day: understanding entrepreneurs’ daily idea generation through a recovery
lens. J. Bus. Ventur. 33, 1–19. doi: 10.1016/j.jbusvent.2017.09.001
15
April 2019 | Volume 10 | Article 865
Purc and Laguna
Values and Innovative Behavior of Employees
West, M. A. (2002). Sparkling fountains or stagnant ponds: an integrative
model of creativity and innovation implementation in work groups. Appl.
Psychol. Int. Rev. 51, 355–387. doi: 10.1111/1464-0597.00951
West, M. A., and Farr, J. L., (Eds.) (1992). “Innovation at work” in Innovation
and creativity at work: Psychological and organizational strategies. (Chichester,
England, New York: Wiley).
Woodman, R. W., Sawyer, J. E., and Griffin, R. W. (1993). Toward a theory
of organizational creativity. Acad. Manag. Rev. 18, 293–321. doi: 10.5465/
AMR.1993.3997517
Wrzesniewski, A., and Dutton, J. E. (2001). Crafting a job: revisioning employees
as active crafters of their work. Acad. Manag. Rev. 26, 179–201. doi: 10.5465/
AMR.2001.4378011
Yuan, F., and Woodman, R. W. (2010). Innovative behavior in the workplace:
the role of performance and image outcome expectations. Acad. Manag. J.
53, 323–342. doi: 10.5465/AMJ.2010.49388995
Frontiers in Psychology | www.frontiersin.org
Zacher, H., Robinson, A. J., and Rosing, K. (2016). Ambidextrous leadership
and employees’ self-reported innovative performance: the role of
exploration and exploitation behaviors. J. Creat. Behav. 50, 24–46. doi:
10.1002/jocb.66
Conflict of Interest Statement: The authors declare that the research was conducted
in the absence of any commercial or financial relationships that could be construed
as a potential conflict of interest.
Copyright © 2019 Purc and Laguna. This is an open-access article distributed
under the terms of the Creative Commons Attribution License (CC BY). The use,
distribution or reproduction in other forums is permitted, provided the original
author(s) and the copyright owner(s) are credited and that the original publication
in this journal is cited, in accordance with accepted academic practice. No use,
distribution or reproduction is permitted which does not comply with these terms.
16
April 2019 | Volume 10 | Article 865
PLOS ONE
RESEARCH ARTICLE
How personal values shape job seeker
preference: A policy capturing study
Carol L. Hicklenton ID1*, Donald W. Hine2, Aaron B. Driver3, Natasha M. Loi ID1
1 School of Psychology, University of New England, Armidale, Australia, 2 School of Psychology, Speech
and Hearing, University of Canterbury, Christchurch, New Zealand, 3 UNE Business School, Armidale,
Australia
* carol.hicklenton@gmail.com
a1111111111
a1111111111
a1111111111
a1111111111
a1111111111
OPEN ACCESS
Citation: Hicklenton CL, Hine DW, Driver AB, Loi
NM (2021) How personal values shape job seeker
preference: A policy capturing study. PLoS ONE
16(7): e0254646. https://doi.org/10.1371/journal.
pone.0254646
Editor: Iván Barreda-Tarrazona, Universitat Jaume
I, SPAIN
Received: January 18, 2021
Accepted: July 1, 2021
Published: July 29, 2021
Peer Review History: PLOS recognizes the
benefits of transparency in the peer review
process; therefore, we enable the publication of
all of the content of peer review and author
responses alongside final, published articles. The
editorial history of this article is available here:
https://doi.org/10.1371/journal.pone.0254646
Copyright: © 2021 Hicklenton et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Data Availability Statement: All work climate,
personal values, and organization attractiveness
files are available from the RUNE database
(accession number(s) 10.25952/5fffc354212c6).
Abstract
Does the “ideal” organization exist? Or do different workplace attributes attract different people? And if so, what attributes attract what types of employees? This study combines person-organization fit theory and a policy capturing methodology to determine (a) which
attributes are the strongest predictors of perceived organization attractiveness in a sample
of Australian job seekers, and (b) whether the magnitude of these predictive effects varies
as a function of job seekers’ personal values. The design of this study is a randomized
experiment of Australian job seekers who responded to an online survey invitation. Each of
the 400 respondents received a random subset of 8 of 64 possible descriptions of organizations. Each description presented an organization that scored either high or low on six attributes based on the Employer Attractiveness Scale: economic, development, interest,
social, application, and environmental value. Multi-level modelling revealed that all six attributes positively predicted job seekers’ ratings of organization attractiveness, with the three
strongest predictors being social, environmental, and application value. Moderation analyses revealed that participants with strong self-transcendent or weak self-enhancement values were most sensitive to the absence of social, environmental, and application value in
workplaces, down-rating organizations that scored low on these attributes. Our results demonstrate how job seekers’ personal values shape preferences for different types of workplaces. Organizations may be able to improve recruitment outcomes by matching working
conditions to the personal values of workers they hope to employ.
Introduction
Securing high-quality employees is critical to the success of business organizations. Successful
recruiting involves not only being judged as attractive by desirable job applicants, but also
being the employer-of-choice for applicants weighing several offers. But what exactly makes
organizations attractive to potential applicants? Industry leaders, such as Google and Apple,
can use name recognition and reputation to attract desirable applicants, but other less highprofile organizations must rely on alternative strategies. Research into the attractiveness of
organizational attributes varies substantially across studies. Some studies indicate that factors
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
1 / 15
PLOS ONE
Funding: The authors received no specific funding
for this work.
Competing interests: The authors have declared
that no competing interests exist.
How personal values shape job seeker preference
like pay and promotion potential are most important, whereas others highlight the prospect of
challenging and interesting work, opportunities for teamwork and positive social interactions
[1, 2]. Person-organization (PO) fit, operationalized in this study as the level of congruence
between values of organizations and their prospective employees, is a useful theoretical lens
for understanding these inconsistencies [3]. This study combines PO fit theory and a policy
capturing methodology to determine which organizational attributes are the strongest predictors of perceived organization attractiveness in a sample of Australian job seekers, and whether
the magnitude of these predictive effects varies as function of job seekers’ personal values.
Organizational attractiveness
Organizational attractiveness refers to the overall appeal of an organization to employees, prospective employees, and others who may choose to engage (or not engage) with it. Attractiveness can be conceptualized as an expectancy of “envisioned benefits” and/or as “an attitude or
expressed general positive affect”, reflecting the general desirability of initiating or maintaining
a relationship with a particular organization [4–6].
To date, two meta-analyses have summarized much of the research on workplace attributes
and organization attractiveness [1, 2]. The first review of 71 studies, conducted by Chapman
et al., found that work environment and organization image (reputation) were much stronger
predictors of perceived organization attractiveness (r = .60 and .48, respectively) than job characteristics such as pay (r = .27) and promotion opportunity (r = .27) [1]. A subsequent review
of 232 studies by Uggerslev et al. also found organization image to be a stronger predictor of
perceived organization attractiveness (r = .48) than pay (r = .23) and promotion opportunity
(r = .35) [2]. Interestingly, work environment, the strongest predictor in the first meta-analysis,
was more modest in the second (r = .30) [2].
Both meta-analyses reported statistically significant Q coefficients for most predictors,
reflecting heterogeneity in effect sizes across studies. That is, the effects of specific workplace
attributes on perceived organization attractiveness varied significantly across studies; different
studies often identified different workplace attributes as the primary drivers of participants’
perceptions of organization attractiveness. Moderation analyses conducted in both reviews
examined whether average effect sizes for a given attribute varied as a function of sample characteristics such as gender and nationality, and examined measurement approaches for assessing organization attractiveness or organization attributes. For example, Chapman et al. found
that women placed more weight on job characteristics such as location and pay than did men,
and job applicants were likely to weigh justice perceptions more strongly than non-applicants
[1].
Heterogeneous effects have also been identified within, as opposed to across, studies. Alnıaçık et al. compared the mean attractiveness scores for 25 organization attributes across two
nationalities and reported significant cross-national differences for 24 of the 25 attributes [7].
An above-average basic salary was the only attribute for which there was no significant difference in attractiveness rating by nationality.
Many studies investigating the associations between workplace attributes and job seekers’
perceptions of organization attractiveness have employed ad hoc strategies, focusing on one or
a few individual attributes making it difficult for business organizations to use research findings for guiding their recruitment strategies. In an attempt to develop a more systematic and
comprehensive framework for assessing organization attributes that predict attraction, Berthon et al. developed the Employer Attractiveness Scale (EAS) [4]. Benefits of the EAS include
a structure derived from both interviews and a factor analysis, with item descriptions that
encompass a broad range of work values. The work values in the EAS are categorized from the
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
2 / 15
PLOS ONE
How personal values shape job seeker preference
perspective of potential job applicants, and align with psychological processes that might
explain perceptions of attractiveness. The 25 items in the EAS assess five dimensions: (1) economic value (basic salary, overall compensation, job security and promotion opportunities);
(2) development value (supporting employees’ personal and career development); (3) interest
value (supporting novel work practices and forward thinking, and valuing and making use of
employees’ creativity in the production of high quality and innovative products and services);
(4) social value (providing a positive and pleasant social environment for employees); and
(5) application value (being humanitarian and customer-oriented, and providing opportunities for employees to apply their knowledge, teach others, and experience acceptance and
belonging).
One important limitation of the EAS is that its application value dimension does not
include alternative types of corporate social responsibility (CSR), such as a commitment to sustainability and positive environmental outcomes. Corporate environmental responsibility is
sometimes regarded as a sub-type of CSR [8, 9]. In an influential review, Orlitzky et al. suggested that researchers should focus on specific sub-dimensions of CSR, and several studies
have found that corporate environmental responsibility is an important predictor of organization attractiveness [5, 8, 10–12]. Given these findings, in the current study we employ an
expanded EAS framework which includes both application value (reflecting CSR) and environmental value (reflecting corporate environmental responsibility).
Person-organization fit and perceptions of attractiveness
PO fit provides a useful conceptual framework for investigating personal values and perceptions of organization attractiveness, and for understanding why certain workplace attributes
are strong predictors of perceived organizational attractiveness in some studies but not others
[3]. PO fit is broadly defined as the compatibility between individuals and organizations [3].
Compatibility is conceptualized as complementary fit and supplementary fit. Complementary
fit occurs when a “weakness or need of the environment is offset by the strength of the individual or vice versa” [13]. Supplementary fit refers to situations where the person and the organization possess similar characteristics, such as when work values promoted by recruiting
organizations match personal values of potential job applicants [3]. The present study focuses
on supplementary fit between work values and personal values as they relate to job-seekers’
perceptions of organization attractiveness. PO fit can help explain that attraction is not based
on organization attributes per se but on how those attributes match employees’ or prospective
employees’ values, skills, and interests. To date, most of the research on PO fit has employed
perception-based measures where respondents are asked how well organizations fit their values and needs (e.g., “To what degree do you feel your values ‘match’ or fit this employer?”)
[14].
In the present study, we employed an alternative approach. Job seekers were asked to evaluate the attractiveness of a range of organizations that either provide weak or strong support for
a range of workplace outcomes (i.e., economic, development, interest, social, application, and
environmental outcomes). Using a policy capturing methodology, we evaluated whether job
seekers would focus on different features of organizations when generating their attractiveness
judgements. In this approach, increased PO fit is reflected in the degree to which an organization’s support for specific workplace outcomes matches job seekers’ personal values.
Personal values and perceived organization attractiveness
Schwartz’s value theory provides a useful conceptual model for understanding precisely why
job seekers with different values would prefer certain types of organizations more than others
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
3 / 15
PLOS ONE
How personal values shape job seeker preference
[15, 16]. According to Schwartz, personal values reflect desired goals that apply in a broad
range of situations, and implicitly or explicitly serve as guiding principles in people’s work and
personal lives [17]. Schwartz’s model is most commonly presented as a circumplex with nine
value dimensions: self-direction, universalism, benevolence, conformity, security, power,
achievement, hedonism, and stimulation [18]. The values captured by Schwartz’s circumplex
are often combined into sets of superordinate values [18]. Of relevance to this study are two
superordinate values: self-transcendence and self-enhancement. These are sometimes referred
to as “other” and “self” orientations [19].
Self-transcendent values “emphasize concern for the welfare and interests of others” and
encompass universalism and benevolence [18]. Universalist values derive from “the survival
needs of individuals and groups” which contrasts with the in-group focus of benevolence values. Benevolence values are defined by goals of “preserving and enhancing the welfare of those
with whom one is in frequent personal contact” [18]. Self-enhancement value types, on the
other hand, prioritize achievement and power. Achievement is defined as “competent performance that generates resources”. Power is defined as “control or dominance over people and
resources” [18].
Schwartz argues that people tend to endorse all personal values to some degree, but prioritize them differently [17]. The process of value prioritization makes certain organization attributes more personally relevant to job seekers than others. For example, someone who
prioritises self-enhancement might rate organizations that provide employees with generous
financial remuneration and opportunities for training advancement as more attractive than
organizations that do not. Alternatively, a job seeker who prioritises self-transcendence might
be more attracted to organizations with a strong commitment to CSR.
To date, several studies have assessed how personal values predict job seekers’ and current
employees’ perceptions of organization attractiveness. In an early study, Cable and Judge
hypothesized that certain types of pay systems would be generally preferred over others, and
that different types of job seekers would prefer different pay systems [20]. They found that job
seekers, overall, preferred organizations that offered high pay, flexible benefits, pay based on
individual performance, and fixed pay that was not contingent on the overall performance of
the organization. Consistent with the pay-person fit hypothesis, Cable and Judge also found
that job seekers with stronger materialist values were particularly attracted by high pay levels,
whereas those with stronger collectivist values were more opposed to pay systems that
rewarded individual as opposed to group performance [20].
More recently, Bridoux et al. conducted a study assessing the trade-offs stakeholders are
willing to make when deciding to associate with a firm (e.g., by purchasing a product from the
firm or seeking employment there) [19]. They found that stakeholders who scored higher on
self-transcendent values were more willing to trade-off personal material benefits to secure
improved conditions for suppliers from developing nations. In contrast, stakeholders with
stronger self-enhancement values were more attracted to firms that favoured their own ingroup. The current study extends previous research by examining the interplay between a
much broader range of workplace attributes and personal values on perceptions of organization attractiveness.
The current study
This study employed a policy capturing methodology to determine which workplace attributes
are the most important drivers of perceived attractiveness of organizations in a sample of Australian job seekers. Utilizing PO fit theory and multi-level modelling, it also evaluated whether
the magnitude of predictive effects varied as a function of job seekers’ values [3, 21]. Although
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
4 / 15
PLOS ONE
How personal values shape job seeker preference
previous studies have examined PO fit using a policy capturing methodology, the present
study is unique for a number of reasons [20, 22]. First, whereas, these PO fit policy capturing
studies relied on small university student samples, we employed a larger, more representative
sample of employed Australians who were planning to switch jobs within the next year. Second, whereas previous research focused on an ad hoc collection of one or a few predictors of
organization attractiveness, our study used a more comprehensive EAS-derived framework
that assessed six workplace dimensions: economic, development, interest, social, application,
and environmental value [4]. Our research is the first policy capturing study to investigate
whether job seekers with different personal values focus on different EAS dimensions when
constructing their judgements of organization attractiveness.
Based on research conducted using the EAS and meta-analyses by Chapman et al. and
Uggerslev et al., we predicted that organizations that support positive workplace outcomes
related to economic, development, interest, social, application, and environmental values
would be more attractive than organizations that do not support these values (Hypothesis 1)
[1, 2, 4]. Based on the effect sizes presented in the meta-analyses, we predicted that organization support for positive employee relations (social value) would be a particularly strong driver
of perceived attractiveness (Hypothesis 2). Challenging and interesting work (interest value),
personal and career development (development value), and pay and promotion opportunities
(economic value), would be reliable but weaker predictors of attractiveness than social value
(Hypothesis 3). Given previous findings that commitment to positive societal and environmental outcomes are stronger predictors of perceived organization attractiveness than promotion opportunities and pay, we predicted that the attractiveness of both application value
(Hypothesis 4) and environmental value (Hypothesis 5) would be stronger than economic
value, interest value, and development value [5, 12].
Based on PO fit theory and research, we predicted that job seekers’ self-transcendent and
self-enhancement values would moderate the predictive effects of workplace attributes on perceived attractiveness [23]. Specifically, organizations with strong commitment to supporting
social, application, and environmental outcomes would be perceived as more attractive by job
seekers with stronger self-transcendent values, relative to those with weaker self-transcendent
values (Hypothesis 6). Organizations committed to supporting positive economic, interest,
and development outcomes would be perceived as more attractive to job seekers with stronger
self-enhancement values relative to those with weaker self-enhancement values (Hypothesis 7).
Methods
Participants
A sample of 400 Australian adults, recruited from a Qualtrics™ (Provo, UT) online panel, participated in this study. At the time of recruitment, all participants indicated that they were
employed full-time but looking to change jobs within the next 12 months (assessed by a
screening question at the beginning of the survey). Close to two-thirds of participants were
women (62%), somewhat higher than the Australian workforce participation rate of 54.8%
[24]. Ages ranged from 19 to 75 years: 18–24 (6%), 25–34 (19.5%), 35–44 (30%), 45–54 (23%),
55–64 (16%), and 65 to 75 years (5.5%). The mean age of our sample of 42 years was slightly
higher than the national average of 38 years [24]. The sample included a broad range of education levels: less than Year 10 (<1%), Year 10 high school (4%), Year 12 high school (10%),
vocational education training certificate (15%), diploma or advanced diploma (13%), graduate
diploma or bachelor degree (43%), and postgraduate university degree (16%). University graduates were somewhat over-represented in our sample compared with the national average in
which 34% of the labour force has a degree or higher [25].
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
5 / 15
PLOS ONE
How personal values shape job seeker preference
Procedure
The survey was developed and delivered using the Qualtrics™ online survey platform. Prior to
data collection, the host institution’s Human Research Ethics Committee reviewed and
approved the project. The surveys were administered between 26 June and 13 July, 2017. A
screening question preceding the survey was used for participant consent. Participants indicated their agreement with written survey information by clicking a button. All participants
indicated being over 18 years of age and received payment under $3, administered by Qualtrics™, after completing the survey. The first part of the survey, immediately following the
screening question, assessed demographics and personal value orientations. Each participant
then read a random selection eight descriptions of organizations (selected from 64 in total),
which varied all possible combinations of six attributes relevant to job search (e.g., salary,
opportunities for career development, environmental policies, etc.). Effective policy capturing
design requires enough scenarios and cues for stable estimates, but not too many for respondents to become bored or fatigued [5]. For continuity, the six attributes were presented in the
same order in each organization description. After reading each description, participants completed five items assessing how attracted they were to the organization as a potential employer.
A central aim of the study was to assess whether certain types of work environments would be
perceived as more attractive, depending on participants’ values. Details about the experimental
stimuli and measures are presented below.
Manipulations and measures
Organization attributes. Based on the EAS, we created 64 unique descriptions of organizations that varied on six dichotomous attributes reflecting the degree to which the organization: (a) provided a good salary and promotion opportunities (economic value); (b) supported
employees’ personal and career development (development value); (c) possessed a reputation
for being exciting and innovative, encouraging creativity, and providing a challenging work
environment (interest value); (d) provided a positive and pleasant social environment for
employees (social value); (e) exhibited a strong commitment to customer focus, social and
racial equality, and operating in a manner that supports society (application value); and (f) had
strong pro-environmental policies and procedures, and encouraged environmentally sustainable practices (environmental value) [4].
The first five attributes were based on five facets of the EAS (4). Environmental value was a
new attribute developed for this study to assess the degree to which prospective job applicants
value organizations’ commitment to environmental sustainability when considering employment options. The organization descriptions reflected all possible combinations of the attributes, ensuring that the attributes were all orthogonal. A summary of the high and low
descriptors for each organizational attribute is presented in S1 Table.
Scenarios were created by combining the text presented in S1 Table in all possible combinations. No additional text was added, and all scenarios were constructed with text blocks in the
same order (i.e., economic value first, followed development, interest, social, application, and
environmental value).
Organization attractiveness. Following the presentation of each description, organization attractiveness was assessed as the extent to which participants felt attracted to the organization and intended to pursue employment with that organization. Using multi-level
modelling, participants’ reactions to each organization description were assessed as organization attraction and job pursuit intention with five items used by Aiman-Smith et al. [5, 21].
Representative items include, “This would be a good company to work for” and “I would like
to work for this company” for organization attraction, and “I would actively pursue obtaining
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
6 / 15
PLOS ONE
How personal values shape job seeker preference
a position with this company” and “I would accept a job offer from this company” for job pursuit. All responses were measured using a 7-point scale (1 = very unlikely, 7 = very likely). An
overall attractiveness scale was computed by taking the mean of all attraction and job-pursuit
items. Cronbach’s alpha for the scale was.98.
Self-transcendence and self-enhancement values. Participants’ personal values were
assessed by the self-transcendence (15 items) and self-enhancement (9 items) subscales of the
most recent version of the Portrait Values Questionnaire [16]. All items were comprised of
brief, gender-matched portraits portraying the motivation or aspirations of a fictitious person
(e.g., “It is important to her to care for nature” and “It is important to her to be wealthy”). Participants rated how similar they are to the person portrayed in the portrait on a 6-point scale
(1 = not like me at all, 6 = very much like me). Scores for self-transcendent and self-enhancement value orientations were computed by taking the mean of relevant items identified by
Schwartz [18]. Self-transcendence was computed by taking the mean scores across 15 items
assessing universalism and benevolence (α = .88), and self-enhancement was computed as the
mean of nine items assessing power and achievement (α = .87).
Results
Descriptive statistics
Means, standard deviations, and intercorrelations for organization attractiveness, selfenhancement, and self-transcendent values were examined using SPSS V25. On average, participants reported they were moderately attracted to organization attributes as presented in the
scenarios with the mean on the organization attractiveness measure falling above the midpoint
(4.22 on a 1 to 7 scale, SD = 1.78). The sample mean on the self-enhancement scale (3.38, SD =
.93) fell just below the midpoint on the 1 to 7-point scale, and the mean for self-transcendence
(4.77, SD = .63) fell above the midpoint. Self-enhancement and self-transcendent values were
weakly correlated (r = .09, p = .07).
Workplace attributes predicting job seekers’ perceptions of organization attractiveness. We used policy capturing and multilevel modelling to test our hypotheses. Policy capturing is a method used in applied psychology to investigate the associations between people’s
judgements and cues in the environment used to make those judgements [26]. The present
study explored which workplace attributes job seekers use when constructing judgements
about the attractiveness of organizations as potential employers. Multilevel modelling is a
highly flexible, regression-based statistical strategy for quantifying the magnitude of the relationship between environmental cues and judgements. It is specifically designed to analyse
data with hierarchical or nested structures. Given that each participant in the study provided
attractiveness judgements for eight hypothetical workplaces, participants’ judgements (level of
organization attraction and job pursuit intention) were nested within their reactions to each
organization description presented. In the Level 1 (within-person) analysis, regression equations were created for each participant using attractiveness as the outcome variable and the six
organization attributes from the scenarios as predictors (i.e., economic, development, interest,
workplace, application, and environmental values). This enabled the study to determine which
organization attributes predicted higher ratings of perceived attractiveness. Each of the organization attributes were coded 1 for the low condition and 2 for the high condition.
The Level 2 (between-person) analysis involved regressing the intercepts and beta coefficients from the Level 1 analysis on participants’ scores on self-enhancement and self-transcendent values. The Level 2 analysis assessed whether the relations between organization
attributes and attractiveness decisions varied systematically as a function of pre-existing personal values. In this study, all policy capturing analyses were conducted using HLM 6, using
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
7 / 15
PLOS ONE
How personal values shape job seeker preference
restricted maximum likelihood estimates and robust standard errors [21]. For all analyses, a
conservative α cut-off of p < .01 was adopted.
Sample size is an important consideration in multilevel studies. Maas and Hox [27] ran a
series of simulations in which they varied Level 1 and Level 2 sample sizes. They found that
only simulations with small Level 2 samples (consisting of 50 or fewer cases) produced biased
Level 2 standard errors. All other simulations, including those with Level 1 sample sizes as
small as five, produced accurate and unbiased regression coefficients, variance components,
and standard errors at both Level 1 and Level 2. Given the current study had 400 participants
at Level 2 and six ratings per respondent at Level 1, it exceeded Maas and Hox’s recommended
sample size guidelines [27].
Unconditional model. An initial unconditional model (i.e., no predictors at within-person or between-person levels) divided the total variance in organization attractiveness judgments into within- and between-person components. The intraclass correlation computed
from the unconditional model was.40, indicating that 40% of the variance in attractiveness was
attributable to individual differences (between-subjects variance). In other words, irrespective
of the specific workplace attributes presented in the organization descriptions, substantial variation in perceived attractiveness judgements across participants was evident. The remaining
60% of the variance in the data set reflected within-subjects variance across the six attributes,
indicating substantial variation within participants depending on the specific array of workplace attributes in each organization description. Given that the intraclass correlation was
large, multi-level analysis was an appropriate strategy [28].
Level 1 model: Which workplace attributes predict organization attractiveness? The
Level 1 analysis involved regressing organization attractiveness (the criterion variable) on six
dichotomous predictors reflecting low or high economic, development, interest, social, application, and environmental value. Average unstandardized coefficients and robust standard
errors for the intercept and each of the workplace attributes are presented in S2 Table.
The intercept value of 4.22 (SE = .05) indicates that, on average, participants’ organization
attractiveness judgements fell just above the midpoint on the 6-point scale. All six attributes
significantly predicted participants’ attractiveness judgements, with social, environmental, and
application value being the three strongest predictors. That is, providing positive social environments, strong environmental policies and practices, and a commitment to customer and
societal welfare were the strongest drivers of job seekers’ judgements of organization
attractiveness.
Level 2 model: Do personal values moderate the effects of workplace attributes on perceived attractiveness? A major aim of this study was to determine whether the degree to
which workplace attributes predict perceived organization attractiveness varies as a function
of job seekers’ personal values. As previously stated, the PO fit hypothesis suggests that organizations with work environments that match workers’ personal values should be perceived as
more attractive. To address this, we conducted a Level 2 analysis in which the strength of job
seekers’ self-enhancement and self-transcendent values were used to predict the intercepts and
beta coefficients associated with each of the organization attributes from the Level 1 analysis.
Significant Level 2 effects are referred to as cross-level interactions because they indicate the
magnitude of the relations between the Level 1 predictors (workplace attributes) and the criterion (perceived organization attractiveness). Significant cross-level indirect effects show the
extent that perceptions of attractiveness vary as a function of the value of Level 2 predictors
(personal values). To aid in the interpretation of cross-level interactions, all significant Level 2
effects were plotted using HLM’s graph module. A summary of the Level 2 analysis is presented in S3 Table.
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
8 / 15
PLOS ONE
How personal values shape job seeker preference
Plots of the significant interactions are presented in S1 Fig. Plots of the nonsignificant interactions are presented in S2 Fig.
Examination of the intercept analyses indicated that participants with higher self-enhancement values were significantly more attracted to the organizations described in the study than
participants with lower self-enhancement values. The opposite pattern was evident for selftranscendence. Participants with higher self-transcendence values were less attracted to the
organizations, overall, than participants with low self-transcendence values, although this
effect just failed to reach statistical significance (p = .01).
Examination of the cross-level interactions revealed significant effects between personal
values and workplace attributes related to social, application, and environmental value.
All the interactions involving self-transcendence followed the same general pattern (see S1
Fig, top row). Organizations with high social, application, and environmental value were perceived as being highly attractive by all participants (irrespective of whether they had weak or
strong self-transcendence values), with very little differentiation between the two groups.
However, participants with high self-transcendence values were more sensitive to the absence
of these three organizational attributes. Consistent with the PO fit hypothesis, high “self-transcenders”, relative to low “self-transcenders”, rated organizations that scored low on these
attributes as much less attractive.
Interactions involving self-enhancement took a slightly different form than for self-transcendence. Overall, organizations, regardless of whether they had high or low social, application, and environmental value, were perceived as more attractive by participants with strong
self-enhancement values than those with weak self-enhancement values. However, high selfenhancers were less sensitive to the absence of these three attributes than low self-enhancers.
That is, whereas high self-enhancers perceived organizations with low social, application, and
environmental value to be only somewhat less attractive compared to organizations that scored
high on these attributes, low self-enhancers perceived organizations with low social and application value as significantly less attractive. Low self-enhancers also perceived organizations
with low environmental value as less attractive, although this interaction effect failed to reach
statistical significance (p = .06).
Discussion
This study investigated which workplace attributes most strongly predict perceptions of organization attractiveness in a sample of Australian job seekers, and whether the magnitude of
these predictive effects vary as a function of job seekers’ personal values. We found that workplaces with attributes reflecting higher levels of economic, development, interest, social, application, and environmental value were perceived as more attractive than workplaces lacking
these attributes. We also found that the strength of the predictive effects for social, application,
and environmental value varied as a function of job seekers’ personal values. This finding is
broadly consistent with PO fit theory, which suggests that matches between workplace attributes and job seekers’ personal values should produce higher ratings of perceived organization
attractiveness [3]. These findings are explored in more detail in the sections that follow, along
with comments regarding the limitations of the study and recommendations for future
research.
Which workplace attributes are the strongest predictors of organization
attractiveness?
When job seekers decide to apply or not apply for a job, they often do so based on how well
potential workplaces stack up on key dimensions related to remuneration, CSR, intellectual
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
9 / 15
PLOS ONE
How personal values shape job seeker preference
stimulation, and so on. A central aim of this study was to determine which of six workplace
attributes, based on the EAS, are the primary drivers of job seekers’ perceptions of organization attractiveness [4]. Consistent with Hypothesis 1, organizations that support positive workplace outcomes related to economic, development, interest, social, application, and
environmental values were judged as more attractive than organizations that do not support
these values. Also as hypothesized, the strongest predictors of perceived attractiveness were
social value (providing positive social environments; Hypothesis 2), application value (commitment to customer and societal welfare; Hypothesis 4), and environmental value (strong
environmental policies and practices; Hypothesis 5), all of which were significantly stronger
predictors of perceived organization attractiveness than economic value (pay and promotions),
development value (supporting personal and career development), and interest value (provision of challenging and interesting work), providing support for Hypothesis 3. Of all the workplace attributes evaluated as part of this study, social value was by far the strongest predictor of
perceived organization attractiveness, with a coefficient more than twice the size of the next
highest predictor, environmental value. This result is consistent with Uggerslev et al.’s metaanalysis which also found positive employee relations and treatment to be the strongest predictor of attractiveness [2].
In the current study, environmental value (reflecting corporate environmental responsibility) was the next strongest predictor of attractiveness, followed by application value (reflecting
CSR). Beta coefficients for environmental and application value, while roughly half the size of
social value, were each about three times larger than the predictive effects for economic, development, and interest value. These findings support previous research highlighting the importance of having highly visible corporate social and environmental responsibility strategies [11,
12]. Not only are these strategies good for society and the environment, they are also attractive
to prospective employees and customers.
Our findings also support previous research which suggest that while good pay and promotion opportunities are significant predictors of perceived organization attractiveness, their
effect sizes are modest [1, 2]. This finding supports the meta-analysis by Uggerslev et al. in
which pay (r = .23), promotion (r = .35), and development (r = .49) each were statistically reliable, though not particularly strong predictors of attractiveness [2]. Our results also mirror the
overall pattern of findings in Uggerslev et al.’s meta-analysis, in which the effect size for training and development opportunities (development value) was stronger than for challenging
and stimulating work environments (interest value), which in turn was stronger than pay (economic value) [2]. When job seekers evaluate prospective employers, pay rates are important
but they are not the predominant driver of attractiveness judgements. Other factors such as
providing positive social environments and commitments to corporate social and environmental responsibility appear to be much more important.
Fit between workplace attributes and job seekers’ personal values
A major aim of the study was to determine whether the effects of specific workplace attributes on perceived organization attractiveness would vary as a function of job seekers’ personal values. Based on PO fit theory, we hypothesized that organizations would be perceived
as particularly attractive when workplace attributes matched job seekers’ personal values [3].
More specifically, we predicted organizations with strong commitment to supporting social,
application, and environmental outcomes would be perceived as more attractive by job
seekers with stronger self-transcendent values relative to those with weaker self-transcendent
values (Hypothesis 6). Organizations committed to supporting positive economic, development, and interest outcomes would be perceived as more attractive to job seekers with
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
10 / 15
PLOS ONE
How personal values shape job seeker preference
stronger self-enhancement values relative to those with weaker self-enhancement values
(Hypothesis 7).
Our results only partially supported these hypotheses. With respect to Hypothesis 6, we
found that organizations providing high social, application, and environmental value were
perceived to be quite highly attractive for all respondents regardless of their weak or strong
self-transcendent value orientation. However, differences emerged when workplace attributes
related to social, application, and environmental value were absent. Job seekers with stronger
self-transcendent values were more sensitive to the absence of these attributes, judging organizations without these attributes as much less attractive than organizations that had them. This
suggests that when it comes to PO fit, the absence of key attributes that job seekers value may
be a more important determinant of decisions not to pursue a specific job than the presence of
workplace attributes they do not value. For example, job seekers who score low on self-transcendence would still find attractive a workplace that fosters strong positive social ties and supports corporate social and environmental responsibility even if they do not highly value these
attributes. However, a job seeker who values these same workplace attributes would find their
absence to be off-putting and potentially intolerable.
Our findings on PO misfit support previous research. For example, the study on pay preferences by Cable and Judge found that among all the interactions, the strongest interaction,
reflecting PO misfit, was for collectivism and individual pay (r = -.37) [20]. This negative relationship was much stronger than the next closest interaction, which was a positive interaction
for risk aversion and fixed pay (r = .27) reflecting PO fit.
In terms of Hypothesis 7, we found no evidence to support our prediction that job seekers
with stronger self-enhancement values, relative to those with weaker self-enhancement values,
would perceive organizations committed to strong economic, development, and interest values
to be more attractive. No significant cross-over interactions between self-enhancement values
and these three workplace attributes were present, indicating that organizations that provided
high economic, development, and interest value (relative to those that did not) were perceived
as more attractive to all respondents regardless of their value orientations. However, as noted
earlier, it is important to acknowledge these effects were modest in magnitude.
Although not included in our a priori hypotheses, we did find significant cross-over interactions between self-enhancement values and workplace attributes related to positive social
environments and corporate social and environmental responsibility (i.e., social, application,
and environmental value, in EAS terminology). These interactions indicated that organizations with high or low social, application, and environmental attributes were perceived as
more attractive by participants with stronger self-enhancement values than those with weaker
self-enhancement values. However, low self-enhancers were more sensitive than high selfenhancers to the absence of social, environmental, and application value, rating organizations
that scored low on social and application value as being significantly less attractive and low
environmental value narrowly missing significance (p >.01). Our results support Bridoux et al.
who found that individuals with a high other orientation (i.e., self-transcendent values) were
more likely to want to associate with an organization that displayed high CSR [19].
Practical implications
The current study provides general guidance to businesses about how to increase the attractiveness of their public profile and brand. Many organizations already have such initiatives in
place. However, for the most part, they mainly target potential consumers or investors; initiatives aimed at potential employees are less common. Our results indicate that highlighting corporate social and environmental responsibility, and supportive collegial working
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
11 / 15
PLOS ONE
How personal values shape job seeker preference
environments, may also be an important tool for recruiting participants. For example, a multinational manufacturer of boots, shoes, and clothing, claims an “unwavering commitment to
environmental and social responsibility” and pays its employees to volunteer on projects for
“underserved communities” such as Urban-Greening-Los-Angeles [29–31]. On its website, the
business promotes the multi-million-dollar initiative directly to consumers. Our results indicate that programs like this are attractive to job seekers, regardless of their self-transcendence
or self-enhancement values, and are worthy of promotion as part of a recruitment strategy. In
an article on employer branding, Ambler and Barrow argue that businesses are missing an
important opportunity by focusing narrowly on consumers and investors, and by neglecting
to build brand loyalty in the eyes of prospective and current employees [32].
Organizations can also make better use of new online tools, such as the CSRHub, to benchmark their progress on CSR and use this comparative information to attract high quality staff
[33]. Currently, 18,958 companies from 143 countries have signed up to the CSRHub, indicating that this is a priority for many organizations. The program is voluntary, so the organizations are likely leaders in CSR implementation. Evaluation of the ‘employees’ category has a
top-down focus by assessing, for example, “robust delivery (EEO-1) programs and training”.
Likewise, the subcategory ‘compensation and benefits’ also indicates a management-centric
perspective by evaluating “the company’s capacity to increase its workforce loyalty and productivity through rewarding, fair, and equal compensation and financial benefits” [33]. It
appears that this reporting targets investors; however, employees might also be targeted if the
reports were enhanced by an employee perspective.
Overall, the three key areas that organizations might emphasize when refining and marketing their brands are a positive social working environment, a commitment to positive environmental outcomes, and customer and societal well-being. Other research has identified a long
list of factors that predict attractiveness, but our study shows these three features to be particularly important [1, 2].
Limitations and future research
This study had several limitations that should be considered when interpreting our findings.
First, our study relies on self-reported data provided by job seekers recruited from a non-probability sample. Although we employed a large, diverse national sample, findings cannot presume to be generalizable to the broader Australian population or to other countries. To
evaluate the robustness of our findings, we recommend additional studies using a variety of
samples, including those from other countries and cultures, recruited in ways other than
through an online panel, and with more balanced gender distributions.
A second limitation is that our study focused on only six organization attributes, five
derived from the core dimensions identified by Berthon et al. in their work developing the
EAS, and one additional dimension related to corporate environmental responsibility [4]. The
EAS encompasses a broad range of attributes, from pay to positive social interactions. However, other dimensions such as work/life balance, and the organization’s image and familiarity
to the applicant, which have been shown to be significantly associated with perceived organization attractiveness, were not included in our study. Previous research has shown that recruiter
behaviours and characteristics of the recruitment processes significantly influence attraction
[1, 2]. Future research should systematically examine a broader range of organization attributes, including those described above, to determine how they interact with applicant values
to predict organization attraction.
Third, the six organization attributes investigated in this study were presented in the same
order across presentations, with the economic value attribute always presented first, and the
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
12 / 15
PLOS ONE
How personal values shape job seeker preference
environmental value attribute always presented last. This introduces the possibility of order
effects, potentially increasing the impact of attributes presented early (primacy effect) or late in
the scenarios (recency effect). To rule out order effects, we recommend future studies present
attributes in a random order.
Fourth, the magnitude of difference between the high-low variants of the organization attributes used in our scenarios were not exactly equal. For example, whereas the social value attribute varied from negative and unpleasant (low) to positive and pleasant (high), the economic
value attribute varied from average pay and conditions (low) to above average pay and conditions (high). Thus, the relative differences in the effect sizes for the Level 1 (organizational
attribute) predictors should be interpreted with caution. Despite this limitation, it is worth
noting that (1) all Level 1 predictors were statistically reliable predictors of job seekers’ organization attraction judgements, and (2) the primary purpose of the study relates not to the relative strength of the Level 1 predictors, but the extent to which the direction and magnitude of
these effects changed as a function of job seekers personal values. Nevertheless, future research
should attempt to ensure high and low variants remain more commensurate across attributes.
Fifth, our study focused on job applicants’ perceptions of organization attractiveness.
Although perceived attractiveness is an important determinant of whether applicants will actually choose specific jobs, it is neither a necessary nor a sufficient cause. A meta-analytic review
by Chapman et al. [1] found that organization attribute studies that used attractiveness as the
primary dependent variable typically produced effect sizes that were nearly twice as large as
studies that used job choice. Thus, further research is needed to determine whether the effects
found in the current study for attractiveness ratings can be replicated using a behavior-based
choice measure.
Finally, concerning individual difference factors, we focused on two types of personal values: self-transcendence and self-enhancement. Other personal characteristics may act as
potential moderators and should be investigated in subsequent research. For example, a recent
meta-analysis on individual-level differences and organization attraction found that applicant
ability, personality, and experience were more important predictors of attraction than race,
gender, and age [34]. A framework developed by Ambler and Barrow categorizes job and organization attributes based on functional, economic, and psychological benefits associated with
employment [32]. This framework facilitates the systematic study of personal characteristics
and psychological processes that might influence perceptions of organization attractiveness for
both current and future employees.
Conclusion
The study combined person-organization fit theory and a policy capturing methodology to
determine (a) which workplace attributes are the strongest predictors of perceived organization attractiveness in a sample of Australian job seekers, and (b) whether the magnitude of
these predictive effects varied as a function of job seekers’ personal values. The three strongest
drivers of perceived organization attractiveness were the provision of positive social environments, commitment to customer/societal well-being, and pro-environmental responsibility.
These drivers were significantly more impactful than pay rates, opportunities for personal and
career development, and stimulating/innovative work environments. We also found that personal values moderated the impact of workplace attributes and perceived attractiveness of
organizations. In particular, job seekers with strong self-transcendence values and weak selfenhancement values were most sensitive to the absence of social, environmental, and application value, down-rating organizations that scored low on these attributes. Overall, our findings
highlight the importance of understanding both workplace conditions and the values of job
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
13 / 15
PLOS ONE
How personal values shape job seeker preference
seekers in the recruitment process. Non-collegial workplaces that undervalue customer, societal, and environmental outcomes are less attractive to job seekers, and this effect is particularly
pronounced for those with who value “bigger than self” outcomes.
Supporting information
S1 Table. High and low descriptors for workplace attributes.
(DOCX)
S2 Table. Level 1 analysis: Workplace attributes predicting organization attractiveness.
(DOCX)
S3 Table. Level 2 analyses: Job seekers’ personal values predicting level 1 effects.
(DOCX)
S1 Fig. Cross-level interactions between personal values and workplace attributes predicting job-seekers’ perceptions of organizational attractiveness.
(TIF)
S2 Fig. Non-significant cross-level interactions between personal values and workplace
attributes predicting job-seekers’ perceptions of organizational attractiveness.
(TIF)
Author Contributions
Conceptualization: Carol L. Hicklenton, Donald W. Hine.
Data curation: Carol L. Hicklenton.
Formal analysis: Carol L. Hicklenton, Donald W. Hine.
Methodology: Donald W. Hine.
Supervision: Donald W. Hine.
Writing – original draft: Carol L. Hicklenton.
Writing – review & editing: Donald W. Hine, Aaron B. Driver, Natasha M. Loi.
References
1.
Chapman DS, Uggerslev KL, Carroll SA, Piasentin KA, Jones DA. Applicant attraction to organizations
and job choice: A meta-analytic review of the correlates of recruiting outcomes. J Appl Psychol. 2005;
90:928–944. PMID: 16162065
2.
Uggerslev KL, Fassina NE, Kraichy D. Recruiting through the stages: A meta-analytic test of predictors
of applicant attraction at different stages of the recruiting process. Pers Psychol. 2012; 65:597–660.
3.
Kristof AL. Person-organization fit: An integrative review of its conceptualizations, measurement, and
implications. Pers Psychol. 1996; 49:1–49.
4.
Berthon P, Ewing M, Hah LL. Captivating company: Dimensions of attractiveness in employer brandin.
Int J Advert. 2005; 24:151–172.
5.
Aiman-Smith L, Bauer TN, Cable DM. Are you attracted? Do you intend to pursue? A recruiting policycapturing study. J Bus Psychol. 2001; 16:219–237.
6.
Barber A. Recruiting employees: Individual and organizational perspectives. Thousand Oaks, CA:
Sage Publications; 1998.
7.
Alnıaçık E, Alnıaçık Ü, Erat S, Akçin K. Attracting talented employees to the company: Do we need different employer branding strategies in different cultures? Procedia Soc Behav Sci. 2014; 150:336–344.
8.
Backhaus KB, Stone BA, Heiner K. Exploring the relationship between corporate social performance
and employer attractiveness. Bus Soc. 2002; 41:292–318.
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
14 / 15
PLOS ONE
How personal values shape job seeker preference
9.
Turban DB, Greening DW. Corporate social performance and organizational attractiveness to prospective employees. Acad Manage J. 1997; 40:658–672.
10.
Orlitzky M, Siegel DS, Waldman DA. Strategic corporate social responsibility and environmental sustainability. Bus Soc. 2011; 50:6–27.
11.
Dögl C, Holtbrügge D. Corporate environmental responsibility, employer reputation and employee commitment: An empirical study in developed and emerging economies. Int J Hum Resour Manag. 2014;
25:1739–1762.
12.
Greening DW, Turban DB. Corporate social performance as a competitive advantage in attracting a
quality workforce. Bus Soc. 2000; 39:254–280.
13.
Muchinsky PM, Monahan CJ. What is person-environment congruence? Supplementary versus complementary models of fit. J Vocat Behav. 1987; 31:268–277.
14.
Gully SM, Phillips JM, Castellano WG, Han K, Kim A. A mediated moderation model of recruiting
socially and environmentally responsible job applicants. Pers Psychol. 2013; 66:935–973.
15.
Schwartz SH. The refined theory of basic values. In: Roccas S, Sagiv L, editors. Values and behavior:
Taking a cross cultural perspective. Cham, Switzerland: Springer International Publishing; 2017. pp.
51–72.
16.
Schwartz SH, Cieciuch J, Vecchione M, Davidov E, Fischer R, Beierlein C, et al. Refining the theory of
basic individual values. J Pers Soc Psychol. 2012; 103:663–688. PMID: 22823292
17.
Schwartz SH. Universals in the content and structure of values: Theoretical advances and empirical
tests in 20 countries. In: Zanna MP, editor. Advances in experimental social psychology. 25. New
York, NY: Academic Press; 1991. pp. 1–65.
18.
Schwartz SH. An overview of the Schwartz theory of basic values. Online Readings Psychol Cult. 2012;
2.
19.
Bridoux F, Stofberg N, Den Hartog D. Stakeholders’ responses to CSR tradeoffs: When other-orientation and trust trump material self-interest. Front Psychol. 2016; 6. https://doi.org/10.3389/fpsyg.2015.
01992 PMID: 26834657
20.
Cable DM, Judge TA. Pay preference and job search decisions: A person-organization fit perspective.
Pers Psychol. 1994; 47:317–348.
21.
Raudenbush SW, Bryk AS. Hierarchical linear models: Applications and data analysis methods. 2nd
ed. London: Sage; 2002.
22.
Judge TA, Bretz RD Jr. Effects of work values on job choice decisions. J Appl Psychol. 1992; 77:261–
271.
23.
Kristof-Brown AL, Zimmerman RD, Johnson EC. Consequences of individuals’ fit at work: A meta-analysis of person-job, person-organization, person-group, and person-supervisor fit. Pers Psychol. 2005;
58:281–342.
24.
Australian Parliament House. 2018 [cited April 8 2021]. Labour force statistics: A quick guide [Internet].
https://www.aph.gov.au/About_Parliament/Parliamentary_Departments/Parliamentary_Library/pubs/
rp/rp1718/Quick_Guides/LabourForce.
25.
Australian Bureau of Statistics. 2020 [cited April 8 2021]. Qualifications and work [Internet]. https://
www.abs.gov.au/statistics/people/education/qualifications-and-work/latest-release.
26.
Cooksey R. Judgment analysis: Theory, methods, and applications. Bingley, UK: Emerald Group Publishing Limited; 1996.
27.
Maas C, Hox JJ. Sufficient sample sizes for multilevel modeling. Methodology. 2005; 1:86–92.
28.
Garson GD. Multiple regression. Asheboro, NC: Statistical Associates Publishing; 2014.
29.
Timberland serves: 1 million hours reached. 2020a Dec 22 [cited 10/01/20]. https://www.timberland.
com/responsibility/stories/timberland-serves.html
30.
Timberland careers and employment. 2020b Dec 22 [cited 10/01/20]. https://www.timberland.com/
about-us/careers.html.
31.
DeAcetis J. Timberland’s unwavering commitment to environmental and social responsibility. 2019
[cited 10/01/20]. https://www.forbes.com/sites/josephdeacetis/2019/02/04/timberlands-unwaveringcommitment-to-environmental-and-social-responsibility/#4e24490c5706.
32.
Ambler T, Barrow S. The employer brand. J Brand Manag. 1996; 4:185–205.
33.
CSRHUB. Sustainability management tools. 2020 Dec 222 [cited 10/01/20]. https://www.csrhub.com/
csrhub.
34.
Swider BW, Zimmerman RD, Charlier SD, Pierotti AJ. Deep-level and surface-level individual differences and applicant attraction to organizations: A meta-analysis. J Vocat Behav. 2015; 88:73–83.
PLOS ONE | https://doi.org/10.1371/journal.pone.0254646 July 29, 2021
15 / 15
Does Employee Happiness Have an Impact on
Productivity?∗
Clément S. Bellet
Erasmus University Rotterdam
Jan-Emmanuel De Neve
University of Oxford
George Ward
Massachusetts Institute of Technology
February 22, 2023
Abstract
This paper provides evidence from a natural experiment on the relationship between
positive affect and productivity. We link highly detailed administrative data on the behaviors
and performance of all telesales workers at a large telecommunications company with survey
reports of employee happiness that we collected on a weekly basis. We use variation in
worker mood arising from visual exposure to weather—the interaction between call center
architecture and outdoor weather conditions—in order to provide a quasi-experimental test
of the effect of happiness on productivity. We find evidence of a positive impact on sales
performance, which is driven by changes in labor productivity – largely through workers
converting more calls into sales, and to a lesser extent by making more calls per hour and
adhering more closely to their schedule. We find no evidence in our setting of effects on
measures of high-frequency labor supply such as attendance and break-taking.
∗
We thank Alex Bryson, Ed Diener, Alex Edmans, Paul Frijters, Sergei Guriev, John Helliwell, Micah Kaats,
Caspar Kaiser, Erin Kelly, Tom Kochan, Armando Meier, Rob Metcalfe, Mike Norton, Paul Osterman, Alberto
Prati, Alexandra Roulet, Mark Stabile, Anna Stansbury, Andrew Stephen, John Van Reenen, Ashley Whillans,
and Nate Wilmers for helpful comments. We are grateful to the editors and three anonymous referees, whose
constructive feedback greatly improved the paper. We also thank seminar participants at Oxford, MIT, LSE,
Erasmus University Rotterdam, and Paris School of Economics for helpful discussions. We are grateful to British
Telecom for the opportunity to design and run this study and for providing access to their administrative data,
and to Butterfly AI (where De Neve is a research advisor) for their technical support in implementing the
employee survey. Corresponding author: George Ward, MIT Sloan, 100 Main Street, Cambridge MA. Email:
wardg@mit.edu.
Electronic copy available at: https://ssrn.com/abstract=3470734
1
Introduction
A large number of employers are increasingly claiming to care about how their employees feel at
work, and have begun to invest in management and organizational practices aimed at creating
and maintaining a happier workforce. There may be various reasons for this – such as an
increased ability to attract and retain high quality workers – but at least one motivation is
a belief that happier workers will be more productive. When surveyed, for example, around
79% of U.S. managers reported an expectation that unhappiness in their workforce is likely
to hurt productivity.1 While this recent focus on employee happiness may seem a relatively
new development, the relationship between happiness and productivity has in fact been the
keen focus of both researchers and practitioners for many decades (see, e.g., Fisher and Hanna,
1931; Hersey, 1932, for early examples). One reason for this long-running interest is that the
relationship has potentially key implications for how firms manage their employees and organize
work (Edmans, 2012; Wright and Cropanzano, 2000). However, isolating the causal effect of
happiness on productivity has remained an empirical challenge, particularly in field settings.
Indeed, despite multiple generations of research on the topic, the literature has been bedeviled
by inconsistent findings (Iaffaldano and Muchinsky, 1985; Judge et al., 2001; Tenney, Poole and
Diener, 2016), such that claims surrounding the organizational benefits of worker happiness
have frequently been met with skepticism (Wright and Cropanzano, 2000).
In this paper, we study the effects of employee positive affect on productivity. We use data
on the universe of telesales workers at British Telecom (BT), allowing us to observe objective,
granular information about the behaviors and performance of 1,793 workers at one of the United
Kingdom’s largest private employers. We link this administrative data to a survey instrument
designed to measure the week-to-week affect of employees using a well-established measure of
happiness. We use variation in exposure to visual weather conditions while at work, arising out
of the interaction between weather and architecture, in order to provide a quasi-experimental
test of the effect of happiness on sales performance.
We find that a one unit increase in happiness, on a standard 0-to-10 scale, leads to around 3
additional weekly sales, around a 12% increase over a base of 25. Using detailed data on worker
behaviors, we rule out any effect going through employees working more (e.g. by taking fewer
breaks or working overtime). Instead, we are able to study three potential productivity channels
behind the effect of happiness on sales performance. First, workers could be better at organizing
their time while happier at work and in doing so adhere more closely to their prescribed daily
workflow schedule. Second, they could work faster when happier – that is, answer a higher
number of calls per hour. Third, they could be more efficient at converting calls into sales when
in a better mood. Although we find evidence for all three potential channels, the magnitude
of the third channel is much stronger, such that the estimated effect on sales can be almost
entirely explained by workers converting more of their calls into sales during weeks when they
feel happier. We interpret this as suggesting that, at least in our context, much of the effect
of happiness on productivity can be explained by better moods augmenting the ability to solve
1
The survey included 1,073 managers from a wide range of sectors and organization sizes, but was not a
randomly drawn sample (see HBR Analytical Services, 2020, for a more extensive discussion of the survey and
the beliefs and attitudes of managers in relation to employee wellbeing).
1
Electronic copy available at: https://ssrn.com/abstract=3470734
more complex cognitive tasks, where social and emotional skills may also matter more. In line
with this, when breaking down the analysis by sales type, we find strong effects of happiness
on sales when the worker is selling bundles of products and, in particular, when re-contracting
– but negligible effects when doing more routine order taking.
Our identification strategy relies on four key features of the empirical setting. First, the
11 call centers are dispersed geographically across the whole of the United Kingdom, such
that there is significant variation, within week, in weather in the local vicinity of each of the
call centers. Second, workers take incoming calls that are allocated to them based on the
call-type and handler availability, but not based in any way on the location of the caller –
meaning that, in this two-sided market, workers based in a given location will take calls from
customers all over the country. Third, the call centers vary significantly in terms of their
architecture and, in particular, their window coverage – ranging from fully glass-covered tower
buildings all the way to warehouse-style buildings with almost no windows at all. Finally,
despite these major exterior differences, all are laid out internally in the same open-plan way,
such that any given worker within a call center has roughly equal visual exposure to the external
walls – be they fully windowed, solid, or anywhere in between. We hypothesize that only the
most psychologically-relevant features of weather—namely, the extent to which it is bright or
gloomy—will impact worker happiness. Such aspects are visual in nature, meaning that any
effect should be contingent on a worker’s observable exposure to them. We show that visibly
gloomy weather has a strong negative impact on our measure of worker mood, on average,
but that this effect is dependent on the window coverage of each call center – in other words,
workers’ exposure to it. We exploit this plausibly exogenous variation in happiness to provide
a quasi-experimental test of the effect of happiness on sales performance in a real-world field
setting.
We make three main contributions. First, we provide causal field evidence on the relationship
between happiness and productivity. In doing so, we build on an extensive literature that spans
many decades as well as several disciplines across the social and behavioral sciences. Despite
a long line of research, the literature has been plagued with inconsistencies (Tenney, Poole
and Diener, 2016). Although experimentally-induced positive affect has been shown to improve
performance on stylized productivity tasks in the lab (see, e.g., Erez and Isen, 2002; Oswald,
Proto and Sgroi, 2015), it remains unclear whether such effects translate to real-world, largescale organizational settings – which are typically very different along a number of different
dimensions.
Second, we make a methodological contribution in terms of how we identify mood effects in
the field. While affective states are increasingly seen as a potentially important factor in driving
economic behavior (Loewenstein, 2000), demonstrating this in natural settings has proven difficult. We join a growing literature that typically proceeds by estimating the effects of various
proxies for mood such as weather patterns on outcomes like stock returns, consumption, real
estate transactions, and voting (e.g. Agarwal et al., 2020; Edmans, Garcia and Norli, 2007; Hirshleifer and Shumway, 2003; Hu and Lee, 2020; Li et al., 2017; Meier, Schmid and Stutzer, 2019;
Saunders, 1993). We label this existing method the reduced-form approach to mood effects in
the field, and build on it in three ways. First, by studying participants in a two-sided market
2
Electronic copy available at: https://ssrn.com/abstract=3470734
who are located in different places, we are able to identify weather-induced worker mood effects
aside from overall shocks that may, for example, affect national demand or customer mood. Second, implicit to the reduced-form approach is an instrumental variables (IV) set up, whereby
weather i) has an impact on mood and ii) affects behavior solely through that mood mechanism.
However, whereas this is often assumed rather than fully estimated, we follow Guven (2012) in
collecting a measure of happiness and estimating both stages of the IV specification (see also
Coviello et al., 2020; Guven and Hoxha, 2015). This is particularly important since the prior
literature on the effects of weather on happiness suggests the relationship is not necessarily a
given, threatening the implied first stage of the IV equation (Feddersen, Metcalfe and Wooden,
2016; Frijters, Lalji and Pakrashi, 2020). Third, an ever-growing number of economic phenomena have been instrumented for using weather patterns, casting doubt on the validity of the
exclusion restriction (Gallen, 2020; Mellon, 2020). Our novel use of variation in architecture
coupled with a focus on only the visual and mood-relevant aspects of weather allows us to overcome many of the usual objections related to this assumption. We rely on detailed institutional
knowledge of our workplace setting, gleaned from a mixture of image coding, employee surveys,
semi-structured interviews with managers, and site visits. This mixed methods approach means
we can design an identification strategy in which differential visual access to outside weather
patterns allows us to “turn on and off” the treatment – and in doing so better isolate any causal
effect.
Given that firms are increasingly at least claiming to focus on the happiness of their employees, the third main contribution of our paper is to provide more fine-grained and potentially
useful evidence for managers on the source of the happiness-productivity relationship. A recent
survey of U.S. executives suggests, for example, that while a large proportion of U.S. firms say
they are considering investing in managerial practices designed to foster a happier workforce,
only a small number currently have any sort of strategy in place to move in this direction (HBR
Analytical Services, 2020).2 Since work is one of the most unhappy activities people do in their
day-to-day lives in countries like the USA and UK (Bryson and MacKerron, 2016; Krueger
et al., 2009), there is ample room for improvement that could unlock potential productivity
gains. In one sense, our empirical approach suggests the significance of a managerially important but often overlooked aspect of work life – space and the physical workplace environment.
But, even more importantly, a long line of research has found that a wide range of management
and organizational practices influence the happiness of workers – suggesting a large number of
potential levers for firms to pull.3 By probing mechanisms through which happiness may impact
productivity, we are able to discuss the types of tasks and jobs where happiness is most likely to
be an important factor in explaining productivity differentials. In particular, with the number
of jobs requiring workers to interact socially with customers increasing rapidly (Deming, 2017),
2
87% of executives agreed that workplace happiness can provide their firm with a competitive advantage, but
only a third of the organizations in the survey of executives noted above say their organization sees employee
wellbeing as a strategic priority. Not only this, fewer than 20% of these firms actually have any sort of strategy
in place to measure or improve the wellbeing of their workforce.
3
While evidence on the effectiveness of employee “wellness programs” is mixed (Gubler, Larkin and Pierce,
2018; Jones, Molitor and Reif, 2019), a growing literature demonstrates the more fundamental point that the
ways in which work is managed and organized by firms—as well as the cultures they create—has a significant
impact on employee wellbeing (Bloom et al., 2014; Clark, 2010; Gosnell, List and Metcalfe, 2020; Krekel, Ward
and De Neve, 2019; Moen et al., 2016).
3
Electronic copy available at: https://ssrn.com/abstract=3470734
our finding that much of the happiness effect may be traced to improved social and emotional
skills suggests that the importance of employee happiness in driving productivity growth is
likely to rise in the coming years.
2
Background & Theory
For over a century, the relationship between happiness and productivity has been the keen
focus of both researchers and practitioners. One reason for this long-running interest is that
the relationship has potentially key implications for how firms manage their workers and for the
place, more broadly, of human resource management in firms’ overall business strategy (Edmans,
2012; Wright and Cropanzano, 2000). Yet, despite a long line of research, the literature is
bedeviled by inconsistent findings – many of which may be traceable to i) the multiplicity of
ways that researchers approach—theoretically and empirically—the concepts of both happiness
and performance, as well as ii) a number of inherent empirical difficulties in estimating any
causal effect, particularly in natural field settings.
2.1
Happiness
Although the study of human happiness has a long history (see Diener et al., 1999), confusion
can arise insofar as the term “happiness” is sometimes used loosely as a catch-all term referring
to subjective wellbeing (SWB) – which has both affective and cognitive dimensions (Krueger
et al., 2009). Cognitive measures of SWB are evaluative in nature, refer to global judgements
people make about how things are going overall, and are typically assessed in the workplace
context using survey questions on job satisfaction. Affective SWB, on the other hand, refers to
people’s emotional or hedonic experience. Kahneman, Wakker and Sarin (1997) refer to this as
‘experienced utility,’ in the Benthamite tradition, and note that it can be measured either in
real time or via people’s recollections – for example, by asking how happy they feel or have felt
during a given day, week, or month.
One potential reason for the inconsistent nature of the literature on happiness and productivity is that researchers have approached the question often with differing notions of what
“happiness” means (Wright and Cropanzano, 2000). Whereas much of the early literature focused on measures of job satisfaction (e.g., Brayfield and Crockett, 1951; Fisher and Hanna,
1931; Lawler and Porter, 1967; Locke, 1969), a more recent body of work has generally turned
toward the study of affect in the workplace (see, e.g., Barsade and Gibson, 2007; Brief and
Weiss, 2002; Knight, Menges and Bruch, 2018). This distinction is particularly important as
the theoretical links between happiness and performance are, as we will discuss below, arguably
much stronger when thinking in terms of affect than satisfaction (Côté, 1999; Lucas and Diener,
2003).
In this paper, we focus on affective wellbeing – specifically, workers’ feelings of happiness as
they experience it week-to-week. We see this as a general measure of positive affect that can also
reasonably be referred to as “mood.” Within the broad category of affect or affective wellbeing,
there is a key distinction between moods and emotions (see, e.g. Frijda, 1986). Emotions
typically refer to a specific feeling that is a (relatively short-lived) reaction to a particular
4
Electronic copy available at: https://ssrn.com/abstract=3470734
(and usually known) stimulus. Moods, on the other hand, are less specific and are typically
less intense. They are not directed at a particular person, task, or situation, but are rather a
more diffuse general feeling. While it is often easy for people to trace the root of a particular
emotion, they are usually not aware of the source of a good or bad mood (Russell and Barrett,
1999). Given this, there is little reason to expect the effects of a weather-induced good or bad
mood to be any different from the effects of a mood state induced by other factors, ranging
from working arrangements to line manager behavior. This is important, since although we use
weather-induced mood shocks for identification, we are nevertheless able to say something more
broadly about managerial and policy implications.
In addition to being influenced by a range of management and organizational factors (Gosnell, List and Metcalfe, 2020; Krekel, Ward and De Neve, 2019), SWB is also influenced by
the weather, one of the most pervading background variables in human life. However, the literature suggests that the link is not straightforward (Feddersen, Metcalfe and Wooden, 2016;
Frijters, Lalji and Pakrashi, 2020), since the empirical relationship between weather and affect
can be unstable (Denissen et al., 2008). A key explanation for the instability of these findings
is that effects are contingent on the extent to which weather is visible. Keller et al. (2005)
find weather affects mood, for example, but only when people are experimentally assigned to
be outdoors. A related literature shows that the visual pleasantness of weather improves mood
and prosocial behavior in studies with outdoor settings (Cunningham, 1979), though this does
not replicate using time-series data on tipping in an indoor restaurant (Flynn and Greenberg,
2012).4 Overall, one of the key findings of this literature is that the visibility of weather is key
to any relationship with subsequent mood and behavior.5 Given this contingent relationship,
in order to convincingly use weather as a mood proxy or instrument, it is (a) useful to have
variation in weather that is visual in nature and (b) even more useful to have variation in visual
exposure to any given weather, in order to eliminate concerns related to the direct effect of
weather on non-mood related drivers of productivity.
2.2
Performance
In addition to confusion surrounding conceptual definitions and measurement of happiness, a
further potential explanation for the inconsistent state of the literature is that many different
definitions of the performance outcome have been studied. Here we study labor productivity
– that is, the residual variation in output that cannot be fully explained by observable inputs
(Syverson, 2011). Call centers provide a particularly good setting in which to study this, since
we not only observe detailed data on a large number of labor inputs, but workers in our setting
also largely do the same telesales job, which is to take incoming calls from new and existing
customers and sell them various products using the same phones and computer system.
4
Rind (1996) also studies an indoor setting – a casino hotel in Atlantic City – in which hotel rooms all have
dark, limo-tinted windows that make it look like it is cloudy outside regardless of the brightness of the weather.
Having a server inform customers of the weather outside, experimentally varying how bright it is reported to be,
the authors find that (a belief in) sunny skies increases tipping. That is, though this experiment does not vary
visual exposure to weather, it does vary a related concept, namely its salience.
5
This is in line with a large medical literature on seasonal affective disorder (SAD), which shows that experimental exposure to sunlight improves mood (e.g. Kripke, 1998), even among the non-depressed (e.g. Leppämäki,
Partonen and Lönnqvist, 2002).
5
Electronic copy available at: https://ssrn.com/abstract=3470734
A large number of existing studies rely on employee self-reports of productivity or subjective
managerial evaluations (e.g. Staw and Barsade, 1993; Zelenski, Murphy and Jenkins, 2008). In
the case of using self-reported performance, there are well-known empirical difficulties associated
with regressing one subjective report on another, and in the case of managerial reports there
is a strong possibility that performance will be subject to a ‘halo’ effect whereby the happier
employee is rated more highly by the managerial rater precisely because they are happier and
more agreeable, and not because of any real performance differences. We are able to use
administrative data on a clear and objectively measurable output that is unambiguously positive
for the firm: sales performance. Moreover, fine-grained objective data on worker behaviors also
allows us to investigate channels through which any effect of happiness may translate into sales.
Given the various ways in which workers’ mood may affect performance, having a clear
understanding of which performance indicator is being used in any specific context is especially
important. For instance, a task involving complex interactions with coworkers or customers
may involve different skills than a more autonomous and repetitive task. The most recent
field-experimental literature shows that management practices can have simultaneously positive
impacts on i) productivity as well as ii) employee happiness and satisfaction (Gosnell, List and
Metcalfe, 2020). From pay inequality (Breza, Kaur and Shamdasani, 2017; Cullen and PerezTruglia, 2019) to gift exchange (DellaVigna et al., 2020) and work autonomy (Bloom et al.,
2014), this line of research suggests employee wellbeing as one possible channel through which
workplace organization may feed through to productivity. However, it is unable to isolate the
happiness channel in a causal manner. As a result, little discussion has been paid to the types
of tasks or psychological channels through which improvements in worker wellbeing itself may
mediate the positive effects of managerial practices on productivity.
2.3
Happiness and Performance
Whereas much of the earlier work on happiness and workplace performance is based on crosssectional comparisons, more recent studies have been able to leverage within-worker variation
in longitudinal research designs that go some way to assuage concerns related to unobserved
heterogeneity between workers, and in doing so have demonstrated that prior affective states
predict subsequent performance (see, e.g. Koys, 2001; Miner and Glomb, 2010; Rothbard and
Wilk, 2011; Staw and Barsade, 1993; Staw, Sutton and Pelled, 1994).6 But although this
temporal ordering is consistent with a causal effect, it still may be the case that time varying
third factors could be driving both. To infer causality, Oswald, Proto and Sgroi (2015) rely on
a series of mood-inducement experiments in the lab,7 using as their outcome an incentivized,
math-based productivity task designed to be similar to something one might find in a real-world
work setting – and, ultimately, find a positive effect of happiness (see also Erez and Isen, 2002,
for similar findings using a non-incentivized task).
Yet, while this evidence using a stylized, piece-rate productivity task moves the literature
6
For a much fuller treatment of this large literature, which we cannot review exhaustively here, see Walsh,
Boehm and Lyubomirsky (2018) and the citations within.
7
The authors randomly assign subjects to watch comedy or neutral video clips in their main experiment, and
in a further test use a mood treatment involving fruit, chocolate, and bottled drinks. Finally, they also leverage
recent real-world shocks like bereavement and family illnesses, which have an impact on happiness.
6
Electronic copy available at: https://ssrn.com/abstract=3470734
forward, the extent to which these affect-induced productivity effects translate into real-world
employment settings remains an open question. Indeed, real-world jobs typically involve bundles
of tasks, decisions on how to focus time and energy between them, as well as a number of other
factors that make it difficult to generalize from a math task in the lab to a real job in the
field. The external validity of existing lab-evidence can therefore be built upon, particularly
for tasks involving social interactions with customers or coworkers (which are becoming ever
more common in modern economies (Deming, 2017)). In such cases, the positive effect of mood
on performance found in a constrained lab-environment may either be reduced (e.g. if happier
workers spend less time at work and more time socializing with co-workers) or magnified (e.g.
if happier workers are better able to deal with customers). It is therefore important to be
more specific about the exact mechanisms through which positive affect may lead to greater
performance (for extensive discussion of the theoretical mechanisms between happiness and
performance, see, Lucas and Diener, 2003; Tenney, Poole and Diener, 2016).
First, good mood may affect performance by augmenting cognitive skills, independently of
the social interactions in which workers might be involved. In particular, positive affect can
influence how we think and process information. The influential broaden-and-build framework
suggests that positive affect signals to people experiencing it that the environment is nonthreatening and that things are generally going well. As a result, positive mood states tend
to broaden people’s thought-action repertoires as well as allow them to build longer-lasting resources (Fredrickson, 2001). In line with this, laboratory evidence suggests that people induced
into positive mood states tend to think in ways that are more flexible (Isen and Daubman,
1984), creative (Isen, Daubman and Nowicki, 1987), integrative (Isen, Rosenzweig and Young,
1991), open to information (Estrada, Isen and Young, 1997), and efficient (Isen and Means,
1983). Relatedly, it has been shown that the thoughts of happier people are less likely to “wander” (Killingsworth and Gilbert, 2010), a mechanism that has been formalized into an economic
model in which happiness reduces the amount of time spent worrying about negative aspects of
people’s lives, and thus drives productivity (Oswald, Proto and Sgroi, 2015).
Second, a further potential channel for the happiness-performance link is that happier workers may be more motivated (Erez and Isen, 2002). People in a positive mood state may have
greater prior expectations about the task, for example, and since people experiencing positive
affect are more likely to expect to enjoy an upcoming task, they are likely to be more motivated
to initiate or engage with it. Moreover, happier people might attribute their positive mood
state to the task at hand, and in doing so make them feel that they are enjoying the task – and,
ultimately, make them want to complete it (Forgas, 1995).
Third, positive affect may also influence behavior and outcomes by improving people’s social
and emotional skills. Outward indicators of happiness such as laughter signal that a person is
friendly and open. People induced into positive mood states (in the lab) are more likely to
engage in social contact with others (Isen, 1970) and people in happier moods tend to be more
cooperative and less aggressive with others (Isen and Baron, 1991). The positive impact of
affect may hence be even stronger when the task involves interacting directly with customers or
coworkers. For instance, Carnevale and Isen (1986) show that positive affect improves bilateral
negotiation skills in bargaining tasks, with participants employing less contentious tactics and
7
Electronic copy available at: https://ssrn.com/abstract=3470734
also finding more integrative solutions. Related to this, the sociological literature on emotional
labor (see, e.g., Hochschild, 1983) has long argued that in tasks involving interactions with
customers, happier workers may be better at negotiating with angry customers, as it becomes
easier to manage their emotions.
Given the differences in these psychological mechanisms, the extent to which affective happiness is likely to lead to greater productivity in real-world jobs will depend on a number of
factors, including the type of tasks and the nature of the workplace in question. For example,
being more integrative in thought may be helpful to productivity in jobs where novel or more
complex solutions to specific problems are performance-boosting, but less so where performance
is best accomplished by following precise instructions or routines. However, to the extent that
positive affect boosts motivation, task persistence, and energy, we may still expect it to lead
to greater productivity regardless of the job being performed. Equally, since happiness leads to
greater social rewards it may be a particularly strong predictor of productivity in jobs where
employees frequently interact with others, where social contact is beneficial, and where cooperation or negotiation with others is required in order to be successful. But in jobs where
social contact is less integral to the successful carrying out of the job, or where there is little
supervision or structure, happiness may be less important – or may even reduce productivity
by providing a distraction.
3
Institutional Setting & Data
Administrative Firm Data. We use detailed individual-level administrative data from BT,
a large multinational telecommunications company based in the United Kingdom. We focus our
attention on sales workers, whose job it is to take incoming calls and sell BT products, at 11
call centers across the United Kingdom (see Figure 1 for a map). The vast majority of the work
(91% of time and 82% of tasks) carried out by the employees in the sample are incoming calls
from potential or existing customers, with the remainder consisting of outgoing calls (4% of
time and 12% of tasks) and “other” activities (which includes tasks such as dealing with letters,
online customer chats, and SMS messaging). Workers are paid a fixed hourly wage, with a
potential bonus if they meet their target.8 At the worker-day level we observe the number of
sales, the distribution of which can be seen in panel (a) of Figure 2. As is typically the case
with sales data, the distribution is both right-skewed and also contains some zero values. In
addition, we also observe a host of information about worker behaviors such as break-taking,
attendance, number of calls, average length of calls, and so on.
Affective Wellbeing Survey. We link this performance data at the worker-week level with
a survey we administered to capture positive affect. We use a succinct happiness question that
was designed following the OECD’s (2013) guidelines on the measurement of SWB. Employees
were asked “Overall, how happy did you feel this week? ” over a six-month period. This is an
affective question, and, following Kunin (1955) and decades of subsequent work in psychology,
8
This is neither an explicit piece-rate pay schedule nor is it a commission-based pay system. In each of these
instances, one might expect each individual sale to bring with it a psychological reaction. Rather, the pay system
is a much more slow-moving bonus scheme, in which the majority of pay is paid through a base salary.
8
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure 1: Spatial Distribution of Call Centers
Note: Map shows the location of the 11 call centers in the study, as well as the number of sales workers in each.
we offer five response categories as a Faces Scale that ranges from very sad to very happy
androgynous faces. The use of faces in this way is both intuitive to respondents, and is also
known to strongly pick up the affective component of wellbeing questions (Fisher, 2000). The
survey was sent by email every week on Thursday afternoon, and is shown in Figure 3. The
single-item survey question could be quickly answered within the email. Workers were assured
that their individual happiness responses were being collected externally for the sole purpose of
academic research, and would not be shared with management. Workers were also offered the
opportunity to opt-out of the study at any time, via a simple email click-through. The study
ran for 6 months – the first and final emails were sent on the 20th of July 2017 and the 18th of
January 2018, respectively.
Benjamin et al. (2021) note the importance of being explicit about what happiness researchers are measuring. It is not only important in terms of wellbeing notion – job satisfaction
versus affect in the workplace, for example – but also the time horizon.9 We are purposefully
specific in the question about the time frame, measuring affect during a week-long period and
thus allowing us to match up with contemporaneous weekly data on productivity. One concern
is that respondents may answer solely based on their current mood at the end of the week (or
the peak during it), given that recall of emotions can be biased (Thomas and Diener, 1990).
While affective recall is not always fully accurate, Kemp, Burt and Furneaux (2008) nevertheless show that subjects do respond to the time prompts in such questions: By surveying daily
9
For example, Finkelstein, Luttmer and Notowidigdo (2013) ask people about their happiness “during the
past week”, Allcott et al. (2020) variously measure people’s happiness “right now”, “over the last ten minutes”
and “over the past four weeks,” and Kahneman et al. (2004) utilize the Day Reconstruction Method to measure
people’s emotional experience during a particular episode of the previous day.
9
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure 2: Distribution of Happiness and Sales
(a) Sales
(b) Happiness
Note: Panels (a) and (b) show the overall distribution of sales and happiness. Each observation is a worker-week.
Figure 3: Happiness Survey Email
Notes: Screenshot of the mood survey, which was sent weekly over a six month period to all workers. Respondents
had to click a face within the email for their response to be registered. See text for more details.
mood over a week-long period and then subsequently asking about total weekly mood, they are
able to show that people are able to provide a good reconstruction of the affective states (for
further discussion of the validity and reliability of SWB measures, see Krueger and Stone, 2014;
Krueger and Schkade, 2008).10
The distribution of responses is shown in panel (b) of Figure 2. Happiness in our setting
is low, with the modal answer being the most unhappy. We use our happiness responses both
ordinally and cardinally, depending on specification. When using happiness as a continuous
measure—as is typically done in the SWB literature—we assign the five categorical happiness
states equally-spaced numerical values between 0 and 10 from least to most happy. This is
done in order to be more aligned in terms of effect size magnitudes with scales typically used
in similar survey measures, such as in household panel surveys widely used in the literature.
When doing so, the mean response is around 4, with a within-person standard deviation of 2.4
(see Table A1).
Sample construction and characteristics. We aggregate all of the administrative data to
the Monday-to-Friday working week. All 1,793 workers were invited to take part in the study
10
In Figure S7 we are able to provide an empirical test of the temporal nature of our happiness measure.
Using daily weather data (described in more detail below), we show that the mood measure taken on a Thursday
afternoon or Friday is meaningfully related to weather exposure not only on that same day, but a few days before
within that same week. But that the relationship strongly declines in the days after the mood report – lending
intuitive support to the weekly nature of the measure.
10
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure 4: Distribution of Visual Weather Index
(a) Raw Data
(b) Within-Week Variation
Note: Visual weather index is a weekly measure that counts the total number of daily instances of fog, rain,
and snow in the vicinity of each call center. Panel (a) shows the raw distribution, while panel (b) shows the
distribution of residuals from a regression of the index on week fixed effects (bin width=0.5).
and were sent weekly mood surveys. Of these employees, 1,438 (around 80%) participated by
answering at least one survey over the subsequent 6 months. Conditional on participating in
the study, workers responded to a mean of 10.3 waves (SD = 7.1). The weekly response rate
of workers who participated was on average around 37%, which rises to 50% if we focus only
on workers who work on Thursday or Friday. We drop any participants who responded to only
one survey wave, since we rely on within-worker variation over time. This leaves us with a final
sample of 1,157 employees. Summary statistics for this final sample are shown in Table A1.
4
Empirical Results
We are interested in whether positive affect has any causal impact on weekly performance at
work. We estimate equations of the following general form:
Sijt = βP Aijt + γXijt + νi + τt + εijt ,
(1)
where Sijt corresponds to the sales performance of worker i in call center j during week t,
and P Aijt is their positive affect during that same period. Worker fixed effects νi capture any
individual-specific characteristic that does not change over time, and τt is a time fixed effect
partialing out any shocks that may affect both mood and sales. Finally, we include a vector
of controls Xijt for two time-varying labor inputs – the (logged) total number of selling hours
and the fraction of time spent at work in the week on mandatory non-productive activities. We
adjust the error term to account for two-way clustering on individuals and location-week.11
4.1
Reduced Form Effect of Visual Exposure to Weather on Performance
We begin by following the existing literature on mood-in-the-field effects by estimating the
impact of weather on sales. That is, we first assume weather to be a suitable proxy for P Aijt
11
For an empirical example of a similar approach using panel data, see Acemoglu and Pischke (2003), who
cluster standard errors at the individual and at the region-time level. A week is defined in our case by the date
on which a worker answered our survey and location by the call center.
11
Electronic copy available at: https://ssrn.com/abstract=3470734
in the above equation. Given that sales is a right-skewed count variable including some zero
values, we use a Poisson quasi-maximum likelihood estimator. Using local weather station data
that we matched to the locations of the 11 call centers, we coded an index of how visually
gloomy the weather is. This “Visual Weather Index” corresponds to the total number of daily
incidences of fog, rain, and snow during the working week (see Appendix H for more details and
Figure 4 for the distribution).12
In column (1) of Table 1 Panel A, we show that the Visual Weather Index has a negative,
though imprecisely estimated, impact on sales. Going beyond this, we further isolate the mood
effect by using variation not only in weather but also in people’s visual exposure to it, making
use of two additional factors critical to our identification strategy. In our setting, while all
workstations are open-plan across buildings, the type of building varies significantly – all the
way from warehouse-style workplaces with almost no exposure to outdoor conditions to glass
tower buildings or large window buildings with full exposure to the outdoor weather. Coding the
proportion of external walls that is covered by glass windows using image processing software,
we confirm that there is large variation across call centers – with the window share ranging from
.03 to .59 (see Table A1).13 Figure 5 illustrates this variation in architecture with photos taken
from the outside and inside of Doncaster and Swansea call centers, two ends of the external
window coverage spectrum.
In column (2) of Panel A in Table 1, we interact the weather index with visual exposure
to it. We find that the negative effect on sales is much stronger in situations where weather
is visible. The effect of window share itself is not estimated since it is captured by the worker
fixed effects, but recall that it lies between 0 and 1. The coefficient on the main effect of the
weather index thus gives the effect of weather for buildings that have no windows. Here we find
no significant impact. The interaction with window share, on the other hand, suggests that the
effect is much larger in magnitude (i.e. more negative) for buildings that are fully windowed.
To further illustrate what these results mean in terms of magnitude, we re-estimate our
regression equation within equally-sized groups of call centers with below and above median
window share. As can be seen in Figure 6a, the point estimate on sales is close to zero in call
centers with very few windows, but is significantly negative in centers with many windows.14
12
This in theory has a range of 0 to 15, where 0 would mean a likely bright day with no rain, snow, or fog on any
day of the week at all and 15 would mean that all three happened on every single day of the week. Importantly
for our identification, the United Kingdom has sufficiently volatile weather so that there is significant variation
in weather conditions across call centers, even within the same week (Panel (b) of Figure 4).
13
For an objective measure of external window-coverage, we first collect all wall photos from each of the call
centers in the dataset using Google Street View. For each building, we then code the percentage of wall surface
that is covered by glass windows using the ImageJ software (see Appendix I for more details). We supplement
this data below with a worker-level survey asking about the number of windows and subjective experience of
natural light.
14
Here in the above median share group, every 1-point increase on the weather scale (which is coded such that
higher numbers mean gloomier weather and has a standard deviation of 1.36) lowers weekly sales by 1.5%. We
also look for potential asymmetries, testing whether sales are more or less sensitive to visual exposure to bright
or gloomy weather. Though both effects go in the expected opposite direction, we find no systematic evidence of
an asymmetrical effect in terms of magnitude (Figure S5).
12
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure 5: Photos of External Walls and Internal Offices
4.2
(a) Outside View (Swansea)
(b) Inside View (Swansea)
(c) Outside View (Doncaster)
(d) Inside View (Doncaster)
First Stage Impact of Exposure to Weather on Happiness
The finding of a significant interaction in the reduced form-equation between weather and visual
exposure to it lends credence to the idea that we are picking up a mood effect. However, without
observing mood itself, alternative explanations may still be possible. In column (1) of Panel B in
Table 1, we show there is, on average, a negative effect of gloominess on happiness. Column (2)
suggests that this effect is much stronger in buildings with high glass coverage and non-existent
in buildings without windows. Another way to see the contingent relationship of weather on
happiness is shown in Figure 6b, which shows that the negative effect of gloomy weather on
happiness is concentrated within the buildings with high window coverage. This means at least
two things. First, by using exposure to visual weather, we are effectively relying on variation
in positive affect rather than any physical effect of weather. Second, we provide evidence that
the source of the mood shock is occurring while at work.15
Our identification comes here not from either windows or weather, but rather from the
interaction between the two. Note that the main effect of windows is not estimated, since it
is subsumed into the worker fixed effects. Indeed, we are not here principally interested in the
effect of windows, particularly since we do not have random variation in the architecture of these
buildings – which may, for example, be correlated with local economic conditions. Nevertheless,
we show that the presence of windows is—on average—positively correlated to workers’ mood
(Figure S1). More important for our identification is the within-worker variation in happiness
15
In this case, just like in the case of sales, we find no strong evidence of any asymmetrical effect on mood
between the effect of bright and gloomy weather (Figure S5).
13
Electronic copy available at: https://ssrn.com/abstract=3470734
Table 1: Impact of Exposure to Visual Weather on Sales and Happiness
Panel A: Reduced Form (DV: Sales)
Visual Weather Index
(1)
(2)
-0.0059
(0.0036)
0.0069
(0.0074)
-0.0666∗∗
(0.0333)
Weather × Proportion Windows
Visual Exposure to Weather (SDs)
Observations
Log Likelihood
Panel B: First Stage (DV: Happiness)
Visual Weather Index
12,282
-41,657
12,282
-41,643
-0.0617∗∗∗
(0.0207)
0.0139
(0.0377)
-0.3572∗∗∗
(0.1325)
Weather × Proportion Windows
12,282
0.534
Observations
12,282
-0.0258∗∗
(0.0104)
12,282
-41,646
12,282
0.534
-0.1950∗∗∗
(0.0442)
12,282
0.534
12,282
0.1331∗∗
(0.0532)
12,282
Visual Exposure to Weather (SDs)
Observations
R2
Panel C: CF Poisson-IV (DV: Sales)
Happiness
(3)
Notes: Panel A: Poisson-FE estimates reported with weekly sales as dependent variable. Panel B: OLSFE estimates reported with weekly happiness as dependent variable. Panel C: Two-stage control-function
Poisson-IV estimate. Standard errors in parentheses, adjusted for two-way clustering on individuals and
location-week in Panels A and B and calculated using the delta method in Panel C (see text for more details
and alternative SEs using a bootstrap procedure). Visual exposure to weather is a z-scored index resulting from
the interaction between the window share of a call center and the visual weather index that measures the total
number of daily instances of fog, rain, and snow. All regressions include individual and week fixed effects,
work schedule controls, and indicator variables for day of week of response to survey. ∗ p < 0.10, ∗∗ p < 0.05,
∗∗∗
p < 0.01.
across the buildings. Consistent with the intuition behind our empirical strategy, the mood of
workers (and their performance) in more heavily glass buildings is more variable than those who
work in call centers that block visual access to outside weather (see Figure S1).16
4.3
Putting it Together: IV Estimates
Control Function Poisson-IV Estimates. Column (3) of Table 1 shows the elements of
our main IV approach. For our main IV specifications, we prefer to use one single instrument –
since there are well-known issues with strength when using multiple instruments. We will thus
rely on the interaction term by itself in those models (such that this measure can be thought
of as a window-weighted or window-adjusted weather index). To aid interpretation when using
the interaction by itself, we z-score it – such that, in Panel A, the coefficient suggests that a one
16
The variance in sales across call centers is also generally higher in locations with windows (see Figure S2). The
overall relationship between windows and sales is negative, though less systematic than the positive relationship
between windows and happiness (see Figure S2).
14
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure 6: Impact of Weather on Sales and Happiness by Visual Exposure
(a) Sales (Poisson-FE)
(b) Happiness (OLS-FE)
Note: Coefficients are reported together with 95% confidence intervals. Panel (a): Poisson-FE estimates reported
with weekly sales as dependent variable. Panel (b): OLS-FE estimates reported with weekly happiness as dependent
variable. Visual weather is the total weekly number of daily instances of fog, rain, and snow in the vicinity of
each call center. Visual exposure is captured by window share. Each dot corresponds to a separate regression for
low visual exposure (below median window share) vs. high visual exposure (above median window share). Average
window share within each equally-sized group of workers is 9% and 32%, respectively. Full set of fixed effects and
controls are included, as in main specification.
standard deviation change in visual exposure to gloomy weather leads to a 2.5% shift in sales. To
be valid as an instrument, it must (at least) have a sufficiently strong impact on happiness in the
first stage. In the third column of Panel B, we find that our preferred instrument significantly
depresses mood (with an F-statistic of 19.44). A one standard deviation increase in visual
exposure to weather leads to around a 0.2 point decrease in happiness on the 0-10 scale.
The IV estimate logically arises from the ratio between the reduced form and first stage
estimates presented in column (3) of Table 1. Following Lin and Wooldridge (2019), in Panel
C we provide an initial IV estimate using a control function approach. Here we estimate the
first stage via OLS and then add the first-stage residuals as a control in the second-stage
Poisson regression.17 A one point increase in happiness (on a 0-10 scale)—which amounts to
around a 42% of a standard deviation increase in within-worker happiness—leads to a .13 log
point increase in weekly sales. We estimate an average marginal effect of 3.36 additional sales
(SE = 1.34; 95% CIs: 0.73, 5.99). In line with there being a strong downward bias in the noninstrumented model (see Appendix B for further discussion and evidence on the strength and
direction of this bias), the non-IV estimate is smaller than the quasi-experimental one. Indeed,
in the equivalent Poisson-FE regression of sales on happiness, with the same set of fixed effects
and controls, the coefficient on happiness is 0.0141 (SE = 0.0014; p < .001). We return in more
detail to this point in our extended discussion of magnitudes below.
17
We use the delta method to calculate the standard errors in this case, as suggested by Lin and Wooldridge
(2019). As an alternative, we can also bootstrap the whole two-stage procedure using a panel bootstrap (i.e.
that re-sample across individuals). When doing so, we estimate a smaller standard error (SE = .0483). Using a
2SLS estimator, as below, we are able to more straightforwardly allow for two-way clustering on individuals and
location-week.
15
Electronic copy available at: https://ssrn.com/abstract=3470734
Table 2: 2SLS Estimates of the Effect of Happiness on Sales Performance
Weekly Data
Happiness
16
Electronic copy available at: https://ssrn.com/abstract=3470734
Observations
Individual + Time FEs
Work Schedule
Additional Controls:
Temperature
Visual Weather Index
Detailed Schedule
England × Week FEs
Alternative IVs:
Subjective Windows
Subjective Light
Weather2
asinh(Weather)
Dis-Aggregated Weather
Daily Sample:
Response Day Only
Daily Data
(1)
0.142∗∗∗
(0.047)
12,282
Yes
Yes
(2)
0.157∗∗∗
(0.053)
12,282
Yes
Yes
(3)
0.193∗∗
(0.087)
12,282
Yes
Yes
(4)
0.139∗∗∗
(0.044)
12,282
Yes
Yes
(5)
0.122∗∗∗
(0.039)
12,282
Yes
Yes
(6)
0.134∗∗∗
(0.049)
12,282
Yes
Yes
(7)
0.124∗∗∗
(0.047)
12,282
Yes
Yes
(8)
0.106∗∗∗
(0.039)
12,282
Yes
Yes
(9)
0.167∗∗∗
(0.054)
12,282
Yes
Yes
(10)
0.122∗∗∗
(0.042)
12,282
Yes
Yes
(11)
0.176∗∗
(0.075)
43,883
Yes
Yes
(12)
0.168∗
(0.099)
11,545
Yes
Yes
No
No
No
No
Yes
No
No
No
No
Yes
No
No
No
No
Yes
No
No
No
No
Yes
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
No
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
Yes
—
—
—
—
—
Yes
—
—
—
—
—
Yes
—
—
—
—
—
Yes
—
—
—
—
—
Yes
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
—
No
Yes
Notes: 2SLS estimates reported, where asinh(sales-per-hour) is the dependent variable. Robust standard errors in parentheses, adjusted for two-way clustering on individuals
and location-week. All regressions include individual and time fixed effects, work schedule controls, and indicator variables for day of week of response to survey. Columns
(1) to (10) use weekly data on sales and visual exposure to weekly weather. Columns (11)-(12) use daily data on sales and visual exposure to daily weather. Visual
exposure to weather is a z-scored index resulting from the interaction between the window share of a call center and the visual weather index that measures the total number
of daily instances of fog, rain, and snow. Time fixed effects are study week in columns (1) to (10) and calendar date in columns (11) and (12). Column (11) assumes
that responses to the happiness question applies equally to each of the weekdays. Column (12) only uses observations from the day of response to the happiness survey.
∗
p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
2SLS Estimates. While the Poisson approach is attractive with a count outcome variable like
sales, there are nevertheless a number of benefits to using a linear two-stage least squares (2SLS)
estimator, which is more tractable and whose properties are well-understood in the literature.
Given that sales is right-skewed and contains zeros, we use as our main outcome in this case the
inverse-hyperbolic sine (asinh) of sales-per-hour – a transformation that allows us to estimate
equations that are roughly log-linear, while preserving the zeros and general interpretability of
our estimates. We thus estimate a 2SLS equation of the following form:
asinh(Sijt ) = βP Aijt + γXijt + νi + τt + εijt .
(2)
This equation includes the same set of fixed effects and time-varying controls as above
and adjusts the error term for two-way clustering on individual and location-week. Here we
use a direct survey measure of positive affect rather than a proxy, but in order to deal with
endogeneity, P Aijt is instrumented for using Zijt , where:
Zjt = W eatherjt × P ropW indowsj .
(3)
The first-stage equation is the same as above in column (2) of Panel B in Table 1, where
we showed that visual exposure to weather has a strong effect on worker happiness. Using this
variation, we show in column (1) of Table 2 a 2SLS estimate of 0.14 (95% CIs: .05, .23). This
is similar to the Poisson-IV estimate shown above using a control function approach.
4.4
Robustness
Window-Based Exposure. Given that our identification relies on workers’ differential windowinduced exposure to weather, one concern with the approach of relying on objectively-measured
external window coverage is that this may not translate to a worker’s visual exposure to outdoor conditions. For example, even if a building is externally fully glass-covered, some workers
inside may nevertheless have work-spaces with no windows. In our context this is unlikely to
be a problem, given the internal layout is similarly open-plan across buildings. This means the
inside is always one large space in which any given worker will have roughly equal visual access,
on average, to the walls – be they glass or solid. Moreover, as a fully open space, natural light
(if it is let in through windows) will spread through the space.
We combine our objective data on window coverage with two additional sources of data:
semi-structured interviews with managers and a short supplementary survey of workers (see
Appendix J for more details on this additional data collection). The survey enabled us to confirm, from the the perspective of workers themselves, what we (a) were told by management as
well as (b) observed on site visits: that despite significant exterior variation, all of the buildings
are open-plan (see Figure 5 for examples of this in both high- and low-window buildings). We
find from the survey that 95.6% (N=318) report working in an open office space as opposed to
a closed office space.
Moreover, the supplemental worker survey allowed us to ask workers directly about their
subjective experience of windows and light. Here we first ask workers to imagine sitting at their
typical workstation, and then ask “Do you see few or many windows? ” – with a 0 to 10 answer
17
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure 7: Subjective and Objective Measures of Visual Exposure to External Conditions
Notes: Objective window share is calculated from photos and using image processing software. Call-center-averages
displayed for responses to worker-level survey questions, each on a 0 to 10 scales, with the following wordings.
Subjective windows: “Imagine sitting at your typical workstation. Do you see few or many windows? Use the
slider below. Imagine a 10 being a completely glass office and 0 being a room with no windows at all.” Subjective
light: “While at work, how much natural light do you have access to from your workstation? Use the slider below.
Imagine a 10 being like seating outside while working and 0 being an office with no access to natural light at all.”
scale where 0 is labelled as “no windows at all ” and 10 “fully glass building.” As a further test to
this, we also ask how much natural light they have access to from their workstation, on a scale
where 0 is “no natural light at all ” and 10 is “like sitting outside.” As can be seen in Figure 7, we
find that workers’ subjective impression of windows and natural light is very highly correlated
with our objective measure of external window coverage (r = 0.83 and r = 0.91, respectively).
Using these subjective measures instead of the objective measure in order to construct our main
instrument, we also show that this does not affect our main 2SLS estimates (see columns (6)-(7)
of Table 2).
Product Demand Effects. A further concern in relation to the exclusion restriction is that
weather may have an effect on customer demand (either directly or by, indirectly, affecting
customers’ mood). This would be a threat to the exclusion restriction. However, in this twosided market, we have call center workers in fixed locations, and customers calling in from
all over the country. As we noted in the Introduction, one of the four key factors in our
identification strategy is that our call centers are sufficiently well dispersed across a country
that has variable weather across space, even within a given week. For a map of the spatial
distribution of these call centers, see Figure 1, which shows this dispersion across three nations
of the United Kingdom. We are also able to show in panel (b) of Figure 4 that, conditional on
18
Electronic copy available at: https://ssrn.com/abstract=3470734
the time fixed effects, there is variation in the visual nature of the weather across the locales.18
The inclusion of time fixed effects ensures that our key piece of identifying variation is exposure to weather shocks across call centers but within week. We rely on variation in weather
across call centers within any given week, rather than on movements in national weather conditions from week-to-week. Given that call centers do not field calls based on originating location,19 local weather in the vicinity of the focal call center should be independent, on average,
of customer demand.20
Although we cannot observe the origin of calls directly—our data is at the worker-day level
rather than the call level—we provide direct evidence that local demand pressure at a particular
call center measured by the average daily number of incoming calls per worker and the average
duration of a call is not affected by daily weather that is local to that particular call center
(Table S6).21 Moreover, if it were the case that calls were only routed within each of the four
nations of the UK, such that all calls coming from English customers were only routed towards
workstations located within England, then the addition of England-week fixed effects should
significantly affect our point estimate. We find in column (5) of Table 2, however, that this is
not the case.
Additional Controls. Adverse weather could physically be affecting sales performance through
changes in temperature or pollution. Temperature has been shown, for example, to affect student learning and academic test scores (e.g. Park et al., 2020) as well as investment decisions
(Huang, Xu and Yu, 2020).22 We show in column (2) of Table 2 that, when controlling for local
temperatures, all of our main findings are robust. The temperature variable itself does not enter
into the equation in a statistically significant way. Relatedly, air pollution can have a direct
impact upon worker productivity (e.g. Chang et al., 2016, 2019; Graff Zivin and Neidell, 2012).
Although we are not able to measure air pollution directly, pollution correlates with temperature, and there is little reason to suspect that glass-clad buildings would be more susceptible to
air pollution effects than warehouse-style ones.
18
Although weather also varies within a day across locations, the (normalized) distribution of the weather
index within a day is narrower than within a week (Figure S8). Measuring employee mood on a weekly basis is
hence also consistent with the spatial variability of weather being higher within weeks than within days.
19
The company have since our study introduced a new system (in Spring 2019) that does allow for geographical
allocation; however, no such technological capability was in place at the time of our study (July 2017 - January
2018).
20
Using data on customer satisfaction aggregated at the location-week level, we confirm that a small (negative)
residual correlation between our weather index and customer satisfaction across workstations nationally (r=0.105) is entirely nullified after adding week fixed effect (r=0.001).
21
Local supply shocks could also affect productivity if, for instance, gloomy weather makes it harder for workers
to answer calls. However, this should affect all call centers regardless of the window coverage of the building.
These effects are more likely to be driven by snowfalls than by fog or rain, but we find the effects are not driven
solely by snowfall (Table S7).
22
Using an empirical strategy somewhat analogous to ours, Park et al. (2020) show null effects in schools
that have air conditioning (i.e. instead of turning visual weather on and off with windows, they turn heat on
and off with AC). Nevertheless, Heyes and Saberian (2019) presents evidence to suggest a mood effect (though
without measuring mood) using high temperature and decisions of immigration judges who are inside of climatecontrolled buildings. While they argue judges may ‘import’ the mood effect of outdoor temperature when they
move indoors, Spamann (2022) finds no evidence of temperature on judge decision-making when using a larger
sample of years and when looking at all criminal sentencing decisions by US federal district judges. In terms of
studying mood effects, we prefer to focus clearly on visual aspects of weather coupled with observable variation
in exposure to be more sure of the mood mechanism taking place.
19
Electronic copy available at: https://ssrn.com/abstract=3470734
In addition to controlling for temperature, in column (3) of Table 2 we control for the main
effect of the visual weather index, while using the interaction of weather and windows as our
instrument. This analysis ensures our identification comes solely from the interaction, and when
doing so we find consistent results, though a slightly higher point estimate. As was suggested
by the reduced form and first stage evidence shown above in column (2) of Table 1, the main
effect of weather is not statistically different from zero in this case.
While we favor a parsimonious specification, our main 2SLS estimate also remains largely
unchanged if we include a much more exhaustive set of controls capturing the detailed daily
work schedule of workers and additional labor supply controls (see column (4) of Table 2).23
Sickness. Adverse weather conditions may cause sickness among workers, and impair their
ability to work effectively if they attend work while ill. Looking directly in the data, the local
weather turns out to be unrelated to the local share of workers under sick leave in any given
day or week (Table S8). We also consider the possibility that such a relationship may occur
with some lag. Weather conditions a day (or a week) before remains unrelated to the frequency
of sick leaves a day (or week) after. Most importantly, however, any sickness argument would
apply whether or not the call center had many windows. Given the relationships shown in
Figure 6, it seems clear that the variation our instrument picks up on is related to psychological
rather than physical health.
Sorting Effects. It is assumed throughout the paper that no other factors correlated with the
share of windows, but unrelated to visual exposure itself may explain heterogeneous sensitivity
to weather. The issue could arise if certain types of workers happen to be more negatively
affected than others by adverse weather conditions (e.g. older or sicker people), and if those
same workers tend to be systematically working in call centers with more windows. Table S9
shows balance across call centers with few or many windows (below vs. above median window
share) in terms of either baseline worker characteristics or the weather index. Of course, one
should only be worried about sorting effects if there exists important sources of heterogeneity
in worker sensitivity to weather in the first place, other than through visual salience. We
investigate this possibility directly, looking at whether weather (non-adjusted for exposure)
affects workers’ mood differently across observable worker characteristics. We look at basic
demographics (gender, age and workers’ tenure), the total number of weekly sales, and how
frequently the worker takes sick leave. We find no evidence of heterogeneity across any of these
dimensions (Table S10).24
23
This includes a full set of 35 indicator variables capturing the detailed daily work schedule of workers. For
each day of the week, we control for whether workers started (ended) their shift in the morning (7:00-12:00),
afternoon (12:00-17:00), or evening (17:00-24:00), or whether they did not work at all that day. We also add to
this list more detailed working supply controls, namely i) the total amount of hours spent on breaks, ii) the total
amount of hours spent working overtime, and iii) whether the worker was reported sick during the week.
24
It may still be that workers in call-centers with more windows would have a tendency to report a better (or
worse) mood when they can visualize good (or bad) weather. This effect would be consistent with the effect of
visual weather on mood being stronger in call centers with more windows. However, it is not a threat to our
identification strategy as long as (i) this effect is not biased towards reporting only good or bad mood and (ii)
reporting behavior is correlated to an actual shift in mood, which is further confirmed by the fact visual exposure
to weather does have clear behavioral effects on performance.
20
Electronic copy available at: https://ssrn.com/abstract=3470734
Functional Form of Happiness. One concern that we noted above in relation to our happiness survey is that answers are given on an ordinal scale. We make the assumption that this can
be cardinalized into a continuous measure of happiness. We provide a test for the reasonableness of this assumption by replacing continuous happiness with indicator variables for different
levels of happiness in a Poisson regression of sales on happiness (including the same set of fixed
effects and controls as in our main IV specification). Figure S3 reports the coefficients from
this exercise. We interpret the pattern of coefficients as suggestive evidence for being able to
use the happiness survey in a continuous manner in our instrumented analyses, meaning that
we “only” require one valid instrument rather than one for each categorical response.
First Stage Functional Form. In Figure S4, we show a graphical representation of our first
stage regression of happiness on visual exposure to weather. The relationship looks roughly
linear. But in order to explore and account for possible non-linearities more fully, we test
alternative functional forms for our instrumental variable. In Table 2 we use the squared value
of visual exposure to weather as well as the inverse hyperbolic sine transformation. We find in
columns (8) and (9) of Table 2 that the resultant second-stage coefficients are consistent with
our main results.25 Related to this, concerns related to weak instruments should be mitigated
by the reduced form evidence provided in this paper. Indeed, reduced form estimates remains
unbiased estimates, even if the instruments are weak (Angrist and Krueger, 2001).
Heterogeneous Responses. Instead of identifying an average treatment effect (ATE), a valid
instrument identifies a local average treatment effect (LATE) in the second stage (Angrist,
Imbens and Rubin, 1996) – that is, the effect driven by those whose mood is most sensitive
to visual exposure to weather.26 Assuming away the possibility of heterogeneous treatment
effects can be problematic when the causal effect of the endogenous variable is directly related
to the individual’s own choice (Angrist and Imbens, 1995). While this issue has been widely
discussed, for instance when estimating the returns to education (Angrist and Krueger, 1991), in
our case, mood movements are largely “external” to an individual: one does not have a direct
control over them. Heterogeneous treatment effects arising from employees’ selection on the
productivity gains of good mood are unlikely to occur in our context. Table S11 shows the first
stage of our IV strategy this time interacting visual exposure to weather with each of the six
main characteristics described earlier. We find no evidence of heterogeneity across any of these
dimensions.27 We also conduct sub-group analysis splitting between generally unhappy and
25
We also show a 2SLS regression in column (10) of Table 2 where we include three separate instruments,
one each for the incidence of the three weather phenomena that make up the index. Here we run into potential
problems of weak instruments, since the combined F-statistic is much lower in this case – as is typically the case
when using multiple instruments (see Table S7 for the first stage). However, results remain consistent overall.
26
As pointed by Angrist, Imbens and Rubin (1996), the LATE (or causal effect of weather-induced happiness
on sales) corresponds to the ratio of the impact of visual exposure to weather on sales (the reduced-form, which
may be referred to as an intent-to-treat effect) and the impact of visual exposure to weather on happiness (i.e.
the fraction of workers whose mood is sensitive to weather) – or alternatively it can be calculated using an IV
estimator. The LATE is of specific policy-relevance if the goal is to target those individuals whose affective state
is most likely to be affected by any policy change.
27
One reason for the higher salience of weather in buildings with more windows may result from workers paying
more attention to weather over time in those locations as they can more easily blame the bad weather for their
low productivity. Such learning effects should build up over time, so that workers with longer tenure should be
more sensitive to visual exposure to weather, which is not what we find (Table S11). We also found no evidence
21
Electronic copy available at: https://ssrn.com/abstract=3470734
happy workers as well as generally low and high productivity workers (below/above median in
each case). We find no statistical difference in the sensitivity of productivity to weather-induced
mood effects across those groups (Table S13).
Survey Non-Response. Using our final sample of workers, we do not observe a fully balanced
worker-week panel since we are restricted by non-response to the happiness survey instrument.
One concern here is that non-response to the survey is unlikely to occur randomly, and may
indeed relate to our main variables of interest in ways likely to bias our estimates. For example,
it could be that a worker does not respond in a given week because they are either too happy
or miserable to spend time reading the email. To explore this potential issue further, we
regress a dummy for having responded to the survey in a given week on a number of timevarying observables like sales, selling time, local gloomy weather (multiplied or not by window
share) and team average happiness (as well as a set of individual and week fixed effects).
Reassuringly, neither weekly sales performance nor team average happiness (minus the focal
worker) is significantly related to non-response within-individuals over time (see Table S1).
Non-response is, however, positively related to the number of hours worked during the week
and whether or not they work on Thursdays or Fridays, suggesting that workers are less likely
to respond during weeks in which they are scheduled to work less. Importantly, response is also
unaffected by local weather patterns as they vary week to week.28
Timing of Happiness Response. Respondents are explicitly asked to report their average
mood state over the course of the week. Here, we test whether the response to the happiness
question indeed captures respondents’ mood during the week in which the response is reported
(and not the week after or before). As a placebo test, we check whether weekly happiness
significantly relates to visual exposure to weather a week before or a week after the happiness
response week. We find that it is not the case (Table S14). We also find the same result
looking at reported happiness and weekly sales. Moreover, looking at those relationships within
the same week (with reported happiness applied equally to each day up to 3-4 days before vs.
after the response day) using daily weather and sales data around the response day, reported
happiness about “this week” is significantly and strongly related to visual exposure to weather
and sales on the response day and a few days before, but much less so (or not significantly) a
few days after (Figure S7).
Analysis using Daily Data. Although our happiness data is measured at the weekly level,
our productivity data is reported largely at the daily level. In table S15 we regress daily sales
on daily weather exposure at work, together with a full set of individual and date fixed effects,
plus our standard set of daily work schedule controls (equivalent to above). We find that daily
visual exposure to weather has a negative and significant effect on daily sales performance.
for seasonality in the effect of visual exposure to weather for both happiness and sales (see Table S12).
28
One potential approach to dealing with non-response to the survey is to impute any missing values as the
lowest or the highest category. However, given the suggestive evidence that response behavior is not systematically
related to individuals’ happiness, imputing low or high value is likely to simply add measurement error to the
reported happiness data. When imputing in this way, we find that it does not affect the reduced form effect of
visual exposure to weather on sales, but it does lower the first stage impact of visual exposure to weather on
happiness (Appendix Table S4).
22
Electronic copy available at: https://ssrn.com/abstract=3470734
We provide two further analyses, this time using the weekly happiness data combined
with the daily sales and performance data. First, we assume that responses to the happiness
question—which is asked on Thursday and refers specifically to “this week”—apply equally to
each of the weekdays (Figure S7 demonstrates this assumption is supported by the data itself).
We then estimate the 2SLS regression using a daily dataset, and include date (instead of week)
fixed effects. When doing so, in column (11) of Table 2 we find that our results are unchanged.
In column (12) we make the more restrictive assumption that the weekly happiness question
applies only to the day of response. Restricting only to the day of response, we again find
similar results. These effects are less precisely estimated, consistent with the lower variance in
weather within a given day across locations, relative to within a given week, as documented in
Figure S8.
5
Evidence on Channels
In Section 2.3 we discussed three broad ways in which happiness might be expected to affect work
performance: the impacts of positive affect on cognitive processing (in particular being more
efficient or integrative in thought), work motivation, and social or emotional skills. Although the
main focus of the paper is to provide evidence on the main effect of happiness on productivity
in a field setting, we move in this section to provide some suggestive evidence on the relative
importance of those various mechanisms, at least in our context.
5.1
Cognitive Mechanisms
Though we cannot measure cognition directly, an impact of positive affect on the ways in which
workers think could be reflected in three major labor productivity measures: adherence to daily
workflow schedule, speed, and call-to-sale conversion. First, adherence to workflow – where,
for example, positive affect may lead to greater flexibility in thought and a better ability to
multi-task as well as effectively plan and switch between tasks. In our setting, workers attend
and have their day’s workflow scheduled for them and displayed on their terminal screen (for
example, they may have the first hour scheduled as selling TV bundles, the second selling
internet connections, a 15 minute break, and then an hour selling something else). The firm
routinely records the extent to which employees adhere to this scheduled workflow. We code
our adherence outcome variable here as 1 if the firm’s target is met, zero otherwise.29 How
does workers’ mood affect this outcome? In Table 3 Panel A, we present reduced form evidence
using our measure of visual exposure to weather. In Panel B, we show the results from the
second stage of a 2SLS regression, in which happiness is instrumented for using visual exposure
to weather. We find that happier workers adhere more closely to the workflow that has been
set out for them (see column (1) in Table 3). In our setting, however, conditional on the
total number of hours spent at work (selling or doing other internally scheduled non-productive
activities), adherence happens to have little influence on sales (see Table S16). In other settings
29
The measure is continuous, out of 100. However, occasional deviance from this workflow may be beneficial
if the worker has to stay on a call to complete a sale, for example. As such, the firm sets a loose target of 91%
adherence each week, which is the cut-off we use.
23
Electronic copy available at: https://ssrn.com/abstract=3470734
Table 3: Happiness and Labor Productivity
Panel A: Reduced Form
Visual Exposure to Weather (SDs)
Adherence
(Met Target=1)
Calls Per Hour
(Log)
Conversion Rate
(Log)
(1)
(2)
(3)
(4)
-0.0155∗∗
(0.0068)
-0.0119∗∗∗
(0.0033)
-0.0564∗∗∗
(0.0143)
12,169
12,100
11,720
-0.0650∗∗∗
(0.0151)
0.0084
(0.0105)
-0.8782∗∗∗
(0.0703)
11,672
0.0822∗∗
(0.0382)
0.0632∗∗∗
(0.0227)
0.2832∗∗∗
(0.0965)
12,169
12,100
11,720
Adherence (Met Target=1)
Calls per hour (ln)
Observations
Panel B: 2SLS
Happiness (0-10)
Adherence (Met Target=1)
Calls per hour (ln)
Observations
0.3254∗∗∗
(0.1047)
-0.0628∗
(0.0347)
-0.5623∗∗∗
(0.1414)
11,672
Notes: 2SLS estimates reported, using visual exposure to weather as an IV for happiness. Visual exposure to
weather is a z-scored index resulting from the interaction between the window share of a call center and the
visual weather index that measures the total number of daily instances of fog, rain, and snow. Robust standard
errors in parentheses, adjusted for two-way clustering on individuals and location-week. All regressions include
individual and week fixed effects, and controls working hours, internal shrinkage, and day of response to
survey. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
with different types of work and where adherence may be more critical to performance, however,
this mechanism could well be more consequential.
Second, improved efficiency in information processing, brought about by higher positive
affect, should translate into an ability to work faster. We observe, on a daily basis, the total
number of minutes spent on incoming calls as well as the number of calls taken, and show in
column (2) of Table 3 that in happier weeks workers work faster. This “speed” measure is what
would typically be used as a labor productivity metric in the manufacturing industry. However,
in our setting, and in the service industry more generally, it is not clear that taking more,
shorter calls will be beneficial when the goal is selling.30 Table S16 suggests that calls-per-hour
is not a good predictor of productivity – and, if anything, it is associated with a reduction in the
number of weekly sales per worker. In settings where speed may be more crucial, this channel
could have more of an effect.
Relative to adherence or speed, a third productivity metric is arguably more clearly linked
to problem-solving: call-to-sale conversion. Column (3) shows that in happier weeks, workers
convert more of their calls to sales. Out of the three cognitive mechanisms, workers’ improved
ability to solve customers’ problems seems most likely to explain our main productivity effect.
Indeed, the point estimate for adherence and calls per hour are relatively small: Though a
30
This speed-quality trade-off is particularly salient in call center settings (Singh, 2000). Indeed, faster calls
may displease customers and make them less likely to buy if the operator is too blunt or quick with them.
Furthermore, sales calls are likely to be mechanically longer, due to the time it takes to complete an order, take
payment details, and so on.
24
Electronic copy available at: https://ssrn.com/abstract=3470734
1-point increase in happiness leads to a rise in the average number of calls per hour from 5
to 5.3 calls, speed is unable to explain much of an increase in sales. The dominance of the
conversion channel is more apparent in Column (4), where we control for adherence and the
number of calls per hour. It confirms that the average number of calls per hour is negatively,
not positively, correlated with the conversion rate.
We saw that an important higher-order mechanism explaining how positive affect may lead
to higher performance is through its impact on workers’ ability to find integrative solutions
to problems. In routine jobs or tasks where there is little space for integrative thinking, this
channel may be much smaller than in solving more complex tasks (or even go in the other
direction). Although we do not observe the amount of time spent (or number of calls) selling
different products, we are able to examine the effect of happiness on different types of sales.
When doing so, we find that, although all of our estimates are less precise, the magnitude is close
to zero for regular order-taking (see Figure 8a). This is consistent with the main mechanism
being call-to-sales conversion rather than working faster (or more efficiently), since line sales are
largely mechanical order-taking. More strongly positive effects are found for TV and cell-phone
contracts, which are also more technical and involve selling bundles with multiple different
options, as well as for re-contracting sales.
5.2
Motivational Mechanisms
Besides purely cognitive mechanisms, positive affect may also increase performance through
higher work motivation – in particular, as noted in Section 2.3, by making work more enjoyable,
happiness may incite workers to put more effort on the least enjoyable tasks and spend more
time at work generally (or take fewer breaks). Although we do not measure work motivation
directly, higher motivation is unlikely to be the main driver of the happiness-productivity effect
in our setting. First, happiness has no impact on simple order-taking, which is the most routine
and likely least fulfilling selling task. Since baseline motivation on those tasks is low, if higher
motivation were a major mechanism then those particular sales should be most reactive to
happiness, which is not what we find. Second, work motivation is arguably linked to the
amount of time spent at work. In addition to labor productivity, we can therefore investigate
the impact of positive mood on short-run labor supply decisions. If positive mood makes work
more enjoyable, we may also expect to find that workers would spend more time at work.
We first look at total number of selling hours, which we used as our main control of labor
inputs throughout the paper. In column (1) of Table 4, we find no robust evidence of any
happiness effects on the amount of time spent selling. We observe additional high-frequency
data on the allocation of time between work and leisure. First, we observe a percentage measure
of weekly attendance, which has a mean of around 93%. Here we code whether the employee
recorded perfect attendance to their scheduled hours during the week. Here too, we find no
robust evidence of any significant mood effects on attendance. This rules out the possibility that
happier workers would find work more enjoyable, and hence be motivated to attend work more
often. We also find negative (but non-significant) coefficients for over-time working. Finally, we
observe whether workers took any paid vacation during the week, and the number and length
of breaks taken by workers. Both coefficients are negative but non-significant. Taken together,
25
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure 8: Effects by Type of Sales and National Levels of Customer Satisfaction
Note: Coefficients and 95% confidence intervals are estimated using Poisson-IV. Happiness is instrumented using
visual exposure to weather. Visual exposure to weather is a z-scored index resulting from the interaction between
the window share of a call center and the visual weather index that measures the total number of daily instances
of fog, rain, and snow. The outcome in all cases is the number of sales. In Figure (a), separate regressions are
estimated according to the type of sale. In Figure (b), the sample is divided into weeks with above vs. below median
levels of national customer satisfaction. National customer satisfaction is the share of BT workers dealing with
satisfied customers (customer satisfaction > 7) each week, excluding the worker’s own workplace. All regressions
include individual and week fixed effects, work schedule controls, and day of response to survey.
we find very little evidence of any robust happiness effects on labor supply decisions. This is in
line with what would be expected in the context of a call center, where employees work alone
on independent tasks and have little autonomy or freedom to decide how much they work, once
they arrive and are sat at their terminal. We thus do not want to over-interpret this evidence as
strongly suggesting that happiness does not affect labor supply decisions (and the motivation
to work) in general. As we noted above in relation to the validity of our weather instrument,
the very limited labor supply flexibility in our call center field site effectively provides us with
an ideal setting in which to test for the pure productivity effects.
5.3
Social and Emotional Mechanisms
Finally, positive mood could also augment social and emotional skills, especially in a real-life
workplace where workers interact with customers and co-workers. Figure 8a shows that the
strongest positive effect of happiness is on re-contracting sales. In these situations, workers are
negotiating and, consistent with the experimental literature discussed in Section 2.3, may be
better able to find integrative solutions through persuasion – likely because of relying less on
26
Electronic copy available at: https://ssrn.com/abstract=3470734
Table 4: Happiness and High-Frequency Labor Supply
Panel A: Reduced Form
Visual Exposure to Weather (SDs)
Observations
Panel B: 2SLS
Happiness (0-10)
Observations
Sell Time
(ln)
Attendance
(100% =1)
Overtime
(Any = 1)
Paid Vacation
(Any = 1)
Break Time
(ln)
(1)
(2)
(3)
(4)
(5)
0.0185
(0.0127)
12,282
0.0052
(0.0103)
12,279
0.0066
(0.0041)
12,282
0.0011
(0.0083)
12,282
0.0104
(0.0067)
12,282
-0.0958
(0.0663)
12,282
-0.0270
(0.0542)
12,279
-0.0342
(0.0216)
12,282
-0.0055
(0.0432)
12,282
-0.0539
(0.0378)
12,282
Notes: 2SLS estimates reported, using visual exposure to weather as an IV for happiness. Visual exposure to
weather is a z-scored index resulting from the interaction between the window share of a call center and the
visual weather index that measures the total number of daily instances of fog, rain, and snow. Robust standard
errors in parentheses, adjusted for two-way clustering on individuals and location-week. All regressions include
include individual and week fixed effects and indicator variables for day of response to survey. ∗ p < 0.10,
∗∗
p < 0.05, ∗∗∗ p < 0.01.
contentious tactics.
In fact, the effect of positive affect on re-contracting likely involves both a cognitive (better
problem-solving) and a social (friendliness and negotiation) channel. Both factors could be
playing a role and we cannot separately identify each factor in this paper. However, we present
some suggestive evidence consistent with a more social channel. In a customer-facing setting,
this is an expected channel – indeed, the sociological literature on emotional labor (see, e.g.
Hochschild, 1983) has long argued that, in tasks involving interactions with customers, it becomes particularly costly for unhappy employees to leverage their social skills and manage their
emotions as they need to “fake” happiness.31 Consistent with those hypotheses, we find that
the happiness effect is stronger during weeks where workers are, on average, most likely to face
unsatisfied customers. Figure 8b replicates our main analysis but split by weeks with above versus below median levels of national customer satisfaction.32 In weeks where national customer
satisfaction is low, being in a good mood has a stronger positive effect on sales than during
weeks where customer satisfaction is high. Going beyond this, we also find that this effect only
manifests in the most complex tasks of TV/cell phone and re-contracting sales: in particular,
in weeks where the average customer is satisfied, the effect of happiness on those sales is null,
which suggests the type of skills driving the effects of positive affect in our setting are not simply
cognitive but also social (Figure S9). This effect may be due to being nicer, better at negotiation (e.g. via persuasion), or a mix of both. The dominance of persuasion in negotiation skills
would suggest an overall negative effect on customer satisfaction as customers would accept
solutions that may not be in their best interest. Using the weekly average customer satisfaction
response for each worker, we show in Table S17 that, within-workers over time, happiness has
31
Related to this work, the psychological broaden-and-build framework similarly suggests that positive affect
not only broadens people’s thought-action repertoires but also enables them to build resources, meaning that
happier people over time amass a greater stock of resources to deal with shocks (Fredrickson, 2001).
32
After each call, customers are asked by text or phone to report the extent to which they would recommend
BT to others, on a 0 to 10 scale. We use the national share of BT workers whose customers reported an average
satisfaction higher than 7 each week. To lower endogeneity concerns, we exclude the worker’s own workplace.
The sample is then split between weeks with a below vs. above median national share of workers dealing with
satisfied customers.
27
Electronic copy available at: https://ssrn.com/abstract=3470734
a negative (although very imprecisely estimated) relationship with customer satisfaction. We
are hesitant to over-interpret this result, however, given that the customer satisfaction data is
not only endogenous but also very noisy when used at the worker level because each employee
receives very few feedback ratings, on average, per week.33
Finally, as we noted in Section 2.3, happiness may here have an ambiguous theoretical
relationship with performance given that the more social mechanisms may in some contexts
lead to distraction or loafing (cf. Coviello et al., 2020). Indeed, higher sociability may incite
workers to spend less time working and more time socializing with their co-workers while at
work, which would predict negative happiness effects on productivity. In our particular setting,
however, where team work is absent and workers are monitored, we find no evidence suggesting
sociability may be detrimental to productivity. On the contrary, happier workers take calls
slightly faster and the effect of happiness on break taking is negative, effectively ruling out any
large-scale effect whereby happier workers take longer breaks to chat with their co-workers.
6
Discussion
6.1
Managerial Implications
We employ variation in visual exposure to weather level as an econometric device in order to
isolate the causal effect of happiness on productivity. Our study is thus best thought of as a
form of basic research, albeit in an applied setting. As such, we are not able to say definitively
whether windows, in and of themselves, are good or bad for firms. We show that workers are,
on average, happier in buildings with more windows; however, without plausibly exogenous
variation in window coverage or a setting where workers routinely switch between buildings, it
is difficult to make any strong claims. Nevertheless, our findings do demonstrate the importance
of an often-overlooked aspect of work, namely the physical environment – and the ways that it
is an important factor in mediating the effects of environmental factors on workers.
A natural question is whether or not the effect of weather-induced happiness on productivity
is a useful (i.e. policy- or managerially-relevant) parameter to estimate. One initial thing to
note here is that although the root of an emotion is typically easily traceable for people, the
source of moods is not. There is little reason to expect the effects of a weather-induced mood
to be any different from the effects of a mood state induced by other factors, many of which
are managerially relevant. Indeed, a great deal of research has shown workplace mood and
happiness can be influenced by a range of management practices and other organizationallyrelevant factors (Krekel, Ward and De Neve, 2019). Interestingly, this is a point that is already
well understood by firms themselves: in a recent survey of a large sample of U.S. executives, 95%
believed that they have “some” or “a high degree” of control when it comes to influencing the
happiness of their employees (see HBR Analytical Services, 2020). A growing body of evidence
suggests that employee happiness is at least partially determined by structural factors related to
how firms organize and manage work as well as the workplace cultures they create. Recent fieldexperimental evidence shows, for example, significant effects on wellbeing of various management
33
The mean number of satisfaction responses a worker receives per week in our sample is 2.66. 18% of workerweek observations have 0 customer responses and the modal number of responses is 1.
28
Electronic copy available at: https://ssrn.com/abstract=3470734
practices – including monitoring, performance information feedback, personal targets, and prosocial incentives (Gosnell, List and Metcalfe, 2020). Further work on aspects of work life—
such as manager support and flexibility (Moen et al., 2016), pay inequality (Breza, Kaur and
Shamdasani, 2017; Cullen and Perez-Truglia, 2019), gift exchange (DellaVigna et al., 2020), and
worker autonomy (Bloom et al., 2014)—has also shown that management practices can have
impacts on employee wellbeing.
Although there has been over a century of empirical work on the issue of employee wellbeing
and performance, there remains little causal evidence in the field. Thus our confirmation of
earlier laboratory findings (e.g. Erez and Isen, 2002; Oswald, Proto and Sgroi, 2015) is an
important step forwards in the literature. In particular, managers may worry that findings
inside the lab may not replicate or scale easily in real-life settings, and may not be able to
relate the experimental evidence to the types of tasks, skills and workplace environments that
their workers face. Our paper not only provides confirmation that the type of experimental
evidence generated in the lab replicates in the field, but suggests those effects may be even more
relevant when looking at more complex tasks involving real social interactions with customers.
Conversely, our results should lower managerial concerns that the benefits of happiness on
productivity may necessarily be smaller in real-life settings as more sociable workers would
simply tend to work less.
6.2
Magnitudes & Comparisons with Existing Literature
We estimate an average marginal effect of 3.36 additional sales for each one unit increase in
happiness (from a base of around 25 sales per week), suggesting around a 12% effect. This is for
a one unit increase in the 0-10 happiness scale, which has a within-worker standard deviation
of 2.37 during our study period. It is worth bearing in mind when thinking of magnitudes that
a 1 point change would be a relatively large increase. Indeed, the first stage and reduced form
estimates in our IV equation show that a one standard deviation increase in visual exposure
to weather has around a 0.2 point effect on happiness and around a 2.6% increase in sales per
week.
We can benchmark our estimates against other common predictors of sales in the data. We
run a pooled cross-sectional regression of sales on a number of demographic characteristics of
workers (as well as time fixed effects and the usual set of time-varying controls, as in our main
specification). In Figure S6, we show that workers who have at least 1 year of experience on the
job (compared with those with less than 1 year of tenure) generally make around 24% more sales
per week. Male workers and workers under 40 in general make around 10% more sales per week
on average. Finally, we can compare our instrumented estimate with the non-instrumented one.
The non-IV within-person partial correlation estimate is smaller, which is in line with the fact
that—as we discuss in more detail in Appendix B—the non-IV equation is likely to be severely
downward biased.
We can also compare our estimates with previous studies, in both lab and field. In the
experimental set-up of Oswald, Proto and Sgroi (2015), a short-run one standard deviation
increase in happiness (induced by viewing a comedy, as opposed to a placebo, video clip) causes
participants to correctly do around 29 to 35 percent more incentivized additions (See Appendix
29
Electronic copy available at: https://ssrn.com/abstract=3470734
K for further detail). In our setting, a one standard deviation increase in happiness (equivalent
to a 2.4 point increase on the 0-10 scale), leads to around a 30 percent increase in sales. In
addition to lab experiments, we can compare our estimates with the results of field experiments
in which management practices simultaneously impacted employee happiness and productivity.
In these contexts we cannot treat the relationship between happiness and productivity as a
causal parameter. Even so, we can assess the extent to which our estimates are consistent
with the observed patterns. Bloom et al. (2014), for example, run a field experiment that also
takes place within a call center setting on the impact of working-from-home. The policy change
led to a 0.55 standard deviation increase in positive emotions (and a 0.44 SD fall in negative
emotions), which, using our IV estimate, is consistent with the 13% increase in productivity
they observe.
Finally, we can compare our estimates with studies in the field using observational data such
as our own. Coviello et al. (2020) also study call center workers in the USA, but with a number
of differences to our study. First, the authors instrument for worker engagement—on a 1-to-5
scale corresponding to feeling ‘unstoppable’, ‘good’, ‘so so’, ‘exhausted’, and ‘frustrated’—using
weather patterns. Second, as opposed to sales, the outcome is short-run labor supply decisions
(i.e. percentage of unproductive time at work) and productivity in terms of work speed (i.e.
number of calls per hour). Third, the study focuses largely on customer service representatives
rather than sales workers, who perform a somewhat different task. In apparent contradiction
to our findings, the authors find that more engaged workers answer fewer calls per hour and
spend a higher percentage of time at work not working. We see the paper as complementary to
ours, since despite a number of differences between both settings, they also find positive (though
non-significant) effects within their sub-sample of sales workers. One possibility is that positive
productivity effects of happiness at work are likely to dominate any negative effect on labor
supply in contexts where tasks are well-defined (sales advisors have clear targets, for example).
However, for the various reasons outlined in Section 2, productivity effects of happiness are
likely to be stronger or weaker in different industries and occupations.34
6.3
Further Limitations
Our study has a number of weaknesses and there are various areas where future research is
required in order to better understand the relationship between positive affect and performance.
While we study weekly data over a six-month period, future research may benefit from studying
higher-frequency measures such as daily happiness surveys – though there are usually tradeoffs between frequency of mood data collection and the possible length of the study period,
with higher-frequency data typically being more difficult to collect in real-world settings and
requiring a much shorter study period. One potential avenue of future research in this direction
may be to use things like natural language processing of call transcripts to measure mood,
or tonal analysis of recordings, in order to obtain higher-frequency measures of mood without
34
A further possibility in this comparison is that the performance gains from positive mood may play a stronger
role at lower levels of happiness. Indeed, a key difference is that while a significant fraction of workers in our
sample report feeling unhappy, 70% of workers in Coviello et al. (2020) report feeling “good” or “unstoppable.”
However, this is unlikely to explain the difference: as discussed earlier, we do not find significant heterogeneity
in the effect of happiness between generally unhappy and generally happy workers (Table S13).
30
Electronic copy available at: https://ssrn.com/abstract=3470734
having to interrupt workers with surveys. Indeed, this type of approach may also allow for the
measurement of mood on the other side of the market – in our case, customers — opening up
a range of further potential research possibilities.
We rely for identification on exposure to weather using a measure of window coverage at
the call center level. Unfortunately, the firm does not have data on floor plans and does not
routinely collect data on who is sitting where in each building on any given day – such data
may in the future provide more power by providing individual-level (possibly even time-varying)
variation in proximity to windows. In our setting, however, we found that 96% of employees
reported working in an open office environment, such that even though being closer to the
window may provide some useful within-call-center variation in visual exposure to weather, this
variation is likely to be small relative to the between-call-center variation in window coverage we
rely on. Indeed, the very high correlation we obtain between our objective measure of external
window share and the subjective measure of natural light (r=0.91), which is even higher than
the correlation with subjective internal window share (r=0.83) provides further support for
those claims (see Figure 7).
In addition, while we demonstrate evidence suggestive of a causal effect using visual exposure
to weather, further research would benefit from using a range of different mood shocks in order
to improve generalizability – particularly using directly managerial shocks. Studying happiness
effects that are induced by managerial practices can be difficult, however, given that these
typically violate the exclusion restriction – for example, by the practice having a direct effect
on productivity or through a reciprocity-based mechanism whereby employees may respond
to wellbeing-enhancing policies by increasing effort (cf. Akerlof, 1982). Thus although our
weather-based approach may sacrifice some external validity, it does have the benefit of using
an exogenous shock to pin down a “pure” causal mood effect.
We study only one firm and one type of job. Future research may usefully study the extent
to which happiness determines performance in different types of settings – for example in jobs
with different kinds of tasks, different levels of monitoring, or in different locations and cultures.
As we discussed in Section 2, there are theoretical reasons to believe that happiness may have
a stronger effect on some types of tasks than others (and even have a negative effect in certain
contexts). For example, while links have been shown between mood and creativity in other
settings, this is unlikely to play a large role in a call center context. Relatedly, there may also
be diminishing marginal returns to happiness – that is, future research may explore the question
of whether there is some sort of optimal happiness level for productivity or whether more is
always better.
Our use of windows for identification, which essentially allow us to “turn on and off” the
effect of visual aspects of weather, allows us to rule out a number of issues related to the use of
weather in mood research. However, there may always be alternative explanations that we are
not able to fully rule out using our data and setting and that will, ultimately, require further
research. For example, rain may affect productivity through making noise, the extent to which
may vary between glass windows and solid walls (though we are able to replicate our effects
when dis-aggregating the weather index into parts other than rainfall, such as fog).35
35
In addition to noise, there may be sleep-related effects if window coverage affects people’s circadian rhythms
31
Electronic copy available at: https://ssrn.com/abstract=3470734
Finally, our setting is not well suited to isolating fine-grained mechanisms through which any
effect of mood on productivity may take place. While we have presented suggestive evidence
on channels, further research is ultimately required in order to make further progress – most
likely in more controlled laboratory settings or using carefully designed field experiments.
7
Conclusion
A long-running literature has sought to explain heterogeneity in productivity across individuals
as well as firms. In this paper, we contribute to an extensive literature in management and
elsewhere on the relationship between happiness and performance. We show a strong positive
impact of employee positive affect on productivity, in a real-world field setting. We follow
the existing mood-effects-in-the-field literature by first presenting reduced-form evidence of the
effects of weather. We extend this literature to the domain of productivity, and build on it by
providing three key pieces of further evidence. First, we clearly pin down mood shocks arising
from weather by exploiting variation in exposure to it. Second, we demonstrate using survey
data that visual exposure to weather while at work has a significant impact on workers’ weekto-week happiness. Third, we are able to provide quasi-experimental estimates of the effect of
happiness on sales. Of course, the latter requires us to make a number of further assumptions,
which we have sought to discuss as clearly as possible; however, we note that these estimates
are subject to the usual critiques of IV strategies to estimate causal effects using observational
data. Nevertheless, taking the three pieces of evidence as whole, we interpret the findings as
suggestive of a strong causal effect of positive affect on productivity.
References
Acemoglu, Daron, and Jörn-Steffen Pischke. 2003. “Minimum wages and on-the-job training.” Research in Labor Economics, 22(2003): 159–202.
Agarwal, Sumit, Souphala Chomsisengphet, Stephan Meier, and Xin Zou. 2020. “In
the mood to consume: Effect of sunshine on credit card spending.” Journal of Banking &
Finance, 121: 105960.
Akerlof, George A. 1982. “Labor contracts as partial gift exchange.” The quarterly journal
of economics, 97(4): 543–569.
Allcott, Hunt, Luca Braghieri, Sarah Eichmeyer, and Matthew Gentzkow. 2020.
“The welfare effects of social media.” American Economic Review, 110(3): 629–76.
Angrist, Joshua D, and Alan B Krueger. 1991. “Does compulsory school attendance affect
schooling and earnings?” The Quarterly Journal of Economics, 106(4): 979–1014.
Angrist, Joshua D, and Alan B Krueger. 2001. “Instrumental variables and the search
for identification: From supply and demand to natural experiments.” Journal of Economic
perspectives, 15(4): 69–85.
– though we rule out physical channels in general, in a more coarse way, by studying sickness and attendance.
Moreover, it is not clear why this physical effect should not also play a role when performing more routine tasks,
or when dealing with satisfied customers, which is where we find our effects to be smaller.
32
Electronic copy available at: https://ssrn.com/abstract=3470734
Angrist, Joshua D, and Guido W Imbens. 1995. “Two-stage least squares estimation of
average causal effects in models with variable treatment intensity.” Journal of the American
statistical Association, 90(430): 431–442.
Angrist, Joshua D, Guido W Imbens, and Donald B Rubin. 1996. “Identification of
causal effects using instrumental variables.” Journal of the American statistical Association,
91(434): 444–455.
Barsade, Sigal G, and Donald E Gibson. 2007. “Why does affect matter in organizations?”
Academy of management perspectives, 21(1): 36–59.
Benjamin, Daniel J, Jakina Debnam Guzman, Marc Fleurbaey, Ori Heffetz, and
Miles S Kimball. 2021. “What do happiness data mean? Theory and Survey Evidence.”
NBER Working Paper 28438.
Bloom, Nicholas, James Liang, John Roberts, and Zhichun Jenny Ying. 2014. “Does
working from home work? Evidence from a Chinese experiment.” Quarterly Journal of Economics, 130(1): 165–218.
Brayfield, Arthur H, and Walter H Crockett. 1951. “An index of job satisfaction.” Journal
of Applied Psychology, 35: 307–311.
Breza, Emily, Supreet Kaur, and Yogita Shamdasani. 2017. “The morale effects of pay
inequality.” Quarterly Journal of Economics, 133(2): 611–663.
Brief, Arthur P, and Howard M Weiss. 2002. “Organizational behavior: Affect in the
workplace.” Annual Review of Psychology, 53(1): 279–307.
Bryson, Alex, and George MacKerron. 2016. “Are you happy while you work?” The
Economic Journal, 127(599): 106–125.
Carnevale, Peter JD, and Alice M Isen. 1986. “The influence of positive affect and visual access on the discovery of integrative solutions in bilateral negotiation.” Organizational
behavior and human decision Processes, 37(1): 1–13.
Chang, Tom, Joshua Graff Zivin, Tal Gross, and Matthew Neidell. 2016. “Particulate
pollution and the productivity of pear packers.” American Economic Journal: Economic
Policy, 8(3): 141–69.
Chang, Tom Y, Joshua Graff Zivin, Tal Gross, and Matthew Neidell. 2019. “The effect
of pollution on worker productivity: evidence from call center workers in China.” American
Economic Journal: Applied Economics, 11(1): 151–72.
Clark, Andrew E. 2010. “Work, jobs, and well-being across the millennium.” International
differences in well-being, 436–468.
Côté, Stéphane. 1999. “Affect and performance in organizational settings.” Current Directions
in Psychological Science, 8(2): 65–68.
Coviello, Decio, Erika Deserranno, Nicola Persico, and Paola Sapienza. 2020. “Effect
of Mood and Worker Incentives on Workplace Productivity.” Mimeo.
Cullen, Zoë, and Ricardo Perez-Truglia. 2019. “How much does your boss make? the
effects of salary comparisons.”
Cunningham, Michael R. 1979. “Weather, mood, and helping behavior: Quasi experiments
with the sunshine samaritan.” Journal of personality and social psychology, 37(11): 1947.
33
Electronic copy available at: https://ssrn.com/abstract=3470734
DellaVigna, Stefano, John A List, Ulrike Malmendier, and Gautam Rao. 2020. “Estimating social preferences and gift exchange with a piece-rate design.” CEPR Discussion
Paper No. DP14931.
Deming, David J. 2017. “The growing importance of social skills in the labor market.” Quarterly Journal of Economics, 132(4): 1593–1640.
Denissen, Jaap JA, Ligaya Butalid, Lars Penke, and Marcel AG Van Aken. 2008.
“The effects of weather on daily mood: a multilevel approach.” Emotion, 8(5): 662.
Diener, Ed, Eunkook M Suh, Richard E Lucas, and Heidi L Smith. 1999. “Subjective
well-being: Three decades of progress.” Psychological Bulletin,, 125(2): 276.
Edmans, Alex. 2012. “The link between job satisfaction and firm value, with implications for
corporate social responsibility.” The Academy of Management Perspectives, 26(4): 1–19.
Edmans, Alex, Diego Garcia, and Øyvind Norli. 2007. “Sports sentiment and stock
returns.” The Journal of Finance, 62(4): 1967–1998.
Erez, Amir, and Alice M Isen. 2002. “The influence of positive affect on the components
of expectancy motivation.” Journal of Applied Psychology, 87(6): 1055.
Estrada, Carlos A, Alice M Isen, and Mark J Young. 1997. “Positive affect facilitates
integration of information and decreases anchoring in reasoning among physicians.” Organizational behavior and human decision processes, 72(1): 117–135.
Feddersen, John, Robert Metcalfe, and Mark Wooden. 2016. “Subjective wellbeing:
why weather matters.” Journal of the Royal Statistical Society Series A, 179(1): 203–228.
Finkelstein, Amy, Erzo FP Luttmer, and Matthew J Notowidigdo. 2013. “What good
is wealth without health? The effect of health on the marginal utility of consumption.”
Journal of the European Economic Association, 11(suppl 1): 221–258.
Fisher, Cynthia D. 2000. “Mood and emotions while working: missing pieces of job satisfaction?” Journal of Organizational Behavior, 21(2): 185–202.
Fisher, Vivian Ezra, and Joseph Vorhees Hanna. 1931. The dissatisfied worker. New
York:Macmillan.
Flynn, Sean Masaki, and Adam Eric Greenberg. 2012. “Does Weather Actually Affect
Tipping? An Empirical Analysis of Time-Series Data 1.” Journal of Applied Social Psychology, 42(3): 702–716.
Forgas, Joseph P. 1995. “Mood and judgment: the affect infusion model (AIM).” Psychological
Bulletin,, 117(1): 39.
Fredrickson, Barbara L. 2001. “The role of positive emotions in positive psychology: The
broaden-and-build theory of positive emotions.” American psychologist, 56(3): 218.
Frijda, Nico H. 1986. The Emotions. Cambridge University Press.
Frijters, Paul, Chitwan Lalji, and Debayan Pakrashi. 2020. “Daily weather only has small
effects on wellbeing in the US.” Journal of Economic Behavior & Organization, 176: 747–762.
Gallen, Trevor. 2020. “Broken Instruments.” SSRN Working Paper 3671850.
Gosnell, Greer K, John A List, and Robert D Metcalfe. 2020. “The impact of management practices on employee productivity: A field experiment with airline captains.” Journal
of Political Economy, 128(4): 1195–1233.
34
Electronic copy available at: https://ssrn.com/abstract=3470734
Graff Zivin, Joshua, and Matthew Neidell. 2012. “The impact of pollution on worker
productivity.” American Economic Review, 102(7): 3652–73.
Gubler, Timothy, Ian Larkin, and Lamar Pierce. 2018. “Doing well by making well:
The impact of corporate wellness programs on employee productivity.” Management Science,
64(11): 4967–4987.
Guven, Cahit. 2012. “Reversing the question: Does happiness affect consumption and savings
behavior?” Journal of Economic Psychology, 33(4): 701–717.
Guven, Cahit, and Indrit Hoxha. 2015. “Rain or shine: Happiness and risk-taking.” The
Quarterly Review of Economics and Finance, 57: 1–10.
HBR Analytical Services. 2020. “Cultivating Workforce Well-Being to Drive Business
Value.” https://bg.hbr.org/resources/pdfs/comm/workplacewellbeing.pdf.
Hersey, Rexford B. 1932. “Rate of Production and Emotional State.” Personnel Journal,
335–364.
Heyes, Anthony, and Soodeh Saberian. 2019. “Temperature and decisions: evidence from
207,000 court cases.” American Economic Journal: Applied Economics, 11(2): 238–65.
Hirshleifer, David, and Tyler Shumway. 2003. “Good day sunshine: Stock returns and the
weather.” The Journal of Finance, 58(3): 1009–1032.
Hochschild, Arlie R. 1983. The managed heart. Berkeley CA: University of California Press.
Huang, Jiekun, Nianhang Xu, and Honghai Yu. 2020. “Pollution and performance: Do
investors make worse trades on hazy days?” Management Science, 66(10): 4455–4476.
Hu, Maggie Rong, and Adrian D Lee. 2020. “Outshine to Outbid: Weather-Induced
Sentiment and the Housing Market.” Management Science, 66(3): 1440–1472.
Iaffaldano, Michelle T, and Paul M Muchinsky. 1985. “Job satisfaction and job performance: A meta-analysis.” Psychological Bulletin,, 97(2): 251.
Isen, Alice M. 1970. “Success, failure, attention, and reaction to others: The warm glow of
success.” Journal of personality and social psychology, 15(4): 294.
Isen, Alice M, and Barbara Means. 1983. “The influence of positive affect on decisionmaking strategy.” Social cognition, 2(1): 18–31.
Isen, Alice M, and Kimberly A Daubman. 1984. “The influence of affect on categorization.” Journal of personality and social psychology, 47(6): 1206.
Isen, Alice M, Andrew S Rosenzweig, and Mark J Young. 1991. “The influence of
positive affect on clinical problem solving.” Medical Decision Making, 11(3): 221–227.
Isen, Alice M, and Robert A Baron. 1991. “Positive affect as a factor in organizationalbehavior.” Research in organizational behavior, 13: 1–53.
Isen, Alice M, Kimberly A Daubman, and Gary P Nowicki. 1987. “Positive affect
facilitates creative problem solving.” Journal of personality and social psychology, 52(6): 1122.
Jones, Damon, David Molitor, and Julian Reif. 2019. “What do workplace wellness
programs do? Evidence from the Illinois workplace wellness study.” The Quarterly Journal
of Economics, 134(4): 1747–1791.
35
Electronic copy available at: https://ssrn.com/abstract=3470734
Judge, Timothy A, Carl J Thoresen, Joyce E Bono, and Gregory K Patton. 2001.
“The job satisfaction–job performance relationship: A qualitative and quantitative review.”
Psychological Bulletin,, 127(3): 376.
Kahneman, Daniel, Alan B Krueger, David A Schkade, Norbert Schwarz, and
Arthur A Stone. 2004. “A survey method for characterizing daily life experience: The day
reconstruction method.” Science, 306(5702): 1776–1780.
Kahneman, Daniel, Peter Wakker, and Rakesh Sarin. 1997. “Back to Bentham? Explorations of Experienced Utility.” Quarterly Journal of Economics, 112(2): 375–406.
Keller, Matthew C, Barbara L Fredrickson, Oscar Ybarra, Stéphane Côté, Kareem
Johnson, Joe Mikels, Anne Conway, and Tor Wager. 2005. “A warm heart and a
clear head: The contingent effects of weather on mood and cognition.” Psychological science,
16(9): 724–731.
Kemp, Simon, Christopher DB Burt, and Laura Furneaux. 2008. “A test of the peakend rule with extended autobiographical events.” Memory & Cognition, 36(1): 132–138.
Killingsworth, Matthew A, and Daniel T Gilbert. 2010. “A wandering mind is an unhappy mind.” Science, 330(6006): 932–932.
Knight, Andrew P, Jochen I Menges, and Heike Bruch. 2018. “Organizational affective
tone: A meso perspective on the origins and effects of consistent affect in organizations.”
Academy of Management Journal, 61(1): 191–219.
Koys, Daniel J. 2001. “The effects of employee satisfaction, organizational citizenship behavior, and turnover on organizational effectiveness: A unit-level, longitudinal study.” Personnel
Psychology, 54(1): 101–114.
Krekel, Christian, George Ward, and Jan-Emmanuel De Neve. 2019. “What makes
for a good job? Evidence using subjective wellbeing data.” In The Economics of Happiness.
, ed. Mariano Rojas, 241–268. Springer.
Kripke, Daniel F. 1998. “Light treatment for nonseasonal depression: speed, efficacy, and
combined treatment.” Journal of affective disorders, 49(2): 109–117.
Krueger, Alan B., and Arthur A. Stone. 2014. “Progress in Measuring Subjective WellBeing: moving toward national indicators and policy evaluations.” Science, 346(6205): 42–43.
Krueger, Alan B, and David A. Schkade. 2008. “The reliability of subjective well-being
measures.” Journal of Public Economics, 92: 1833–1845.
Krueger, Alan B, Daniel Kahneman, David Schkade, Norbert Schwarz, and
Arthur A Stone. 2009. “National time accounting: The currency of life.” In Measuring
the subjective well-being of nations: National accounts of time use and well-being. 9–86. University of Chicago Press.
Kunin, Theodore. 1955. “The Construction of a New Type of Attitude Measure 1.” Personnel
Psychology, 8(1): 65–77.
Lawler, Edward E, and Lyman W Porter. 1967. “The effect of performance on job satisfaction.” Industrial relations: A journal of Economy and Society, 7(1): 20–28.
Leppämäki, S, T Partonen, and J Lönnqvist. 2002. “Bright-light exposure combined with
physical exercise elevates mood.” Journal of Affective Disorders, 72(2): 139–144.
36
Electronic copy available at: https://ssrn.com/abstract=3470734
Li, Chenxi, Xueming Luo, Cheng Zhang, and Xiaoyi Wang. 2017. “Sunny, rainy, and
cloudy with a chance of mobile promotion effectiveness.” Marketing Science, 36(5): 762–779.
Lin, Wei, and Jeffrey M Wooldridge. 2019. “Testing and correcting for endogeneity in
nonlinear unobserved effects models.” In Panel Data Econometrics. , ed. Mike Tsionas, 21–
43. Elsevier.
Locke, Edwin A. 1969. “What is job satisfaction?” Organizational Behavior and Human
Performance, 4: 309–336.
Loewenstein, George. 2000. “Emotions in economic theory and economic behavior.” American Economic Review, 90(2): 426–432.
Lucas, Richard E, and Ed Diener. 2003. “The happy worker: Hypotheses about the role
of positive affect in worker productivity.” Personality and work, 30–59.
Meier, Armando N, Lukas Schmid, and Alois Stutzer. 2019. “Rain, emotions and voting
for the status quo.” European Economic Review, 119: 434–451.
Mellon, Jonathan. 2020. “Rain, Rain, Go away: 137 potential exclusion-restriction violations
for studies using weather as an instrumental variable.” SSRN Working Paper 3715610.
Miner, Andrew G, and Theresa M Glomb. 2010. “State mood, task performance, and
behavior at work: A within-persons approach.” Organizational Behavior and Human Decision
Processes, 112(1): 43–57.
Moen, Phyllis, Erin L Kelly, Wen Fan, Shi-Rong Lee, David Almeida, Ellen Ernst
Kossek, and Orfeu M Buxton. 2016. “Does a flexibility/support organizational initiative improve high-tech employees’ well-being? Evidence from the work, family, and health
network.” American Sociological Review, 81(1): 134–164.
OECD.
2013.
“Guidelines
on
Measuring
Subjective
Wellbeing.”
https://www.oecd.org/statistics/oecd-guidelines-on-measuring-subjective-well-being9789264191655-en.htm.
Oswald, Andrew J, Eugenio Proto, and Daniel Sgroi. 2015. “Happiness and productivity.” Journal of Labor Economics, 33(4): 789–822.
Park, R Jisung, Joshua Goodman, Michael Hurwitz, and Jonathan Smith. 2020.
“Heat and learning.” American Economic Journal: Economic Policy, 12(2): 306–39.
Rind, Bruce. 1996. “Effect of beliefs about weather conditions on tipping.” Journal of Applied
Social Psychology, 26(2): 137–147.
Rothbard, Nancy P, and Steffanie L Wilk. 2011. “Waking up on the right or wrong side of
the bed: Start-of-workday mood, work events, employee affect, and performance.” Academy
of Management Journal, 54(5): 959–980.
Russell, James A, and Lisa Feldman Barrett. 1999. “Core affect, prototypical emotional
episodes, and other things called emotion: dissecting the elephant.” Journal of personality
and social psychology, 76(5): 805.
Saunders, Edward M. 1993. “Stock prices and Wall Street weather.” American Economic
Review, 83(5): 1337–1345.
Schneider, Daniel, and Kristen Harknett. 2019. “Consequences of routine work-schedule
instability for worker health and well-being.” American Sociological Review, 84(1): 82–114.
37
Electronic copy available at: https://ssrn.com/abstract=3470734
Singh, Jagdip. 2000. “Performance productivity and quality of frontline employees in service
organizations.” Journal of marketing, 64(2): 15–34.
Spamann, Holger. 2022. “Comment on ”Temperature and Decisions: Evidence from 207,000
Court Cases”.” American Economic Journal: Applied Economics, 14(4): 519–28.
Staw, Barry M, and Sigal G Barsade. 1993. “Affect and managerial performance: A test of
the sadder-but-wiser vs. happier-and-smarter hypotheses.” Administrative Science Quarterly,
304–331.
Staw, Barry M, Robert I Sutton, and Lisa H Pelled. 1994. “Employee positive emotion
and favorable outcomes at the workplace.” Organization Science, 5(1): 51–71.
Syverson, Chad. 2011. “What determines productivity?” Journal of Economic Literature,
49(2): 326–65.
Tenney, Elizabeth R, Jared M Poole, and Ed Diener. 2016. “Does positivity enhance
work performance?: Why, when, and what we don’t know.” Research in Organizational Behavior, 36: 27–46.
Thomas, David L, and Ed Diener. 1990. “Memory accuracy in the recall of emotions.”
Journal of personality and social psychology, 59(2): 291.
Walsh, Lisa C, Julia K Boehm, and Sonja Lyubomirsky. 2018. “Does happiness promote
career success? Revisiting the evidence.” Journal of Career Assessment, 26(2): 199–219.
Wright, Thomas A, and Russell Cropanzano. 2000. “Psychological well-being and job
satisfaction as predictors of job performance.” Journal of occupational health psychology,
5(1): 84.
Zelenski, John M, Steven A Murphy, and David A Jenkins. 2008. “The happyproductive worker thesis revisited.” Journal of Happiness Studies, 9(4): 521–537.
38
Electronic copy available at: https://ssrn.com/abstract=3470734
Appendix
Table A1: Summary Statistics
Happiness
Sales
Selling Time
Internal Shrinkage
Customer Satisfaction
Adherence
Calls per Hour
Conversion Rate
Sick Leave
Attendance
Breaks (hrs)
Overtime (hrs)
Paid Time Off (hrs)
Visual Weather Index
Visual Exposure to Weather
Windows (% of wall surface)
Age
Female
Tenure
Left Firm During Study
N
Mean
12,282
12,282
12,282
12,282
10,120
12,174
12,282
11,850
12,279
12,279
12,282
12,282
12,282
12,282
12,282
1,157
1,157
1,157
1,157
1,157
4.01
25.25
19.99
10.52
7.90
91.99
4.96
26.63
1.58
92.58
3.77
0.15
1.07
4.06
0.77
0.20
33.81
0.41
4.99
0.04
Standard Deviation
Overall Between Within
3.44
2.55
2.37
19.16
14.89
12.41
8.18
5.69
6.38
13.30
10.11
10.74
2.26
1.20
2.06
5.48
3.58
4.34
1.62
1.16
1.14
17.98
15.77
10.59
7.73
3.37
7.26
14.14
6.55
13.15
1.49
1.15
1.09
0.98
0.48
0.89
2.99
1.36
2.78
1.78
1.18
1.36
0.62
0.53
0.32
0.14
10.41
0.50
7.17
0.26
39
Electronic copy available at: https://ssrn.com/abstract=3470734
Supplementary Online Materials
Does Employee Happiness Have an Impact on Productivity?
Clement Bellet, Jan-Emmanuel De Neve, and George Ward
Appendix A
Enrollment/Attrition/Non-Response
Table S1: Predictors of attrition/non-response
Responded to Survey = 1
Sales
Selling time
Not working on thursday/friday
(1)
-0.000
(0.000)
0.008∗∗∗
(0.001)
-0.153∗∗∗
(0.007)
Weather index
(2)
-0.000
(0.000)
0.008∗∗∗
(0.001)
-0.153∗∗∗
(0.007)
0.001
(0.002)
Weather * windows
(3)
-0.000
(0.000)
0.008∗∗∗
(0.001)
-0.153∗∗∗
(0.007)
(5)
-0.000
(0.000)
0.008∗∗∗
(0.001)
-0.153∗∗∗
(0.007)
0.001
(0.002)
0.002
(0.008)
Team happiness (excl. worker)
Observations
R2
(4)
-0.000
(0.000)
0.008∗∗∗
(0.001)
-0.153∗∗∗
(0.007)
33,725
0.448
33,725
0.448
33,725
0.448
-0.001
(0.001)
33,725
0.448
-0.001
(0.001)
33,725
0.448
(6)
-0.000
(0.000)
0.008∗∗∗
(0.001)
-0.153∗∗∗
(0.007)
0.002
(0.008)
-0.001
(0.001)
33,725
0.448
Notes: Robust standard errors in parentheses, adjusted for two-way clustering on individuals and location-week.
Linear models reported, estimated by OLS. Unit of observation is worker-week. Individual and week fixed effects
in all regressions. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
i
Electronic copy available at: https://ssrn.com/abstract=3470734
Table S2: Predictors of study participation: Extensive Margin
Participated in the study = 1
Age
Female
Left firm during study
Tenure (months)
Mean selling hours during study
(1)
-0.002∗
(0.001)
-0.003
(0.019)
-0.127∗∗∗
(0.034)
-0.019∗
(0.010)
0.009∗∗∗
(0.001)
Mean sales during study
Mean team happiness (excl. worker)
(2)
-0.003∗∗
(0.001)
-0.005
(0.022)
-0.131∗∗∗
(0.036)
-0.018
(0.012)
0.010∗∗∗
(0.002)
-0.001
(0.001)
-0.007
(0.006)
Mean bright/gloomy weather (call center)
Building window coverage
(3)
-0.003∗∗
(0.001)
-0.005
(0.022)
-0.133∗∗∗
(0.037)
-0.018
(0.012)
0.010∗∗∗
(0.002)
-0.001
(0.001)
-0.007
(0.006)
-0.006
(0.005)
-0.073
(0.060)
(4)
-0.003∗∗
(0.001)
-0.003
(0.023)
-0.136∗∗∗
(0.035)
-0.020
(0.012)
0.010∗∗∗
(0.003)
-0.001
(0.002)
-0.004
(0.007)
(5)
-0.003∗∗
(0.001)
-0.002
(0.025)
-0.131∗∗∗
(0.034)
-0.020
(0.012)
0.007∗∗
(0.003)
-0.001
(0.002)
-0.006
(0.007)
Yes
1,762
0.061
-0.206∗∗∗
(0.051)
Yes
1,762
0.069
Not working on thursday/friday
Call center dummies
Observations
R2
No
1,793
0.054
No
1,762
0.057
No
1,762
0.058
Notes: Robust standard errors in parentheses, clustered on call centers. Participated =1 if worker responded to at
least one survey. LPMs reported. 1,438 workers (80.2%) participated in the study. A small number of workers did
not observably belong to a team, which explains the drop in sample size after column (1). ∗ p < 0.10, ∗∗ p < 0.05,
∗∗∗
p < 0.01.
ii
Electronic copy available at: https://ssrn.com/abstract=3470734
Table S3: Predictors of study participation: Intensive Margin
# Waves responded to survey
Age
Female
Left firm during study
Tenure (months)
Mean selling hours during study
(1)
(2)
(3)
(4)
(5)
0.006∗∗∗
(0.002)
-0.080∗∗
(0.037)
-0.862∗∗∗
(0.039)
-0.041∗∗
(0.019)
0.022∗∗∗
(0.004)
0.006∗∗∗
(0.002)
-0.084∗∗
(0.036)
-0.850∗∗∗
(0.044)
-0.045∗∗
(0.021)
0.022∗∗∗
(0.005)
-0.000
(0.002)
-0.027
(0.017)
0.006∗∗∗
(0.002)
-0.084∗∗
(0.037)
-0.847∗∗∗
(0.045)
-0.047∗∗
(0.022)
0.022∗∗∗
(0.005)
-0.000
(0.001)
-0.027
(0.017)
0.019
(0.012)
0.027
(0.094)
0.006∗∗∗
(0.002)
-0.072∗∗
(0.034)
-0.856∗∗∗
(0.042)
-0.057∗∗∗
(0.021)
0.025∗∗∗
(0.004)
-0.001
(0.001)
-0.021
(0.019)
0.006∗∗∗
(0.002)
-0.072∗∗
(0.031)
-0.865∗∗∗
(0.041)
-0.063∗∗∗
(0.021)
0.018∗∗∗
(0.004)
-0.001
(0.001)
-0.022
(0.019)
Yes
1,413
-0.546∗∗∗
(0.127)
Yes
1,413
Mean sales during study
Mean team happiness (excl. worker)
Mean bright/gloomy weather (call center)
Building window coverage
Not working on thursday/friday
Call center dummies
Observations
No
1,438
No
1,413
No
1,413
Notes: Robust standard errors in parentheses, clustered on call centers. Poisson estimates reported. Sample is
all workers who participated in the study. A small number of workers did not observably belong to a team, which
explains the drop in sample size after column (1). ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
Table S4: Impact of Visual Exposure to Weather on Sales and Happiness: Imputed Missing
Happiness Data
Sales
Visual Exposure to Weather (SDs)
Observations
Individual + Time FEs
Work Schedule
Imputation of Missing Happiness:
(1)
Red. Form
-0.0244∗∗∗
(0.0086)
24,915
Yes
Yes
Happiness
(2)
1st Stage
-0.0868∗∗∗
(0.0266)
24,915
Yes
Yes
Low
(3)
1st Stage
-0.0922∗∗∗
(0.0273)
24,915
Yes
Yes
High
Notes: Notes: Poisson-FE and OLS-FE estimates reported. Robust standard errors in parentheses, adjusted for
two-way clustering on individuals and location-week. All regressions include individual and time fixed effects,
work schedule controls, and indicator variables for day of week of response to survey. Missing happiness data
imputed using the lowest (column (2)) and highest (column (3)) non-missing reported happiness levels within
worker. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
iii
Electronic copy available at: https://ssrn.com/abstract=3470734
Appendix B
Evidence of Downward Bias in Baseline Equation
There are a number of reasons to be concerned that β in equation (1) may be biased. One
initial reason is measurement error in the survey, which will bias the coefficients downward. A
second reason is the existence of omitted variables that may affect both reported happiness and
productivity week-to-week. A significant further empirical concern is that, even within-workers
over time, a change in SWB is likely to be endogenous to performance. We see two (opposing)
major ways in which reverse causality may bias our coefficients. First, more productive workers
can get compensated for their higher performance through monetary or non-monetary rewards,
for example from their colleagues or managers or simply enjoy successfully completing tasks.
This alone could explain their higher happiness, in which case the β coefficient will be biased
upward. Second, what makes workers happier could lower their productivity, depressing the
true β coefficient. One major candidate is the quantity of work. Over-work can lead to stress
and anxiety, which are both strongly negatively correlated with happiness. Equally, doing more
work may simply be less enjoyable. If this is the case, the coefficient will be biased even further
downward.
Table S5: Evidence of Downward Bias in OLS: Happiness and Number of Calls
Total number of weekly calls (ln)
Observations
Employees
R2
Pseudo-R2
Week FEs
Individual FEs
Happiness
Sales
(1)
OLS-FE
-0.5217∗∗∗
(0.1073)
12,282
1,157
0.535
(2)
Poisson-FE
0.0837∗
(0.0462)
12,282
1,157
X
X
0.620
X
X
Notes: Robust standard errors in parentheses, adjusted for two-way clustering on individuals and locationweek. All regressions include scheduling controls and day of week dummies for response to survey. ∗ p < 0.10,
∗∗
p < 0.05, ∗∗∗ p < 0.01.
In a customer-facing retail setting, we expect a strongly downward bias. In call centers,
there is a pressure to deal with a constant flow of incoming calls, often initiated by unhappy
customers (e.g. re-contracting), which led management scholars (Singh, 2000) to discuss the
conflict between work pressure (e.g., calls per hour) and the quality of work (e.g., call conversion). Although pay is partly based on performance in our setting, this is a slow moving bonus
scheme that makes up only a relatively small amount of total earnings, and so is unlikely to play
a major role. We thus expect higher work volumes to lead to lower happiness among workers.
We use our data and setting to provide direct evidence of this. In Table S5, we regress weekly
happiness on the weekly number of calls received and a full set of individual and week fixed
effects as well as the usual controls included in equation (1). We document a strong negative
impact on workers’ happiness of total number of weekly calls answered. Answering twice as
many calls leads to a fall in happiness of nearly 0.52 points, which corresponds to a happiness
drop of about 20% of a standard deviation within workers. This number even goes to a 30%
drop if we control for sales to capture the fraction of “successful” calls. Because happier workers are also answering fewer calls, our initial estimates from equation (1) are thus likely to be
strongly biased downward.36
36
Note that despite the positive relationship between total number of calls and sales, we still find that happiness
iv
Electronic copy available at: https://ssrn.com/abstract=3470734
Appendix C
Additional Tables and Figures for IV Set-Up
Figure S1: Correlation Between Window Share, Mean Happiness and Standard Deviation in
Week-to-Week (Residual) Happiness at Location
Note: Upper-panels: correlation between mean worker happiness and windows at location. Lower-panels: correlation between standard-deviation week-to-week (residual) worker happiness and windows at location. The residual
happiness is estimated from a regression with worker fixed effects and time-varying controls other than local weekly
weather shocks. Each dot represents a location.
improves sales using equation (1). This is consistent with sales calls generating less emotional distress than nonsales calls, or with happiness affecting performance mostly through the conversion of calls into sales, a possibility
we later explore in the paper.
v
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure S2: Correlation Between Window Share, Mean Sales and Standard Deviation in Weekto-Week (Residual) Sales at Location
Note: Upper-panels: correlation between mean worker sales and windows at location. Lower-panels: correlation
between standard-deviation week-to-week (residual) worker happiness and sales at location. The residual sales is
estimated from a regression with worker fixed effects and time-varying controls other than local weekly weather
shocks. Each dot represents a location.
vi
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure S3: Within-worker Association of Happiness and Sales
Note: Coefficients and 95% confidence intervals shown, estimated using Poisson regression, in which the number
of sales are regressed on a series of happiness dummies, a full set of individual and time fixed effects, as well as
scheduling controls.
Figure S4: IV First Stage: Graphical Representation
Note: Figure shows binned scatter plots of the relationship between visual exposure to weather and happiness,
adjusting for individual and week fixed effects as well as the full set of further controls. Visual exposure is
the weather index multiplied by window coverage, which is measured in three different ways (1 objective and 2
subjective) – see text for more details.
vii
Electronic copy available at: https://ssrn.com/abstract=3470734
Appendix D
Additional Robustness
Table S6: Daily Call-Center-Level Regressions
Visual Weather Index
Observations
R2
Pseudo-R2
Local Demand
(Poisson-FE)
-0.0054
(0.0048)
1,415
Local Speed
(OLS-FE)
0.0055
(0.0049)
1,415
0.839
0.118
Notes: Poisson-FE and OLS-FE estimates reported. Robust standard errors in parentheses, clustered on call
centers. All regressions include call center and date fixed effects. Local demand is the mean number of calls per
employee-day in each call center. Local speed is the mean length of call per employee-day (logged) in each call
center.
Figure S5: Impact of Visually Bright or Gloomy Weather on Weekly Happiness and Sales
Note: Left: Poisson-FE estimates reported with weekly sales as dependent variable. Right: OLS-FE estimates
reported with weekly happiness as dependent variable. Mostly bright weather defined as less than 2 on the weather
index and mostly gloomy weather defined as more than 6. The models are estimated separately on each sub-sample
of high vs. low window coverage locations, defined as above vs. below median window coverage. All regressions
include individual and week fixed effects, work schedule controls, and dummies for day of week of response to
survey. 95% confidence intervals are constructed using robust standard errors, adjusted for two-way clustering on
individuals and location-week.
viii
Electronic copy available at: https://ssrn.com/abstract=3470734
Table S7: Results When Using Weather Index Dis-Aggregated
1st Stage IV
2nd Stage IV
(1)
(2)
0.1219∗∗∗
(0.0422)
Happiness
Visual Exposure to Fog
Visual Exposure to Rain
Visual Exposure to Snow
Observations
1st Stage F-Stat
-0.4198∗∗∗
(0.1404)
-0.2578∗∗
(0.1069)
-0.3084
(0.2421)
12,282
6.95
12,282
Notes: 2SLS estimates reported. Robust standard errors in parentheses, adjusted for two-way clustering on
individuals and location-week. All regressions include individual and week fixed effects, work schedule controls,
and dummies for day of week of response to survey. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
Table S8: Visual Weather Index vs. Local Share of Sick Employees
Local Sickness
(1)
Panel A: Daily Call-Center-Level Regressions
Visual Weather Index (Daily)
-0.1070
(0.1052)
Visual Weather Index (Daily, 1-Day Lag)
Observations
R2
Panel B: Weekly Call-Center-Level Regressions
Visual Weather Index (Weekly)
1,428
0.335
-0.1191
(0.1180)
1,139
0.336
-0.1116
(0.0713)
Visual Weather Index (1-Week Lag)
Observations
R2
(2)
289
0.199
-0.1012
(0.0873)
276
0.213
Notes: OLS-FE estimates reported. Robust standard errors in parentheses, clustered on call centers and time.
All regressions include call center and time fixed effects.
ix
Electronic copy available at: https://ssrn.com/abstract=3470734
Table S9: Baseline Characteristics Across High vs. Low Window Share Workplaces
Windows (% wall surface)
Visual Weather Index
Age
Female
Tenure
Left the firm during study
Low Windows
(Mean)
0.10
4.28
34.92
0.47
7.11
0.06
High Windows
(Mean)
0.35
3.64
32.69
0.39
4.14
0.08
Diff.
(t-test)
-0.24∗∗∗
0.64
2.22
0.09∗
2.97
-0.02
Notes: Balance table compares observed characteristics for workplaces with below median (low) versus above
median (high) window share. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
Table S10: Sensitivity to Weather: Heterogeneous Effects
Happiness
Visual Weather Index
(1)
-0.0617∗∗∗
(0.0207)
Weather Interaction:
× Female Worker
(2)
-0.0438∗
(0.0253)
(3)
-0.0324
(0.0596)
(4)
-0.0658∗∗∗
(0.0247)
(5)
-0.0850∗∗∗
(0.0287)
-0.0449
(0.0358)
× Worker’s Age
-0.0008
(0.0016)
× Worker’s Tenure (Years)
0.0007
(0.0021)
× Worker Avg Sickness > Median
0.0477
(0.0353)
× # Sales
Observations
R2
(6)
-0.0711∗∗
(0.0295)
12,282
0.534
12,282
0.534
12,282
0.534
12,282
0.534
12,280
0.534
0.0004
(0.0009)
12,282
0.536
Notes: OLS-FE estimates reported. Robust standard errors in parentheses, adjusted for two-way clustering on
individuals and location-week. All regressions include individual and week fixed effects, work schedule controls,
and day of response to survey. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
x
Electronic copy available at: https://ssrn.com/abstract=3470734
Table S11: Visual Exposure to Weather: 1st Stage Treatment Effects (LATE)
Happiness
Visual Exposure to Weather (SDs)
(1)
-0.1950∗∗∗
(0.0442)
Weather Interaction:
× Female Worker
(2)
-0.1763∗∗∗
(0.0568)
(3)
-0.0841
(0.1423)
(4)
-0.1751∗∗∗
(0.0501)
(5)
-0.2331∗∗∗
(0.0630)
(6)
-0.2079∗∗∗
(0.0562)
-0.0490
(0.0827)
× Worker’s Age
-0.0032
(0.0038)
× Worker’s Tenure (Years)
-0.0045
(0.0053)
× Worker Avg Sickness > Median
0.0776
(0.0795)
× # Sales
Observations
R2
12,282
0.534
12,282
0.534
12,282
0.534
12,282
0.534
0.0008
(0.0020)
12,282
0.537
12,280
0.534
Notes: OLS-FE estimates reported. Robust standard errors in parentheses, adjusted for two-way clustering on
individuals and location-week. All regressions include individual and week fixed effects, work schedule controls,
and day of response to survey. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
Table S12: Analysis of Potential Seasonal Effects
Happiness
Visual Exposure to Weather (SDs)
(1)
-0.1950∗∗∗
(0.0442)
(2)
-0.1807∗∗
(0.0732)
12282
-0.0386
(0.0808)
0.0086
(0.0880)
-0.0800
(0.0868)
0.0524
(0.1018)
0.0652
(0.1003)
0.0224
(0.1336)
12282
Interaction with Month (Ref. Month: January 2018)
December 2017
November 2017
October 2017
September 2017
August 2017
July 2017
Observations
Sales
(3)
-0.0258∗∗
(0.0104)
(4)
-0.0311∗
(0.0166)
12282
0.0014
(0.0164)
0.0201
(0.0181)
-0.0194
(0.0188)
0.0231
(0.0198)
0.0099
(0.0178)
0.0366
(0.0236)
12282
Notes: Columns (1)-(2) estimated using OLS-FE. Columns (3)-(4) estimated using Poisson-FE. All regressions include individual and week fixed effects, work schedule controls, and day of week dummies for response
to survey. Robust standard errors in parentheses, adjusted for two-way clustering on individuals and locationweek. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
xi
Electronic copy available at: https://ssrn.com/abstract=3470734
Table S13: Impact of Happiness on Sales Performance: Sub-Group Analysis
Happiness
Observations
All
Workers
Unhappy
Workers
Happy
Workers
Unproductive
Workers
Productive
Workers
(1)
0.1424∗∗∗
(0.0465)
12,282
(2)
0.1354∗∗
(0.0541)
6,153
(3)
0.1515∗∗
(0.0641)
6,129
(4)
0.1432∗∗
(0.0727)
6,064
(5)
0.1430∗∗∗
(0.0514)
6,218
Notes: Robust standard errors in parentheses, adjusted for two-way clustering on individuals and locationweek. 2SLS estimates reported. All regressions include individual and week fixed effects, work schedule
controls, and dummies for day of week of response to survey. Sample is split above/below median within
each call center in terms of average sales per hour and happiness over the whole study period. ∗ p < 0.10,
∗∗
p < 0.05, ∗∗∗ p < 0.01.
Table S14: Placebo Regressions: Week Before (Lag) vs. After (Lead)
Happiness
(weekly)
(1)
-0.1950∗∗∗
(0.0442)
Visual Exposure to Weather (SDs)
Visual Exposure to Weather (SDs, 1-week lag)
Visual Exposure to Weather (SDs, 1-week lead)
(2)
-0.1925∗∗∗
(0.0443)
0.0437
(0.0457)
-0.0282
(0.0548)
Happiness
Sales
(weekly)
(3)
(4)
0.0141∗∗∗
(0.0014)
0.0168∗∗∗
(0.0022)
-0.0014
(0.0023)
0.0019
(0.0020)
4,522
Happiness (1-week lag)
Happiness (1-week lead)
Observations
12,282
12,137
12,282
Notes: Robust standard errors in parentheses, adjusted for two-way clustering on individuals and locationweek. All regressions include individual and week fixed effects, work schedule controls, and day of week
dummies for response to survey. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
xii
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure S6: Effect Size Bench-marking
Note: Coefficients and 95% confidence intervals reported from a cross-sectional Poisson regression. Dependent
variable is the weekly number of sales. The model includes scheduling controls and study week fixed effects.
xiii
Electronic copy available at: https://ssrn.com/abstract=3470734
Appendix E
Analysis using Daily Data
Table S15: Reduced Form Effects of Daily Weather on Daily Sales
Daily Sales
(Poisson-FE)
Visual Exposure to Weather (Daily)
(1)
-0.0094∗
(0.0048)
(2)
-0.0086∗
(0.0050)
Visual Exposure to Weather (Weekly)
Observations
Time FEs
42,111
Week
42,111
Day
(3)
(4)
-0.0238∗∗
(0.0109)
42,111
Week
-0.0234∗∗
(0.0109)
42,111
Day
Notes: Poisson-FE estimates reported. Robust standard errors in parentheses, adjusted for two-way clustering
on individuals and location-week. All regressions include individual and date fixed effects, along with daily work
schedule controls. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
Figure S7: Impact of Visual Exposure to Weather on Happiness Before/After Response Day to
Happiness Survey
Note: Left: Impact of daily visual exposure to weather (SDs) on reported happiness estimated using OLS-FE.
Right: Impact of reported happiness on daily sales estimated using Poisson-FE. 95% confidence intervals are
constructed using robust standard errors, adjusted for two-way clustering on individuals and location-week.
xiv
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure S8: Distribution of (Residual) Weather Index Across Locations (Within Weeks vs. Days)
Note: Kernel density distribution of residual weather index across locations within weeks vs. within days from a
regression of the (normalized) weather index on week and location fixed effects (bin width = 0.2).
xv
Electronic copy available at: https://ssrn.com/abstract=3470734
Appendix F
Suggestive Evidence on Mechanisms
Table S16: Impact of Adherence and Speed on Sales Conditional on Labor Supply
Sales
(1)
Labor Productivity:
Adherence (Met Target=1)
(2)
(3)
-0.0579
(0.0365)
0.0034
(0.0079)
-0.0616∗
(0.0365)
0.9926∗∗∗
(0.0135)
0.0000
(0.0005)
12,100
0.9967∗∗∗
(0.0135)
0.0007
(0.0005)
12,033
0.0034
(0.0079)
Total number of calls per hour (ln)
Labor Supply:
Total number of selling hours (ln)
0.9831∗∗∗
(0.0184)
0.0007
(0.0005)
12,169
Internal shrinkage
Observations
Notes: Poisson-FE estimates reported. Robust standard errors in parentheses, adjusted for two-way clustering
on individuals and location-week. All regressions include individual and week fixed effects, scheduling controls,
and day of response to survey. ∗ p < 0.10, ∗∗ p < 0.05, ∗∗∗ p < 0.01.
Table S17: Happiness and Customer Satisfaction
Customer Satisfaction (z-score)
Visual Exposure to Weather
(1)
OLS-FE
0.0168
(0.0172)
(2)
OLS-FE
0.0176
(0.0171)
Happiness
# Sales
Observations
R2
1st Stage F-Stat
10,059
0.173
0.0032∗∗∗
(0.0011)
10,059
0.174
(3)
2SLS
(4)
2SLS
-0.0824
(0.0864)
-0.0886
(0.0878)
0.0052∗∗
(0.0023)
10,059
-0.060
18.59
10,059
-0.055
20.16
Notes: Robust standard errors in parentheses, adjusted for two-way clustering on individuals and locationweek. All regressions include scheduling controls and day of week dummies for response to survey. ∗ p < 0.10,
∗∗
p < 0.05, ∗∗∗ p < 0.01.
xvi
Electronic copy available at: https://ssrn.com/abstract=3470734
Figure S9: Effects by Type of Sales and National Levels of Customer Satisfaction
Note: Coefficients and 95% confidence intervals shown, estimated using Poisson-IV (where happiness is instrumented using visual exposure to weather). Visual exposure to weather is a z-scored index resulting from the
interaction between the window share of a call centre and the visual weather index that measures the total number
of daily instances of fog, rain, and snow. The outcome in all cases is the number of sales, but separate regressions
are estimated according to the type of sale. The sample is then divided into weeks with above vs. below median
levels of national customer satisfaction. National customer satisfaction is the share of BT workers dealing with
satisfied customers (customer satisfaction > 7) each week, excluding the worker’s own workplace.
xvii
Electronic copy available at: https://ssrn.com/abstract=3470734
Appendix G
Replication Details
In this appendix we provide details for practitioners or academics who may seek to replicate
the analysis presented in this paper. These replication steps can be applied to study weatherinduced mood effects in a variety of contexts, in order to build a fuller picture of the effect of
mood on productivity across different workplaces. More specific detail on the measures we use
and procedures we follow are provided in the text of the main manuscript and other areas of the
online supplementary materials. We also provide the code used to perform our analyses using
Stata.
The first step will be to identify a job that is being performed where productivity can be
quantified and measured repeatedly over time. Having obtained productivity outcome data,
it will be necessary to also collect data on labor inputs – such as attendance and time spent
on tasks – as well as further data on worker characteristics such as age, tenure, and gender.
In our context we focus on weekly measures of workplace behaviors and outcomes; however,
replications using even more high-frequency measures (e.g. within a daily shift) would build
well on this research.
The second step will be to measure workers’ mood over time. To replicate our study directly,
this would be done via a weekly email survey. But it may be useful to replicate this type of
study using different frequency and types of measurement tools, as we discuss in the paper.
Equally, for a direct replication, one would use the same happiness question as we did (see
Figure 3 for a screenshot of the email question and answer key); however, it may be useful to
build on our work by measuring different aspects of the affective wellbeing of workers.
With repeated measures of productivity and affect in hand, it will be possible to replicate
the within-worker specification of the paper, which regress productivity on happiness (and timevarying labor inputs) together with a set of individual and time-period fixed effects. However,
in order to more fully replicate our study, further steps are required.
The third step is to identify a context in which i) work is carried out across multiple sites
that are ii) sufficiently geographically spread such that there is significant variation in weather
patterns, across sites, even within a given time period. Moreover, a context is required in which
there is iii) significant variation in visual exposure to weather. This third element of the context
is achieved in our study by having large variation in architecture of buildings in terms of their
window coverage.
Having identified such a study site, a fourth step is to link workplaces geographically to
weather stations and to collect appropriate weather data (for more details of our approach to
weather data linkage, see Appendix H). We used various visually adverse weather conditions
like fog, snow, and rain; however, replicators may also usefully leverage other visual weather
patterns such as sunshine that were difficult to measure consistently in our context.
The fifth step is to quantify window coverage of buildings. For example, by defining percentage of walls covered by windows (for more details of our measurement in this regard, including
software used, see Appendix I) or by surveying workers on their perceived access to windows
while at work (for more details of our survey, including question wordings, see Appendix J).
Without significant variation in building types, an alternative route that may be available to
replicators would be to find a context in which there is less variation in architecture but in
which one can track the individual-level placement of workers within a building – and thus nevertheless have variation in visual exposure to outdoor weather. Equally, it may be possible to
try to leverage alternative mood shocks that affect how happy people are at work but that are
arguably not directly or indirectly related to success on the task at hand (other than through
the mood channel), such as – with some assumptions – local sports results. Such additional
analysis would usefully add to our understanding and provide additional generalizability.
Once data has been collected and collated, the final step is the analysis. The first stage of
analysis will be to run a reduced form regression of the effect of visual exposure to weather on
xviii
Electronic copy available at: https://ssrn.com/abstract=3470734
productivity. This can, in principle, be done using existing observational data where happiness
has not (yet) been measured – which would provide a useful first step toward replication even
in contexts where it is difficult, for whatever reason, to measure mood directly. The second step
provides more validity to the analysis, however, by checking that visual exposure to weather does
in fact affect happiness within-workers over time (i.e. check there is a sufficiently powerful first
stage such that the instrument may be valid). Using these two steps of analysis, it is possible
to then estimate the IV specifications of our paper, in order to – with a series of assumptions –
attempt to back out an estimate of the direct effect of happiness on productivity. A final step
in the analysis is to run a set of empirical checks in order to demonstrate the validity of the
exclusion restriction and other aspects of the research design. The nature of these will depend
upon the context that is being studied; however, we detail a series of such tests in the paper
that should serve as a good starting point in this regard.
Appendix H
Extra Detail on Visual Weather Index
We determine the latitude and longitude of each call center, and match each center to the
closest weather station available in the NOAA Global Surface Summary of the Day database,
which is on average 14km away. We construct for each call center location a Visual Weather
Index, corresponding to the total number of daily incidences of fog, rain and snow during the
working week for which individuals reported their happiness. This in theory has a range of 0
to 15, where 0 would mean a likely bright day with no rain, snow, or fog on any day of the
week at all and 15 would mean that all three happened on every single day of the week. This
is a measure that is visual in nature, ranging from very bright to very gloomy. For robustness,
we also collect weekly mean temperature data from the same source and control for it in some
empirical specifications. Figure 4 shows the distribution of this visual weather index.
Appendix I
Objective Calculation of Proportion of Wall Surface with Glass Windows
This appendix describes the construction of our window share variable. We follow three main
steps described in details below.
Step 1. For each of the 11 call center in our dataset, we first recover the building map from
Google Maps. This allows us to identify the number of wall pictures to be collected, along with
the relative size of each wall. If a long wall is twice as long as a short wall, we give it a weight
that is twice as large in the final wall surface measure. The number of wall pictures per call
center varies depending on the building type and whether it has walls in common with other
neighboring buildings.
Step 2. We then collect wall photos for each call center using Google Street View. In the
few cases where all walls are not fully visible with Google Street View, we can still identify
them by symmetry, as the same architectural rules apply to various sides of the same building.
There exists a large heterogeneity in building types between call centers, and hence exposure to
natural light. While the Swansea call center is located within a tall glass tower building, with
a lot of light, the Newcastle call center is located within a warehouse set-up, with almost no
windows at all. To compute the share of wall surface with windows, we use the open source
image processing software ImageJ (see https://imagej.nih.gov/ij/). ImageJ can calculate
area and pixel value statistics of user-defined selections and intensity-thresholded objects, like
the color of wall surface or windows. We first compute the pixel value of the windows within
each wall, then the pixel value of the entire wall. We take the ratio between these two measures
to obtain the share of wall surface with windows. Window pixel surface is captured in red. The
corresponding values obtained are, respectively, 10% (wall 2, Newcastle), 0% (wall 3, Newcastle),
xix
Electronic copy available at: https://ssrn.com/abstract=3470734
89% (wall 3, Swansea), and 26% (wall 3, Accrington).
Step 3. As a final step, we compute a weighted average at the call center level based on
(i) the number of walls and their respective size and (ii) the share of windows for each wall
belonging to the call center. The resulting call-center level measure of “share of wall surface
with windows” ranges from 3% (Doncaster) to 59% (Swansea), with a mean of 23% and a
standard deviation of 16%.
Appendix J
Supplementary Qualitative Data
In addition to the email survey coordinated with the firm during the study period, we collected
supplementary data from both managers and workers.
Worker Survey. We use the worker-level data largely in order to further validate our empirical
approach leveraging differential visual exposure to weather conditions. In this instance, we
designed a very short survey using Qualtrics and then recruited BT call center workers (N=318),
following innovate work done by Schneider and Harknett (2019), using targeted advertising on
social media. We use two channels. First, for LinkedIn, we use the targeting features that
allow us to advertise the survey based on users’ employer and occupation. Second, for Facebook,
we contacted the administrators of informal BT employee “groups,” some of whom posted
a link to our survey so that their members could see it. In our advertisement, we say that
“The University of Oxford’s Wellbeing Research Centre is conducting a short survey of contact
centre workers, past and present, around the UK. We would like to invite you to submit a
small amount of information regarding your time working at a contact centre. All information
is entirely anonymous. All entrants have the chance to win £100 as a thank your for your
participation.”37
Having clicked through to the survey, respondents are again told the survey will be strictly
anonymous and are given general information about the survey, their rights, how their data will
be handled, IRB approval (which was sought separately for this small survey), whom to contact
in the case of doubts or questions, and so on. Having consented to take part, they are asked
if they currently or previously work at BT. In order to be eligible for the survey, using initial
screen questions, the respondent has to be over 18 and i) either currently working for BT in a
contact center or ii) has done so in the past 5 years.
We then ask the location of the call center that the employee works at or previously worked
at, using a drop-down list of all of BT’s call centres. In addition, we ask a short series of
questions on their working environment. The wordings are as follows:
• “Are you working in an open office space (i.e. where you can easily see the rest of your
co-workers) or in a closed office space (i.e. where you are separated from your co-workers
by internal walls)? ” (potential answers: open office, closed office, other)
• “Imagine sitting at your typical workstation. Do you see few or many windows? Use the
slider below. Imagine a 10 being a completely glass office and 0 being a room with no
windows at all.” (0 to 10 scale with a slider is presented, with 0 labeled “No windows”
and 10 labeled “Full glass office.”)
• “While at work, how much natural light do you have access to from your workstation?
Use the slider below. Imagine a 10 being like seating outside while working and 0 being
an office with no access to natural light at all.” (0 to 10 scale with a slider is presented,
with 0 labeled “No natural light” and 10 labeled “Like sitting outside.”)
The survey ran from 2022-04-28 to 2022-06-20. £100 was paid to one randomly drawn participant at the end
of the survey period.
37
xx
Electronic copy available at: https://ssrn.com/abstract=3470734
In the cases where the respondent reports being a former employee, we alter the wording
accordingly such that the questions are in the past tense.
Managerial Interviews. We conducted semi-structured interviews with managers at BT.
This included interviews with a total of 16 different managers, which took place, broadly speaking, in three main stages. First, an initial round was held in 2017 prior to the launch of the
survey. The aim of these interviews was to better understand the functions of workers at BT,
understand what the firm’s main performance outcomes were, and so on. Second, a round of
interviews was held in 2018 – largely with more technical managers in charge of data who helped
to understand the nuances of the rich administrative data on worker behaviors and outcomes.
Finally, an additional set of interviews was conducted in 2021 and 2022. These interviews
focused more on eliciting additional information about the physical work environment. The
interviews included a mixture of high-level and lower-level managers from various different departments across the business. This included three broad management areas: people in charge
of health and welfare across the firm (for example, the Chief Medical Officer, Health & Wellbeing Lead, and Culture and Engagement Lead), personnel in charge of data and analytics in
contact centers (including a Performance and Insight Manager, Principal Research Scientist,
and Reporting and Analysis Manager) as well as managers running call centers (such as the
Managing Director Customer Care, HR Director of Customer Care, and Head of Customer
Insight). We also held more informal conversations (i.e. interviews without any pre-planned
questions) during site visits to the contact centers. Finally, in designing elements of the survey,
we held meetings with union representatives, though we did use these to interview them or elicit
specific information related to the study.
Appendix K
Extra Detail on Effect Size Comparisons
Oswald, Proto and Sgroi (2015): The figure we quote of a 1 SD increase of happiness leading to
29 to 35 percent more productivity (in terms of incentivized additions) is implied by the results
reported from Experiment 2. The authors measure happiness before and after viewing the
comedy (or placebo) video clip. The difference in happiness between the two groups following
the videos is 0.67 on their 1 to 7 scale. The standard deviation of this scale is 0.86 among the
control group when measured prior to the clip. The treated group do 4.15 more additions than
the control group in the raw data, over a base of 18.1 in the control group. This implies that a
one unit increase in happiness causes a 4.15/0.67 = 6.194 increase in correct additions. A one
standard deviation increase in happiness causes a 6.194×0.86 = 5.327 increase in additions. This
is equivalent to a 29.4% increase in productivity. The implied difference in additions between
treatment and control is larger (5.01) when accounting for various covariates in a regression
analysis. This would imply that a one standard deviation increase in happiness causes a 35.5%
increase in productivity.
Bloom et al. (2014): We use the replication data provided by the authors to re-run regressions
of Table 7, replacing the logged dependent variables with standardized dependent variables. The
experiment reduced negative emotions by .44 SDs and increased positive emotions by .55 SDs.
Similar effect sizes are found for evaluative satisfaction measures. Keeping the logged dependent
variables and inferring standardized effect sizes using the control group SDs provides similar
estimates.
xxi
Electronic copy available at: https://ssrn.com/abstract=3470734
High-Stakes Wall Street Professionals and Personal Values
#180001727
City, University of London
Submitted in Fulfillment of the Requirements for the Award of Masters in Organisational Psychology (MSc.)
Supervised by Paul E. Flaxman, PhD
Submitted on the 12th of September, 2019
Word Count 8,727
table of contents
abstract 5
High stakes wall street professionals
and personal values 5
Literature Review 6
What is acceptance and commitment therapy? 6
personal values- a historic
component to happiness and well-being 7
Previous Research of Values in Accordance
with Act……………………………………………………………….10
Personal values and Reflexivity in light of
foucauldian discourse analysis 11
methods 12
Design 12
participants and common wall street
vernacular 13
measures 15
procedure 16
results and discussion 17
participant descriptions of honesty
amidst wall street dishonesty and
introductory summary of table 2 17
discursive statements describing wall
street’s objective dishonesty 19
discursive constructions of functions
of honestly from differing “seats” 20
theoretical interpretations of
the subjectivity of “trading seats”
amidst wall street’s dishonesty
underpinned by its profitability 22
wall street’s power of profitability 24
wall street’s descriptions of values
relating to challenge and
introductory summary of table 3 25
all participants objectively value the challenges
around hard word while senior
traders objectively value resilience and
fear of failure 27
object position of hard work 27
object position of resilience and fear of failure
for longevity 27
transcript discourse examples of commonly
held values around hard work in senior
trader examples of values of resilience & fear of
failure 28
traders’ discursive statements supporting the values
of hard work 28
senior traders’ and pms’ discursive statements around
the values of resilience and fear of failure 29
theoretical interpretations of the overriding power implications
and subjective positional shifts
for more senior traders seeking
career longevity 30
wall street’s power of profitability 32
additional practical and theoretical implications
of this qualitative research 32
limitations 33
conclusion and future directions 34
appendices 38
appendix a 38
appendix b 40
appendix c 44
appendix d 46
blog 47
list of tables
table 1 participants background information of wall
street professionals 13
table 2 fda analysis of dishonesty on wall street 19
table 3 fda analysis of challenge on wall street 26
Abstract
High stakes professionals, especially Wall Street traders, are often a population deemed to be unworthy of sympathy primarily because of the media’s betrayal of its actors as depraved and entitled. However, Wall Street professionals are normal human beings just like you and me, but their daily work pressures to “turn a profit” are not for the faint of heart, and it appears that they are a population that is continuously over-stressed and in need of strategies to improve their overall well being. Thus, a short introductory session of ACT to such professionals, and its primary mission to cultivate both mindfulness and values based actions appears timely. The current study investigated what six Wall Street traders value most in their lives, and actions undertaken to move towards those of high priority and away from those of low priority. Participants were interviewed one month following a half-day ACT workshop, and a unique qualitative method, Foucauldian Discourse Analysis, was undertaken to analyze the data. The transcript discourse seems to indicate that participants share common values related to honesty and challenges around hard work and longevity of career success. These common values are moderated by different job roles, tenures, and experiences and underpinned by Wall Street’s overarching power of profitability. Furthermore, the research highlights what appears to be a universal yearning for values based living.
High-Stakes Wall Street Professionals and Personal Values
What drives high stakes Wall Street professionals and how do they navigate the emotional ups and downs of the stock markets, the lack of transparency which permeates the industry, and the unending expectation of profitability without losing site of their personal values? One of the most successful billionaire hedge fund managers, Ray Dalio, in his best selling novel, Principles (2017), professes that daily meditation and focus upon one’s core principles are the necessary ingredients for personal and career success (Fabel, 2018; Dalio, 2019). World renown clinical psychologist Jordan Peterson’s, 12 Rules for Life (2018), also advances the idea that happiness is only attainable when individuals pursue what is truly meaningful and not expedient (2018). Wall Street professionals are faced with acute stress due to constant market changes, and thereby need strategies to re-ignite and balance their own personal values. Thus, it seems like an opportune time to introduce these high stakes finance professionals to Acceptance and Commitment Therapy (ACT). ACT is a modern, mindfulness-rooted, and research supported training technique. ACT helps individuals more successfully “carry” their human perplexities and sufferings while still remaining focused upon values-based living.
Literature Review ok
What is Acceptance and Commitment Therapy?
ACT was first developed in the late 1990s by Hayes, Barnes-Holmes, and Roche (2001) to treat various mental health conditions with the goal of teaching individuals how to shift the way they may think and/or feel about emotional pain and suffering in order for them to live healthier, happier, and fuller lives. It is a model born out of contextual behavioral sciences, and unlike its more traditional counterpart, Cognitive Behavioural Therapy (CBT), ACT fosters both mindfulness and acceptance in order for its participants to successfully pursue values-based lives (Flaxman et al., 2013). ACT’s key message is that when there is a “pouring together” or an “entanglement” of a person with his/her negative thoughts and feelings, and he/she, in turn, begins to experientially avoid these feelings, it often creates toxicity (Flaxman, et al., 2013). This ACT process of exposure to negative thoughts and feelings and disentanglement involves “psychological flexibility” (Flaxman et al., 2013). In order to be “psychologically flexible”, an individual must fully contact the present moment, the thoughts and feelings it contains so that he/she can persist or change behaviors in pursuance of values-based living (Hayes et al., 2016).
ACT’s workplace intervention model for “psychological flexibility” is expressed in a six sided, interactive hexagon, i.e., the Hexa-Flex, and each side represents one of the following processes: contact with the present moment, self as context, acceptance, defusion, personal values, and committed action (Flaxman et al., 2013). This model requires participants to use the latter mentioned to help isolate values-based goals and committed actions (Flaxman et al., 2013). One scholar, Harris (2019) has further simplified the Hexa-Flex process from its six core principles to the ACT Tri-Flex model whereby an individual must be present, open up, and “do what matters” in order to be “psychologically flexible”. Flaxman and colleagues (2013) describe in their ACT training manual for improving well-being and performance in the workplace that ACT’s six core procedure is essentially designed to target two main areas — 1) mindfulness and 2) values-based action. In an attempt to begin unraveling “psychological flexibility” among high stakes Wall Street professionals, this dissertation will explore only a portion of one of the two workplace, target areas — personal values.
Personal Values —A Historic Component to Happiness and Well-Being
Many psychological treatments hold personal values to be central to living productive and vital lives. ACT is considered to be a modern psychotherapy model which builds upon many other values-based psychology theories, such as: the client-centered approach of Carl Rogers, B.F. Skinner’s “radical behaviorism”, and Martin Seligman’s positive psychology (Yadavaia & Hayes, 2009).
According to Carl Rogers, individuals have the urge to expand, develop and mature — “to become [their] potentialities” or “self actualise” (Rogers ,1964). However, this self-actualisation process is often difficult because what they value is often buried beneath deep layers of facades, living to please others, and striving to meet external, moral standards (Rogers, 1964). Rogers (1964) describes the self-actualisation or client-centered therapy process to be one of “unconditional positive regard”. Unconditional positive regard is simply defined as accepting and supporting another exactly as they are, and it draws a distinction between “operative values” (i.e. infant perceptions are created in the present moment with each new experience) and “conceived values” (i.e. as we grow older our values become more rigid, inefficient, and influenced by the judgment of others) (Rogers, 1964). Client-centered therapy does not require the client to abandon conceived values, but it encourages the client to continually test and inform him or herself against everyday experiences so that values become more fluid and flexible (Rogers, 1964). Essentially, adjusting one’s behaviour based upon feedback from the environment allows individuals to live authentically (Rogers, 1964).
Similar to Rogers, Skinner (1971) associates values with operant behaviour and with pursuing what is good, i.e. “positive reinforcers”. Skinner (1971) believes that according to his notion of “radical behaviorism”, values are the reinforcing effects of consequences, and these behaviors or values can be done either for the good of others or for the good of oneself (Yadavaia & Hayes, 2009). Additionally, Martin Seligman (2017) is considered to be the father of positive psychology and like Rogers, he believes in the idea of the “self-actualisation” of potential, as well as in “self-determination theory” whereby people intrinsically move towards motivation and autonomy. However, he supplants unconditional positive regard with mindfulness techniques and activities which identify and enhance signature strengths, i.e. values. (Seligman, 2002).
ACT also works well along side or in conjunction with Shalom Schwartz’s circumplex of values, illustrated below (Schwartz, 2012). He asserts that there are ten universal and cross cultural values that all human beings possess, such as self direction, benevolence, hedonism, achievement, security, etc (Potts, 2015; Schwartz, 2012). Schwartz’s (2012) compilation of universal values form a circular structure and reflect the motivations that each value expresses. They sit closely along side one another in the circumplex to form a continuum of motivational similarities and dissimilarities which are simultaneously congruent and conflicting across two axes —Openness to Change versus Conservation and Self-Transcendence versus Self-Enhancement (Potts, 2015; Schwartz, 2015). Based upon the opponent structure of the axes, the values which are opposite to each other compete for priority in individuals’ lives (Schwartz, 2012). In order to create this circumplex, Schwartz (1994) studied values from samples of 30,000 public school teachers, university students, and working adults from every continent across the world.
Previous Research of Values in Accordance with ACT
There exists a substantial body of quantitative literature exemplifying values-based living to be the central component to ACT, and in a recent systematic review Reilly and colleagues (2019) affirmed this notion when they reviewed the most psychometrically sound and appropriate measures to assess values. They describe an important distinction between values and goals, such that goals can be completed and achieved but values serve as guiding principles and reflections of what an individual finds to be meaningful (Reilly, et al., 2019).
In an effort to explore values, ACT also employs experiential exercises amidst different domains of life, such as: marriage, family, community, physical fitness, diet, arts, literature, etc. (Baer, 2015). These exercises are usually done through a Valued Living Questionnaire, values cards, and/or a semi-structured interview process whereby individuals self-rate importance of each value domain and their committed actions in each area (Baer, 2015). This is process by which participants can identify and re-direct energy “towards” areas of high priority and “away” from areas of low priority (Baer, 2015). Additional mindful activities include individuals writing their own tombstone epitaphs or a birthday speech that a friend or co-worker would give about them in order to capture how they would like to be remembered (Baer, 2015). Following these mindful exercises, ACT therapists engage the participants in thoughtful discussions regarding behaviour modifications (Baer, 2015).
Recent qualitative research investigated how 16 working adults articulate, change, and increase value congruent behaviour following a five session values clarification and congruence workshop with faculty and staff of a large metropolitan university (Fitzpatrick et al., 2016). The training was guided by both ACT’s values-based model and Shalom Schwartz’s value circumplex (Fitzpatrick et al., 2016; Schwartz, 1992). Following the workshop, the participants were interviewed regarding the process of articulating their values, changing their values, and increasing value-congruent behaviour (Fitzpatrick et al., 2016). After a thorough thematic analysis was conducted, their qualitative findings were as follows: 1) facing contextual challenges makes values clarification and resulting behaviours pertinent, 2) contextual challenges do not need to be traumatic for socialisation, exploration, and/or activation of values to occur, 3) focused attention is needed for congruent behavioural actions to take place, 4) cognitive activation or re-perceiving of values is necessary, 5) inspiration to make change or activate existing values is necessary, and 6) it’s helpful and encouraging to have a workshop partner to share and articulate values and committed actions (Fitzpatrick et al., 2016; King & Hicks, 2009; Shakespeare-Finch & Lurie-Beck, 2014; Shapiro, Carlson, Astin, & Freedman, 2006; Mendelsohn, Pine, & Schiller, 2014; Martin, Garske, & Davis, 2000).
Personal Values And Reflexivity in Light of Foucauldian Discourse Analysis
Similar to the above qualitative study, this dissertation also explores values, but instead of undergoing a thematic analysis, this dissertation will interpret the qualitative data in light of Foucauldian discourse analysis (FDA). FDA was born out of the philosophical work of Michael Foucault (Ussher & Perz, 2018). It is an innovative technique for interpretation because it assumes that the researcher is a social constructivist who seeks to uncover and deconstruct meaning from discourse and not just seek out causal connections or common themes from language (Willig, 2013). Willig (2013) explains that FDA is employed in order to find out “what characterises the discursive worlds people inhabit and what are their implications for possible ways of being” (p. 139). Thus, in light of FDA analysis, this dissertation will reflect upon the personal values which form the object positions chosen among semi-structured interviews with Wall Street portfolio managers, traders and analysts according to the following research question: What do Wall Street professionals value and how do they maintain focus on these personal values at home and at work?
Methodology
Design
This dissertation will be a qualitative examination of research data obtained through semi-structured interviews conducted one month following a half-day ACT workshop with 15 Wall Street investment bankers, portfolio managers, traders, analysts, and brokers. An organisational psychologist and trained ACT therapist delivered a training workshop entitled Cultivating Psychological Flexibility for Finance Professionals on Saturday morning the 15th of June, 2019 at the Belmond Cadogan Hotel in Chelsea, London. The morning workshop included the scientific evidence behind psychological flexibility in accordance with ACT, an introduction to ACT’s skills model and perspective, and an interactive exploration of the identification and pursuit of personal values (primarily worked with a deck of cards and each card was ascribed a particular value). Ten volunteers from the workshop participated in semi-structured interviews ranging between 25 to 40 minutes regarding personal values, and this pool of participants was narrowed to include only six trading professionals with ten or more years of Wall Street experience (narrowing process discussed below).
Participants & Common Wall Street Vernacular
Table 1, below, depicts the participants that both attended the ACT workshop and volunteered to be interviewed (see Table 1 below).
Pseudonym
Gender
Length of Tenure
“Seat” on Wall Street
Robert
Male
10 months
Back Office Investment Banking
Clemente
Male
2 1/2 years
Junior Portfolio Manager/Trader for Investment Bank
Francesca
Female
15 years
Investment Banker
Anthony
Male
17 years
Stock Broker
Tom*
Male
15 years
Head Trading Manager for Hedge Fund
Nathan*
Male
10 years
Analyst
Paul*
Male
16 years
Portfolio Manager/Trader for Hedge Fund
David*
Male
15 years
Portfolio Manager for Investment Bank
Louis*
Male
15 years
Portfolio Manager for Investment Bank
Christian*
Male
20 years
Global Macro Head/Senior Portfolio Manager for Hedge Fund
Table 1 Participant Background Information of Wall Street Professionals
* interviews transcribed and included in final sample for FDA
The above table also illuminates the varying jobs (“seats”) that exist amidst Wall Street professionals. Like any other group of professionals, Wall Street, commonly referred to as the “Street”, has multiple languages unto itself, but they all boil down to one meaning—the language of money. The language of money spoken on the “Street” is filled with many different “tribes”, such as traders, analysts, portfolio managers (PMs), investment bankers, and stock brokers, and each particular “tribe” uses unique words and phrases (Lopez, 2014). After initial review of the ten verbatim interview transcripts, it became apparent that, like the “Street”, the participants can primarily be divided into the “buy side” and the “sell side”. The “buy side” are the traders, often referred to as the “alphas”, who make large bets on whether stocks rise or fall while the “sell side” are the bank brokers who “wine and dine” the traders in order to sell them stock tips, and, finally, the investment bankers who finance and leverage the traders’ “bets”. The researcher has chosen to analyse only the transcripts of the PMs, traders, and analysts (ie. the “buy side”). Also, the participant pool is further narrowed to include only those with ten or more years of work experience for both consistency and richness. Furthermore, in conjunction with Table 1 (above), and for even greater clarity it’s important for the reader to understand the typical space from which the trading business is conducted. For example PMs, analysts, and traders all work alongside one another on a trading floor. A trading floor is a literal floor in a building where traders, i.e. participant Tom, buy and sell securities (futures, options, commodities, foreign exchange) on behalf of their clients, or on behalf of the financial firm or PM, i.e. participant Paul, who employs them. On the floor itself, it looks like a large gymnasium with rows of desks, each one adorned with multiple, blinking screens separated by groups or teams that trade similar instruments or employ similar strategies. Also, PMs control the “book” which means the particular securities, under their purview, which are bought and sold with the help of their research analysts, i.e. participant Nathan, and on behalf of the firm’s clients. Additionally it’s important to understand that there is a pecking order among the PMs whereby junior PMs are learning and training, and senior PMs are individuals who have shown promise and are beginning to trade larger dollar amounts or “size”, as they call it, and have established a proven track record usually spanning many years and often managing billions of dollars. Furthermore, the most prominent acronym that runs through all of the transcript data of the PMs, analysts, and traders is PNL—Profit and Loss, i.e. how much money finance professionals are up or down in the stock markets. Also, as described above regarding different job roles on the “buy side”, both the “Street” and this dissertation will often refer to all six participants, commonly, as “traders.”
Measures
Fifteen participants were recruited to the ACT workshop via word of mouth or by email invitation (see Appendix A), and were given participant information sheets upon arrival (see Appendix B). Following the session, the ten participants who volunteered to participate in the research were given consent forms (see Appendix C) to sign before interviews were scheduled. All interviews were conducted over a one-week time period and one month following the workshop. All participants were interviewed at their particular places of business and in private conference rooms which bordered the trading floors. The interviews were semi-structured and included three main questions with prompts and extemporaneous follow-up questions to follow (see Appendix D). Following the pilot interview, the researcher decided to add a question which requested participants to give their core set of values because it appeared to help them articulate their individualised definitions of personal value.
Procedure
The qualitative data obtained for this dissertation was recorded and transcribed and after a thorough review of the verbatim transcripts, two major areas of discourse were chosen for FDA. FDA was adapted from the work of post-structuralist philosopher and historian, Michael Foucault, whereby he asserted that discourse or language are bodies of knowledge which, in turn, create social institutions (Holloway, 1997). FDA presupposes that language should be investigated because it does not reflect reality in a transparent manner (Fairclough, 1992;Willig, 2013). Thus, the researcher must adopt a relativist ontology (reality is based upon interpretation of human experiences) and a social constructivist epistemology whereby he/she seeks to uncover both the social and psychological interpretative meanings which surround language or discourse (Willig, 2013). Furthermore, Foucault’s philosophy and FDA also consider the links between discourse and the domination and subordination that powerful social institutions have over certain segments of society (Seale, 1998). The current interpretive analysis undertaken is based upon a four step, conflated version of Willig’s (2013), widely used, six step process for FDA. The conflated version of Willig’s FDA process that will be used for this dissertation is as follows: 1) isolation of the common object, discursive positions from the transcript data, 2) isolation of the discursive transcript statements supporting the object positions, 3) juxtaposition of the varying work/life experiences or functions of the traders in their differing “seats” or job roles , and 4) a theoretical interpretation of the discursive statements in light of their subjectivity which is underpinned by the veil of Wall Street power and control (See Tables 2 & 3 below). Also, the results and the discussion will be combined because isolating the data from its interpretation does not lend itself to effective FDA (Ussher & Perz, 2018).
Results and Discussion
Participant Definitions of Personal Values All of the interviews begin by requesting each participant to define personal values, and all six appear to use similar language in doing so, such as: “the underlying drivers behind actions”, “how I operate on a daily basis”, “what I do and how I go about doing it.” In addition to espousing similar language in defining personal values, the following are the two main subjects of discourse which dominate all six transcripts and serve as the basis to the following two object, discursive positions: 1) Wall Street is Dishonest Amidst Personally Valuing Honesty, and 2) the Challenges associated with working on Wall Street which will be bifurcated into two separate discursive, object positions—(a) the Challenge of Hard Work and (b) the Challenge of Resilience and Fear of Failure for Career Longevity. These object positions will be interpreted, analysed, and discussed in accordance with a Four Step conflated version of Willig’s six step FDA analysis (See Tables 2 & 3 below). Also, per space limitations of this dissertation, theoretical interpretations of power and subjective positions from the participants’ particular trading “seats” and their different tenures on Wall Street will be analysed together, i.e. steps three and four of the interpretive process illustrated in Tables 2 & 3 below.
Participant Descriptions of Honesty Amidst Wall Street Dishonesty and Introductory Summary of Table 2
All participants included personal honesty as a primary value and seemed to discursively position themselves with similar definitions. For example, Tom says that honesty is “doing the right thing” while Louis believes that “if you see that something is wrong, you should actually go on and say that’s it’s wrong”. Also, Nathan strongly professed that “if you can tell someone the kind thing or tell them the honest thing—I always lean towards the honest thing”, and Christian, a senior Wall Street PM, speaking from a more managerial perspective says “being disingenuous…I don’t think that’s the right thing”. Despite personally valuing honesty and transparency, participant transcripts appear to reveal a discursive object position of the dishonesty which permeates Wall Street. However, their individual, subject positions (feelings and/or experiences) and/or functions of operating amidst this dishonesty differ, but all participants do feel subject to Wall Street’s controlling practice or “power of profitability.”
Table 2 FDA Analysis of Dishonesty on Wall Street
1) Object Construction/Position
Senior Traders Value Personal Honesty Amidst a Dishonest Wall Street
Junior Traders Value Personal Honesty Amidst a Dishonest
Wall Street
2) Discursive Examples of
Personal Values of
Honesty Amidst Wall
Street Dishonesty
… people in our industry aren’t as honest or are operating under an ulterior motive
… but being honest and transparent may effect them…it may effect their success
I grew up in a
time where
banking was going
through an
integrity switch
3) Discourse Summaries of the Differing Functions/Job Positions
Senior traders appear to maneuver around dishonesty to achieve success
Junior analyst appears to naively believe “buy-side” co-workers are honest and/or junior PM appears to refuse finding a balance of industry dishonesty with personal honesty to climb corporate “totem”
4) Subjectivity & Practice/Power Implications
Wall Street profitability
Wall Street profitability
Discursive Statements Describing Wall Street’s Objective Dishonesty
The following are examples of two of the participants’ discursive constructions of the dishonesty that pervades Wall Street and appear to represent how the participants still attempt to remain transparent themselves. Tom says:
I think a lot of people in our industry aren’t as honest or are operating under an ulterior motive …So people I manage they know very well the reason I’m asking them to do it, which I’ll usually explain with it. But look if you’re managing a larger business you may not be able to be as transparent with what’s going on.
David appears to concur with the following discourse:
You want to be honest and transparent, but you know the person in front of you will never apply honesty and transparency….I’ve been proven wrong so many times… I remain speechless. They may want to be on a personal level, but being honest and transparent may effect them…it may effect their success.
Discursive Constructions or Functions of Honesty from Differing “Seats”
Participant differences in discursive constructions in how they subjectively manage dishonesty on Wall Street appear to be based upon their job functions or “seats”. The following discursive constructions illustrate how senior traders and PMs have learned to navigate and still achieve success around Wall Street’s dishonesty while a more junior analyst and PM appear either naive to the perils of Wall Street’s dishonesty or unwilling to make adjustments in order to achieve more workplace success. For example, senior trader, Tom, seems disappointed when discussing Wall Street’s dishonesty, but the following discourse seems to explain his acceptance or rationalization in order to navigate around the dishonesty:
You could say it’s an easy way to…move a metric around or move a goal post around and somebody that can just do it from either a position of greater power…or you could also say that it’s something that may come about for somebody else’s interests…Yeah, I mean look just because someone’s not transparent it doesn’t mean they’re dishonest either, but, no, a lot easier to manage.
The most Senior PM, Christian, appears to reflect upon the dilemmas he’s often faced
with in his functional “seat”, oftentimes managing billions of dollars, with pressure to take action or dishonestly manipulate, i.e. terminate/sacrifice junior PMs or peers, for greater personal wealth and success in his own career. Christian says “I think it’s pretty clear in my case, I think I would be more successful in my setting if I was a bit more manipulative and less honest with my employees.” Christian then responded to follow up questions regarding whether he could put a number or percentage on how many firings or other workplace actions were taken from a personally honest and genuine place or on behalf of a superior for other, possibly nefarious reasons, and he said:
…but if just off the top of my head or the seat of the pants…. probably 40-50 percent…and the others I was instructed to do it so or carry it out…Yeah, but I could have been 3X, probably, if I’d been more willing to sacrifice others in certain cases…I don’t think you can really win to that behavior long term….And look the best thing that I could do right now is fire a guy or two, but I think for me, particularly where I am now and knowing what I know, like I’m not going to sacrifice that for “ABC hedge fund founder”.
In juxtaposition to Tom and Christian, more junior analyst, Nathan, and PM, Louis,
subjectively see things differently from their “seats”. For example, Nathan appears to believe that
he entered Wall Street at a time when more honesty exists on the “buy side” than the “sell side”
or, as he says “the pure investment side” of the business. Nathan joined the “Street” immediately
following the world stock market crises of 2008 when some of the oldest and most esteemed US
Investment Banks closed their doors forever because of dishonesty and corruption. Thus, after a
short tenure at one of Wall Street’s largest investment banks, he accepted a job as an analyst at a
competitive “buy side” hedge fund. Nathan appears to reflect on this job transition when he says:
So when I was working at a bank…I always wanted to face the most sophisticated type of client because I felt like that’s where…the relationship is…the most clean, because I thought that people are dealing on more level footing right at that point. And I guess I grew up in a time where you know like banking was going through that kind of integrity switch, if you like.
Nathan’s discursive statements appear to imply a naivety or an innocence to the similar perils of
the “buy” and “sell” side observed by the other five participants. However, in stark contrast to
Nathan’s hopeful discursive statements, and unlike Tom and Christian’s ability to maneuver
amidst Wall Street’s dishonesty, Louis seems steadfast in his views regarding refusing to
succumb to the dishonesty that appears to pervades Wall Street. It seems that his absoluteness
regarding honesty and integrity may not allow him to achieve longevity or additional
promotions and stature in the business. Louis says:
What’s interesting about any organisation is that you assume that they’re meritocratic based, and you assume that being like hard working and good at what you do and ethical …and things like that. But you soon realise…that’s just not reality. To get to the top of the totem pole, all the guys at the top are…just aren’t that.
When Louis was asked if he has or would alter any of his behaviors in the future in order to
climb the Wall Street ladder, he says:
Well that’s the thing I should, but I won’t. I’m probably happy being somewhere
lower down the totem and sticking to my values instead of changing them…and going the extra bit…I would say that honesty and transparency is not particularly valued. And I think…it’s about just perpetuating a narrative that you think… it’s sales basically and exaggerating the things you’ve done well…and not kind of highlighting the things that weren’t done well.
This sort of willing resignation that appears in Louis’ discursive statements can be likened to
Skinner’s (1971) theory of “radical behaviourism” whereby Leo’s “operant” behaviours seem to
align more with the good of others than for the good of himself, by refusing to go the “extra bit”
it appears that his colleagues will likely far surpass him in their career trajectories.
Theoretical Interpretations of the Subjectivity of “Trading Seats” Amidst Wall Street’s Dishonesty Underpinned by its “Power of Profitability”
All participants appear to understand the inherent nature of dishonesty that permeates Wall Street, however, their subjective interpretations of how they maintain or balance this against their shared value of personal honesty varies, and perhaps can be best interpreted in light of Shalom Schwartz’s value circumplex and Carl Roger’s notion of the “fluidity” of personal vales (Potts, 2015; Rogers, 1964). Similar to Schwarzt’s (2012) notion that values along the circumflex both compliment and compete with one another for space in individuals’ lives, Roger’s (1964) theory of “unconditional positive regard” encourages individuals to forgive themselves for engaging in too much “conceived” judgement and, instead, individuals must balance these competing values in order to become their authentic selves.
As further illustrated in Schwartz’s (2012) value circumplex and in light of the current data transcripts, the pursuit of personal honesty on Wall Street with colleagues and subordinates, i.e. Self-Transcendence/ benevolence axis, conflicts or competes with its opposing axis— the pursuit of Self-Enhancement/personal achievement. This conflict may require traders to sacrifice others’ careers or make difficult workplace decisions in order to achieve power and monetary success on Wall Street (Potts, 2015). However, Christian appears to believe that amidst his success he still manages to balance a high level of benevolence. He says:
You know I make sure I give feedback very regularly. That’s more kind of good manager things, but I think I treat people with respect. I take an interest in their careers. I really do try to make them successful, and I think people feel that, and I think they respect that.
Alternatively, for Louis, it appears that he has made a conscious choice that he will not be able to climb the corporate “totem”, as he phrases it, because he is firmly rooted in Schwartz’s Self Transcendence/Universalism values axis, i.e. social equality in the workplace, whereby he appears almost resigned about competing for wealth and Self-Enhancement/achievement because he believes the environment is too disingenuous. For example, Louis says:
But I think what’s really interesting is, I think if you’re really…a bluffer early on in the career, you learn you have to bluff to survive. And so you become really good at developing those bluff or sales skills. And so you sharpen those and you really move up the ladder. And the people that are really good at actually doing their job never get to develop those skills, at all. So inevitably the really good bluffers will float, and keep floating because they’ve already developed those skills at an early age.
When follow up questions are asked of Louis on whether he’s willing to change some of
his behaviours in order to increase his success and profitability, Louis responds with the
following discursive statements:
…it’s like this is just how human beings…behave and it’s just reality, it’s not something to be depressed or sad about, it’s just this is how it works and you either get on the train or not.
Wall Street’s power of profitability Finally, unlike ACT’s values cards (used with the participants in the ACT workshop) which do not include a card for Power or Profitability—Schwartz’s circumplex includes power/authority and wealth, as part of the Self-Enhancement quadrant opposing the axis of Universalism. This appears to reflect or mirror the power aspect of FDA whereby traders are all beholden to the veil or supreme power of Wall Street’s profitability. Thus, in an effort to remain balanced maybe those traders who maintain a middle ground or a more evolved and “fluid” understanding fare best on Wall Street. The transcript data appears to indicate that they can treat their colleagues and subordinates with as much transparency and benevolence as the industry allows, but profitability of the “book” is supremely important. As the senior PM with the longest career of the participants, Christian, reflects on the values’ card exercise that they completed at the ACT workshop, he appears to have established a Carl Roger’s (1964) type of “fluidity” or a, sort of , experienced form of evolution and/or authenticity with his values when he says:
I would love to see you say, we’ll sort these same cards by what you think your boss values rather than what you aspire to be. Like because that I think is where the disconnect resides in a lot of cases, and that’s what makes my job difficult. Because ABC hedge fund founder would sort those cards much differently for me then I would sort them for me. Because he’s willing to live…with a different set of guiding principles which is more driven by just…PNL.
Thus, the aforementioned discourse represents how the subjectivity of our participants “seats”
differ, but unless a trader’s values become more “fluid” or evolve, they will likely have a
difficult time advancing their careers and finding an authentic balance of values as illustrated in
Schwartz’s (2012) circumplex.
Wall Street’s Descriptions of Values relating to Challenge and Introductory Summary of Table 3
The last question of the semi-structured interviews, and the prompts to follow, were whether the participants could describe any strategies that they have used since the workshop, or in the past, to help them stay more aware of their personal values. Also, if they could give specific examples of difficult or challenging times when these particular values have guided them—both in times of striving to achieve, persevering in difficult times, and even times of overwhelming success. All participants appear to discursively espouse similar values necessary to meet the challenges which surround employment on Wall Street, such as hard work, ambition, discipline, perseverance, resilience, and self-development. For example, when Paul reflects upon the traders he looks to hire, he says it’s “the same type of person who probably do share my values in terms of work, in terms of perseverance, in terms of focus, etc”. David echos similar beliefs when he reflects upon what he values in co-workers which is “the strength and determination to sort of overcome difficulties in life.”
Despite all participants valuing the challenges associated with working on Wall Street, the specific challenges chosen from the transcripts appear to align under two separate discursive, object positions—(a) the Challenge of Hard Work and (b) the Challenge of Resilience and Fear of Failure for Longevity of Success. The individual, subjective positions (feelings and/or experiences) surrounding the challenges of working hard on Wall Street appear to be similar among both junior and senior Wall Street participants, but as traders become more senior or more experienced, achieve more success, and live through the emotional ups and downs of the volatile, financial markets, their subjective positions seem to “fluidly” evolve from an operational state of working hard to achieve to more of an operational state of longevity hinging upon a fear of failure. However, like with the discursive positions of honesty under the veil of Wall Street’s power of profitability (discussed above), both discursive positions of challenge are similarly subjected to Wall Street’s language of money or the power of PNL.
Table 3 FDA Analysis of Challenge on Wall Street
a
b
1) Object Construction/Positions for Challenge
Challenges around Hard Work
Challenges around Resilience and Fear of Failure for Longevity
2) Discursive Phrases and examples of Personal Values around the Challenge of being Wall Street Traders
…because I value hard work. I value, you know, doing the hard thing even if it’s not necessarily the easy thing
…well it helps actually if you think it is luck because then it’s like okay you know it’s reminding me to maintain focus, maintain your values
3) Discursive summaries of Functions/Different Job Positions
Pure ambition, hard work, & self -development to succeed on Wall Street
More life experiences and market downturns appear to create a “fluidity” of values whereby traders operate with resilience, innovation and a fear of failure
4) Subjectivity & Practice/Power Implications
PNL/Language of Money
PNL/Language of Money
All Participants Objectively Value the Challenges Around Hard Work While Senior Traders Evolve to Objectively Value Resilience and Fear of Failure
Object position of hard work After defining personal values in the opening interview question, Paul offers the following discursive statements regarding Stanford psychologist, Kelly McGonigal’s book, The Upside of Stress (2015), which he read six months prior to attending the ACT workshop. Paul appears to explain, with the following discursive statements, that McGonigal emphasises pursuing your values, with physical reminders, as a way to create a mindset of embracing life’s challenges and/or stressors, i.e. through the challenge pursuit of hard work:
You can look at that {Paul hands me a leather and white gold bracelet that he’s wearing with the inscription—Remember Your Values—and we both softly chuckle when we realise the irony that he had no idea that my interview would be about how Wall Street traders focus on their values}…it helps you to contextualize the stress you’re seeing in the workplace…because essentially when you contextualize why you’re doing something …Well I’m stressed because I care about work, because I value hard work…even if it’s not necessarily the easy thing…this exact book is about…generating the challenge response rather than the fight or flight response.
Object position of resilience and fear of failure for longevity As traders become more senior, participant discourse seems to indicate that never ending resiliency and fear of failure is what promotes continued success and career longevity. For example, David appears to explain that it is the failures and disappointments which provide for resilience and offer the best learning experiences in life:
and then I promise you, you will not remember the day you made two million a day…but you will remember the day you lost two million…perseverance again. So, realizing that you just need to keep going…and you may need to take two steps back to make two forward later on. You don’t let whatever happen take you down.
Furthermore, when times of great trading success do occur, senior traders appear to continually remind themselves that the majority of it comes down to luck while the remaining portion is their good decision making. More senior PM, Paul says that “ it helps actually if you think it is luck because then it’s like okay you know it’s reminding me to maintain focus, maintain your values.”
Transcript Discourse Examples of Commonly Held Values Around Hard Work and Senior Trader Examples of Values of Resilience & Fear of Failure
Traders’ discursive statements supporting the values of hard work Paul appears to further suggest in the following discursive statements that he is often able to avoid the “the fight or flight” hormonal response created in high stress trading environments when he looks at the physical reminder, his bracelet, with the Remember your Values inscription. This appears to inspire him to work harder. Paul says;
Normally bad trades or yeah mistakes…And so whenever I feel that kind of…. stress response physically…kind of manifesting itself…. Grind my teeth and that sort of stuff…and also you’re a bit more jacked up, you know in terms of cortisol and whatever. Then, I do actually help by just taking a second and looking at this {Paul points to his bracelet} and saying ok…this is now a challenge.
Junior analyst, Nathan, seems to agree when he says that “being technical or like grounding yourself in real work” is the ultimate challenge and should be your anchor, and he elaborates further when he says:
…look our job here is to make money in the same way that you know someone you know in a factory you make widgets. So that’s kind of you know did you have a good day and make more widgets to have a bad day and make less…And there’s two ways you can go about that. One is not by letting your emotions affect your decisions and the other is just by reducing the volatility of your emotions.
In addition to anchoring themselves in the process of of hard work, the participants also appear to commonly agree that in order to achieve success on Wall Street there is a high degree of challenge to continually self-develop, remain disciplined, and to stay focused. For example, Tom appears to believe that keeping a strong body and strong mind in and outside of work is necessary in order to achieve success on Wall Street when he says:
So all that to me aligns to say that if you’re not really taking care of yourself that well a lot of things will fall to the wayside.…you’re not working out, you’re out late, you’re eating unhealthy, and then at the same time you’re trying to prepare yourself for the following week which is going to be of greater stress. So while that happens you’re basically kind of falling down on your own benchmark….you end up operating from a period of kind of physical and mental weakness.
Also, Nathan recalls some steps he has taken in both his personal and work life following working with the values’ cards at the ACT workshop. He seems to portray the sense of importance necessary for continual self-development and focus in the following discursive statements:
But you know kind of on a weekly basis what am I going to do to make sure that I’m moving towards the two or three things that I want to achieve from a technical perspective over the next three to six months…So, one of the things that I want to learn is a programming language in more detail, and I’d already started the process.
Senior traders’ and pms’ discursive statements around the values of resilience and fear of failure In addition to the aforementioned values shared by all participants, as senior traders and PMs gain more experience, trade more “size” (larger trades), trade more sophisticated instruments, and live through several “down period” stock markets, it appears that their strivings to achieve success in the markets remain the same. However, their values of resilience and fear of failure appear to “fluidly” develop and more discursively define how they achieve longevity on Wall Street. For example, Paul appears to discursively discuss the challenges of losing money, persevering, and the never ending battle to avoid attaching one self ’s worth to PNL. He says:
Like not shying away from a challenge… when things are getting horrible sometimes you want to do the ostrich approach and stick your head in the sand… when you are losing money, it’s…sometimes a struggle because you know traders …tend to kind of attach…their sense of self confidence or self-worth to their P &L.
Also, the most senior and experienced PM, Christian, echoes this same notion where he appears to imply that PNL’s reigning power is always looming because traders are payed very little in base salaries, and they make all their money via commissions related to the success of their “books” or portfolios. Thus, Christian says:
look most of these firms are managed in a structure where people are always feeling insecure about their position because these bosses feel like that’s how they get the most productivity out of employees. So it’s all designed around creating insecurity to try to drive people harder. Which is a hard thing because you realize geez, I’m 32 and I just had this amazing year but I could get fired tomorrow, right. So…there’s a very hard component of eat what you kill in this business…
A follow up question was asked to Christian regarding whether he believes that the most
successful hedge fund founders, like his boss, live with this same fear and he said that he believes that they do because “…he’s an innovator, he’s got the fear of failure”.
Theoretical Interpretations of the Overriding Power Implications and Subjective Positional Shifts For More Senior Traders Seeking Career Longevity
According to the above interpretive analysis of the participant transcripts, there appears to be a “fluidity” shift or evolution of values from a young traders mindset or subjective position/functional “seat” on Wall Street to a more senior mindset with respect to values of fearing failure and resilience to keep innovating in order to create longevity. For example, when examining this “fluidity” shift, according to Schwartz’s value circumflex above, the younger, less experienced traders appear to remain in the quadrant of Self -Enhancement, as well as in the adjoining quadrant of Openness to Change (i.e self developing) while continuing to balance the benevolence/equality axis (Schwartz, 2012; Rogers, 1964). However, as traders become older and more experienced, possibly more jaded having likely lived through more market down turns, their subjective positions or “seats” on Wall Street appear to take on the following tenuous balancing act —the competing axis of Conservation, i.e developing security for oneself or a survival of the fittest mindset, versus a strong need for an Openness to Change, i.e. constantly innovating because of a persistent fear of failure (Potts, 2015). For example, senior PM, Paul, seems to express, with the following discursive statements, the increased pressure to perform as your trading “book” gets larger whereby there’s increased risk for both immense profitability and colossal failure:
as in you know either…if you’re an international athlete and you’re racing in the worlds or you know you can have a bigger impact than if you’re just doing your county. You know ultimately it’s the same race and everything…you know for us it’s the amount of money we’re managing is much bigger versus previously or whatever. So I think if you actually get to that…sort of level in the first place you have to have had a certain amount of emotional resilience to get there.
Most senior PM, Christian, agrees regarding the increased pressures faced as traders manage larger “books”, and that he appears to imply that no one on Wall Street is interested in your great successes of yesterday and over confidence is like “the kiss of death” on Wall Street. He seems to argue that traders can never live as if a certain amount of money is always going to be made because “that’s the trap of my business, that is the trap of eat what you kill. Is some people think that they really are that good and it’s really not that sustainable”. Thus, in efforts to innovate and create longevity on Wall Street, Christian appears to assert that traders must add contextual challenges outside of work such as yoga or meditation.
Wall Street’s power of profitability Furthermore, as senior traders’ values become more “fluid” from a perspective of “conceiving” more negative than positive Wall Street experiences, they, along with their more junior colleagues, still, appear to never escape Wall Street’s over arching power of PNL creation (Rogers, 1968). Thus, Christian says that if the values’ cards from the ACT workshop were given to the most successful hedge fund founders in the world, one card would be missing. He summarizes Wall Street’s power best with the following discursive statements:
I’d love it if people would be really honest about…the behaviors that are really valued. Look— I think if you ask ABC Hedge Fund Founder—I think he’d say profitability…Like we want people that innovate…remain cutting edge. But I think…instead people are putting in their mission statements things like integrity and honesty and teamwork, and…that is all complete bullshit.
The aforementioned discourse, from a challenge perspective, appears to highlight how the
subjectivity of our participants’ “seats” evolves or authentically develops into a Neo-
Darwinism paradigm underpinned by Wall Street’s power. This process appears to resemble a
more contemporary form of natural selection whereby traders ultimately seek to obtain the
balance of both success and longevity on Wall Street guided by a sense of personal honesty.
However, it appears that their “operant” behaviours must tip the values axes more in favour of
benefiting themselves than others in order to have longevity of success.
Additional Practical and Theoretical Implications of this Qualitative Research
In addition to the common and central object positions of the participant transcripts, this research would be remiss if it didn’t address other pertinent, transcript data which appears to be in line with the aforementioned ACT research regarding exploration, re-activation, and clarification of personal values and the successful employment of experiential exercises, such as the values cards used in the workshop for this dissertation (Baer, 2015; Fitzpatrick, et al., 2016). Furthermore, like the findings in Baer (2015), the values card exercise seemed to have immediately developed a mindful compassion among some of the participants towards themselves with regards to any guilt and/or regret they may have associated with misplaced priorities. For example Nathan wanted to move towards self-development in particular areas of his work, but he appeared to express the need to get beyond or away from some of the past undesirable feelings he associates with asking questions about new trading products, and “…that sometimes you’re gonna look stupid when you ask questions…but that’s part of the process”.
Furthermore, this data also re-affirms some of Fiztpatrick and colleagues (2016) findings with respect to what individuals seek in order to increase value congruent behavior, including the following: 1) contextual challenges, i.e Tom appears to say that he golfs outside of work because it mimics the focus and attention necessary to work on the trading floor while Christian choses yoga, 2) focused attention, i.e. David says he takes takes a few moments every day to reflect and think about what he wants in life, and 3) cognitive activation or re-perceiving, i.e. Paul’s values’ bracelet discussed earlier in this paper appears to be a perfect example of keeping a physical reminder close by to continually reactive “remembering your values.” Finally, since it appears that all of the participants found the values cards exercise to be the most memorable and helpful part of the ACT workshop, this research further supports Reilly and colleagues (2019) quantitative findings that values-based living appears to be the key component to ACT.
Limitations of this Qualitative Research
A possible limitation is that FDA involves subjective interpretation on the part of the researcher. Therefore, parallel research could be done to see if another researcher would have comparable object positions and interpretations amidst the same data (Willig, 2013). Furthermore because of time limitations and the complicated nature of FDA, this dissertation was only able to focus upon how the participants’ values were related to their work lives, even though the research question inquired about values in relation to both home and work. However, the transcript data did appear to illustrate that the participants found it more difficult to work on application of their values at home than at work. Some participants said they were either too tired and, thus, take it for granted that their loved ones are “picking up their slack” while others said that it seems to come more naturally at home because these environments are oftentimes less stressful than the workplace.
Conclusion and Future Directions
“Disentangling” Wall Street traders from their negative thoughts and feelings in order to move towards values based living is challenging. Thus, this qualitative paper serves as an instructive starting point for further research of values among professionals in high stakes industries. It provides insight into theories or reorientations around the pursuit of values based lives which can be added to ACT training workshops in the future, such as Schwartz’s (2012) circumplex, Roger’s (1964) notions of “fluidity”, and Skinner’s (1971) theories of “operant” behavior.
The participants appeared to exercise a genuine interest in ACT’s experiential exercises and how this may improve their overall well being. Thus, it seems that no one escapes suffering and that traders are faced with immense challenges and the unrelenting pressures of profitability thereby a vulnerable population that appear open to strategies which encourage values based living.
References
Baer, R. (2015). Ethics, Values, Virtues, and Character Strengths in Mindfulness-Based Interventions: A Psychological Science Perspective. Mindfulness, 6(4), 956-969. doi:10.1007/s12671-015-0419-2
Basic Concepts for Qualitative Research: Amazon.co.uk: Immy Holloway: 9780632041732: Books. (n.d.). Retrieved September 10, 2019, from https://www.amazon.co.uk/Basic-Concepts-Qualitative-Research-Holloway/dp/0632041730
Dalio, R. (2017). Principles: Life and work. Simon and Schuster.
Desimone, A. (n.d.). For Whom the Bell: Inaugurating the Spectacle. The NYSE Stock Exchange and its opening bell as a site of Performance. Retrieved September 10, 2019, from https://www.academia.edu/10994380/For_Whom_the_Bell_Inaugurating_the_Spectacle._The_NYSE_Stock_Exchange_and_its_opening_bell_as_a_site_of_Performance
Duff, T. (2103). The Buy Side: A Wall Street Trader’s Tale of Spectacular Excess Hardcover3. New York, NY: Crown Publishing Group.
Fitzpatrick, M., Henson, A., Grumet, R., Poolokasingham, G., Foa, C., Comeau, T., & Prendergast, C. (2016). Challenge, focus, inspiration and support: Processes of values clarification and congruence. Journal of Contextual Behavioral Science, 5(1), 7-15. doi:10.1016/j.jcbs.2016.02.001
Flaxman, P. E., Bond, F. W., & Livheim, F. (2013). The mindful and Effective Employee: An acceptance and Commitment Therapy training manual for Improving well-being and performance. New Harbinger Publications.
Harris, R. (2019). ACT made simple: An easy-to-read primer on acceptance and Commitment therapy. Oakland, CA: New Harbinger Publications.
Hayes, S. C., & Smith, S. (2006). Get out of your mind & into your life the new acceptance & commitment therapy. Enskede: TPB.
Hayes, S. C., Strosahl, K. D., & Wilson, K. G. (2016). Acceptance and commitment therapy: The process and practice of mindful change. New York: Guilford Press.
Jargow, L. (2017, August 18). The Courage to Speak Truth in Untruthful Times. Retrieved September 10, 2019, from http://www.publicseminar.org/2017/08/the-courage-to-speak-truth-in-untruthful-times/
King, L. A., & Hicks, J. A. (2009). Detecting and constructing meaning in life events. The Journal of Positive Psychology, 4(5), 317-330. doi:10.1080/17439760902992316
Lopez, L., & Nisen, M. (2014, February 05). 22 Phrases That Only Wall Streeters Will Understand. Retrieved September 07, 2019, from https://www.businessinsider.com.au/phrases-only-wall-street-understands-2014-1
Martin, D. J., Garske, J. P., & Davis, M. K. (2000). Relation of the therapeutic alliance with outcome and other variables: A meta-analytic review. Journal of Consulting and Clinical Psychology, 68(3), 438-450. doi:10.1037//0022-006x.68.3.438
Mendelsohn, A., Pine, A., & Schiller, D. (2014). Between Thoughts and Actions: Motivationally Salient Cues Invigorate Mental Action in the Human Brain. Neuron, 81(1), 207-217. doi:10.1016/j.neuron.2013.10.019
Mental health in the workplace. (2019, August 09). Retrieved September 11, 2019, from https://www.who.int/mental_health/in_the_workplace/en/
New ways of seeing through qualitative research. (n.d.). Retrieved September 11, 2019, from https://journals.aom.org/doi/10.5465/amj.2018.4004
Peterson, J. B. (2018). Summary of 12 rules for Life: An antidote for chaos. Richdad Summaries.
Potts, D. (2015, August 18). The Schwartz Theory of Basic Values and Some Implications for Political Philosophy. Retrieved September 07, 2019, from https://irfankhawajaphilosopher.com/2015/08/12/the-schwartz-theory-of-basic-values-and-some-implications-for-political-philosophy/
Purser, R. (2018). Critical perspectives on corporate mindfulness: Journal of … Retrieved September 11, 2019, from https://www.tandfonline.com/doi/ref/10.1080/14766086.2018.1438038
Reilly, E. D., Ritzert, T. R., Scoglio, A. A., Mote, J., Fukuda, S. D., Ahern, M. E., & Kelly, M. M. (2019). A systematic review of values measures in acceptance and commitment therapy research. Journal of Contextual Behavioral Science, 12, 290-304. doi:10.1016/j.jcbs.2018.10.004
Rogers, C. R. (1964). Toward a modern approach to values: The valuing process in the mature person. The Journal of Abnormal and Social Psychology, 68(2), 160-167. doi:10.1037/h0046419
Schwartz, S. H. (2012). An Overview of the Schwartz Theory of Basic Values. Online Readings in Psychology and Culture, 2(1). doi:10.9707/2307-0919.1116
Seligman, M. (2017). Authentic happiness: Using the new positive psychology to realise your potential for lasting fulfillment. London: Nicholas Brealey Publishing.
Shakespeare-Finch, J., & Lurie-Beck, J. (2014). A meta-analytic clarification of the relationship between posttraumatic growth and symptoms of posttraumatic distress disorder. Journal of Anxiety Disorders, 28(2), 223-229. doi:10.1016/j.janxdis.2013.10.005
Shapiro, S. L., Carlson, L. E., Astin, J. A., & Freedman, B. (2006). Mechanisms of mindfulness. Journal of Clinical Psychology, 62(3), 373-386. doi:10.1002/jclp.20237
Skinner, B. F. (1971). Beyond freedom and dignity: (6. print.). New York.
Turner, D. (1999). Clive Seale (ed.), Researching Society and Culture, London: Sage, 1998, £45.00 (£14.99 pbk), 349 pp. (ISBN 0-7619-5276-4 hbk; 0-7619-5277-2 pbk). Sociology, 33(4), 835-865. doi:10.1017/s0038038599390532
Ussher, J. M., & Perz, J. (2017). Critical Discourse/Discourse Analysis. Handbook of Research Methods in Health Social Sciences, 1-16. doi:10.1007/978-981-10-2779-6_105-1
Willig, C. (2013). Introducing qualitative research in psychology. Maidenhead: McGraw Hill Education, Open University Press.
World Health Organization. (n.d.). Mental Health in the Workplace. Retrieved September 10, 2019, from http://www.scirp.org/(S(czeh2tfqyw2orz553k1w0r45))/reference/ReferencesPapers.aspx?ReferenceID=818495
Yadavaia, J. E., & Hayes, S. C. (2009). Values in Acceptance and Commitment Therapy: A Comparison With Four Other Approaches. Hellenic Journal of Psychology, 6, 244-272.
Appendices
Appendix A
Acceptance and Commitment Training (ACT) in the workplace: Improving finance professionals’ “psychological flexibility” with Ross McIntosh on Saturday the 15th of June, 2019, 9am-12pm —Belmond Cadogan Hotel, 75 Sloane Street, Chelsea, SW1X 9SG
Dear All,
My name is Tia Lancaster. Many of you know my husband Colin Lancaster. Colin runs a global macro business at Citadel. I’m an ex-employment attorney and decided with my children grown that I would return to school to study organisational psychology. I wanted to study something that has always interested me—to find what drives high stakes’ finance professionals in the markets and how to increase their “psychological flexibility” to elongate careers, improve overall mental health, and maximize performance. I’m reaching out to you today to see if some or all of you would be interested in being my guests to participate in a free, short workplace training session called Acceptance and Commitment Training (ACT) which will then serve as the basis to my Master’s Dissertation.
ACT is an evidence-based, user friendly, mindfulness-rooted approach for increasing employees’ personal resilience, well-being, and “psychological flexibility” which will likely translate into increased success and happiness in one’s professional and personal life. Fast paced, pressure filled Wall Street can at times feel overwhelming and exhausting, and you may often feel disconnected from a sense of personal meaning in your work and/or personal lives. ACT programs delivered in workplace settings are designed to help you become more aware of the qualities and/or values that you most want to express in your daily behaviours. ACT offers strategies or tools to help you relate more skillfully to difficult or unhelpful thoughts and feelings in order to better focus upon personal and professional values and/or goals.
This will be a short training session introducing strategies currently being used in workplace settings through out the world, followed by interviews of 3-8 volunteers. My classmate, Michael, and I will be examining two different research questions for our dissertation projects and volunteer participants are welcome to take part in both or either interview time periods. The first interviews, with Michael, will be conducted within the first week post intervention and the second interviews, with Tia, will be conducted one month post training. The interviews will be scheduled according to your availability outside of work hours, at a, preferably, quiet location chosen by you, and not lasting more than an hour.
If you chose to attend, you will be fortunate to receive this training from Ross McIntosh. Ross is an organisational and coaching psychologist, and he delivers ACT-based training to staff in the NHS, Civil Service and the private sector. He co-founded the start-up, ACT3 Psychology, dedicated to cultivating psychological flexibility in individuals and organisations.
I hope that I have piqued your interest, and that you will decide to join us on Saturday morning, 9am-12pm, the 15th of June, 2019. Many thanks in advance for those of you who decide to attend—I promise that you won’t regret it! If interested, please send me a quick email to confirm your attendance. Coffee and pastries will be served- Cheers!
Best,
Tia Lancaster
tlancaster@me.com
Appendix B
PARTICIPANT INFORMATION SHEET
Title of study
How High-Stakes, Wall Street Professionals Appear to Maintain Focus Upon their Personal Values at Home and at Work
Name of principal investigator/researcher
The main investigator is Tia Lancaster, an organisational Psychology student at City, University of London, who will be carrying out the study as part of her masters’ dissertation. The supervisor is Dr Paul Flaxman, a Senior Lecturer in Organisational Psychology at City, University of London.
Invitation paragraph
We would like to invite you to take part in a research study. Before you decide whether you would like to take part it is important that you understand why the research is being done and what it would involve for you. Please take time to read the following information carefully and discuss it with others if you wish. Ask us if there is anything that is not clear or if you would like more information. You will be given a copy of this information sheet to keep.
What is the purpose of the study?
This research is part of an organisational psychology Masters’ dissertation. This qualitative research will introduce Wall Street traders to a half-day, modern, user-friendly, mindfulness-informed, training technique called Acceptance and Commitment Training (ACT). This training is being conducted in order to illicit information regarding the personal values of Wall Street bankers and/or traders. The participant’s perspective will likely help to emphasize the diversity of interpretation or characterization of the trader/banker’s individual values and their implications for possible ways of being.
Why have I been invited to take part?
In order to take part in the study, participants must be above the age of 18 and can be either part-time or full-time bankers and traders from the Wall Street, finance world. They are volunteers and this will not effect their current employment and/or promotion prospects, etc.
Do I have to take part?
Participation in the project is voluntary, and you can choose not to participate in part or all of the project. You can withdraw at any stage of the project without being penalised or disadvantaged in any way. It is up to you to decide whether or not to take part. If you do decide to take part you will be asked to sign a consent form. If you decide to take part you are still free to withdraw at any time and without giving a reason. The data is confidential and participants will no longer be able to withdraw their data. If a participant choses to withdraw their data, any existing data will be destroyed.
What will happen if I take part?
This will be a short training session at Belmond Cadogan Hotel on the 15th of June, 2019 from 9am-12 pm. An organisational psychologist will implement an Acceptance andCommitment Training (ACT) intervention with 15 Wall Street traders, analysts, and/or bankers in a half-day, one-time workshop, followed by semi-structured interviews of 3-8 participants. My classmate, Michael, and I will be examining two different research questions for our dissertation projects and volunteer participants are welcome to take part in one of two or both interview time periods. The first interviews, with Michael, will be conducted within the first week post intervention and the second interviews, with Tia, will be conducted one month post training.
The participants will receive this training from Ross McIntosh. Ross is an organisational and coaching psychologist, and he delivers ACT-based training to volunteers and staff in the NHS, Civil Service and the private sector. He co-founded the start-up, ACT3 Psychology, dedicated to cultivating psychological flexibility in individuals and organisations.
Following the training and the interviews a Foucauldian discourse analysis will be conducted with a social, constructivist perspective, in mind. This perspective will help to emphasize the diversity of interpretation or characterization of the trader/banker’s individual values and their implications for possible ways of being.
What are the possible disadvantages, risks, and/or benefits of taking part?
There may be the possibility of evoking uncomfortable thoughts and feelings. The research may benefit the wider Wall Street finance community if it’s beneficial to the participants and they chose to share it with their colleagues and competitors or ask to bring an ACT worksop to their particular places of employment. However, in the unlikely case that a participant experiences “extreme detriment to their mental state”, and skipping a question or ending the interview does not restore their well being sufficiently, the participants may contact the NHS Mental Health Services at NHS Central London Clinical Commissioning Group, 0800 0234 650
0800 0234 650
cnw-tr.spa@nhs.net
Data privacy statement
City, University of London is the sponsor and the data controller of this study based in the United Kingdom. This means that we are responsible for looking after your information and using it properly. The legal basis under which your data will be processed is City’s public task.
Your right to access, change or move your information are limited, as we need to manage your information in a specific way in order for the research to be reliable and accurate. To safeguard your rights, we will use the minimum personal-identifiable information possible (for further information please see https://ico.org.uk/for-organisations/guide-to-data-protection/guide-to-the-general-data-protection-regulation-gdpr/lawful-basis-for-processing/public-task/).
City will use your name and contact details to contact you about the research study as necessary. If you wish to receive the results of the study, your contact details will also be kept for this purpose. City will keep identifiable information about you from this study for 10 years after the study has finished.
You can find out more about how City handles data by visiting www.city.ac.uk/city-information/legal. If you are concerned about how we have processed your personal data, you can contact the Information Commissioner’s Office (IOC) https://ico.org.uk/.
Will my taking part in the study be kept confidential?
All data will be kept confidential and stored on an encrypted laptop, and maintained by City, University of London via the UK Data Archive for 10 years.
What will happen to the results?
Results of this study may aid in future research done by myself or other City, University of London researchers regarding ACT’s potential benefits for high stakes’ finance professionals. Also, the anonymised results may be used to prepare for future ACT interventions with other Wall Street professionals when I become a practicing organisational psychologist, and I will ask that you explicitly consent to these possible purposes.
What will happen when the research study stops?
If the project is stopped, all data will be destroyed.
Who has reviewed the study?
This study has been approved by City, University of London, Research Ethics Committee.
What if there is a problem?
If you have any problems, concerns or questions about this study, you should ask to speak to a member of the research team. If you remain unhappy and wish to complain formally, you can do this through City’s complaints procedure. In order to issue any complaints about this study, you need to phone 020 7040 3040. You can then ask to speak to the Secretary to Senate Research Ethics Committee and inform them that the name of the project is: How High-Stakes, Wall Street Professionals Appear to Maintain Focus Upon their Personal Values at Home and at Work
You can also write to the Secretary at:
Anna Ramberg
Research Integrity Manager
City, University of London, Northampton Square
London, EC1V 0HB
Email: Anna.Ramberg.1@city.ac.uk
Insurance
City holds insurance policies which apply to this study. If you feel you have been harmed or injured by taking part in this study you may be eligible to claim compensation. This does not affect your legal rights to seek compensation. If you are harmed due to someone’s negligence, then you may have grounds for legal action.
Further information and contact details
Contact details of my supervisor, Dr. Paul Flaxman, who will answer any inquiries about the research, are as follows: paul.Flaxman@1city.ac.uk
Thank You for Taking the Time to Read this Information Sheet
Appendix C
Training Consent Form
Title of Study: How High-Stakes, Wall Street Professionals Appear to Maintain Focus Upon their Personal Values at Home and at Work
Please initial box
1
I confirm that I have had the project explained to me, and I have read the participant information sheet, which I may keep for my records. I understand this will involve an Acceptance and Commitment Training (ACT) workshop with 15 Wall Street traders, analysts, and/or bankers in a half-day, one-time workshop with brief, skills-based, and group format training programmes. My classmate, Michael, and I will be examining two different research questions for our dissertation projects and volunteer participants are welcome to take part in one of two or both interview time periods. The first interviews, with Michael, will be conducted within the first week post intervention and the second interviews, with Tia, will be conducted one month post training.
2
This information will be held by City as data controller and processed for the following purpose:
Public Task: The legal basis for processing your personal data will be that this research is a task in the public interest, that is City, University of London considers the lawful basis for processing personal data to fall under Article 6(1)(e) of GDPR (public task) as the processing of research participant data is necessary for learning and teaching purposes and all research with human participants by staff and students has to be scrutinised and approved by one of City’s Research Ethics Committees.
3
I understand that any information I provide is confidential, and that no information that could lead to the identification of any individual will be disclosed in any reports on the project, or to any other party. No identifiable personal data will be published. The identifiable data will not be shared with any other organisation.
4
I understand that my participation is voluntary, that I can choose not to participate in part or all of the project, and that I can withdraw at any stage of the project without being penalised or disadvantaged in any way.
5
I agree to City recording and processing this information about me. I understand that this information will be used only for the purpose(s) set out in this statement and my consent is conditional on City complying with its duties and obligations under the General Data Protection Regulation (GDPR).
6.
I agree to the arrangements for data storage, archiving, sharing.
8
I agree to take part in the above study.
____________________ ____________________________ _____________
Name of Participant Signature Date
____________________ ____________________________ _____________
Name of Researcher Signature Date
Appendix D
Semi-Structured Interview Questions
1). A large part of the workshop was about using our personal values. Just to start, what does that term mean to you? How do you personally define what that means?
* Additional question added following the pilot interview: Can you isolate your core set of personal values?
2). Could you tell me about your experience of the personal values part of Ross’ workshop last month? Particularly anything that has stayed with you since attending the workshop?
a) Prompt: In relation to using personal values in your work life?
b) Prompt: In relation to using personal values in your life outside of work?
3). Could you describe any strategies that you’ve used since the workshop to help you to stay more aware of personal values in your life?
a) Prompt: Any specific examples where you wanted to stay aware of personal values during challenging moments or decisions?
b) Prompt: Can you recall a challenging time over this past month, either personally or professionally, when you were able to use personal values as a guide?
c) Prompt: Prompt: How about a time in your past, a specific example, when you’ve achieved more than imagined or expected, how do you think your personal values for into this scenario?
Blog
The Wall Street “ACT” and Values Based Living
What drives high stakes’ finance professionals in the markets and how can we increase their “psychological flexibility” in order to elongate their careers, improve overall mental health, and maximize performance while still helping them to maintain focus on what matters? High stakes professionals, especially Wall Street traders, are often a population deemed to be unworthy of sympathy primarily because of the media’s betrayal of its actors as depraved and entitled—as depicted in the ever popular film, The Wolf of Wall Street. However, Wall Street professionals are normal human beings just like you and me, but they have a sharper, more acute level of stress because it happens in real time and market “swings” can happen instantaneously. Thus, it appears that they are a population that is continuously over-stressed and desire strategies to improve their overall well being. Acceptance and Commitment Therapy could unlock the secret and help cultivate Wall Street professionals who are both mindful and in pursuit of values based living.
ACT is an evidence-based, user friendly, mindfulness-rooted approach for increasing employees’ personal resilience, well-being, and “psychological flexibility” which will likely translate into increased success and improvements in overall well being. Fast paced, pressure filled Wall Street can oftentimes feel overwhelming and exhausting, and these professionals may often feel disconnected from a sense of personal meaning in their work and/or personal lives. ACT programs delivered in workplace settings are designed to help individuals become more aware of the qualities and/or values that they most want to express in their daily behaviours. ACT offers strategies or tools to help individuals relate more skillfully to difficult or unhelpful thoughts and feelings in order to better focus upon values based living.
Examples of ACT strategies which promote values based living include experiential exercises amidst different domains of life, such as: marriage, family, community, physical fitness, diet, arts, literature, etc. These exercises are usually done through a Valued Living Questionnaire, values cards, and/or a semi-structured interviews whereby individuals self-rate the importance of each value domain and their committed actions in each area. These exercises help individuals identify and re-direct energy “towards” areas of high priority and “away” from areas of low priority. Additional mindful activities include individuals writing their own tombstone epitaphs or a birthday speech that a friend or co-worker would give about them in order to capture how they would like to be remembered
What is values based living?
Many psychological treatments hold personal values to be central to living productive and vital lives. ACT is considered to be a modern psychotherapy model which builds upon many other values-based psychology theories, such as: the client-centered approach of Carl Rogers, B.F. Skinners “radical behaviorism”, and Martin Seligman’s positive psychology. Rogers’ client-centered therapy is centered around “unconditional positive regard”. Unconditional positive regard is simply about accepting and supporting another exactly as they are, and it draws a distinction between “operative values”(i.e. infant perceptions are created in the present moment with each new experience) and “conceived values” (i.e. as we grow older our values become more rigid, inefficient, and influenced by the judgment of others). Client-centered therapy does not require individuals to abandon conceived values, but it encourages individuals to moderate their behaviour based upon feedback from the environment which allows them to live more authentically.
Similar to Rogers, Skinner (1971) associates values with operant behaviour and with pursuing what is good, i.e. “positive reinforcers”, and according to his notion of “radical behaviorism”, values are the reinforcing effects of consequences, and these behaviors or values can be done either for the good of others or for the good of oneself . Additionally, Martin Seligman (2017) is considered to be the father of positive psychology and he advances the idea of the “self-actualisation” of potential and “self-determination theory” whereby people intrinsically move towards motivation and autonomy. “Positive psychology” emphasizes more modern day mindfulness techniques and activities which identify and enhance signature strengths, i.e. values.
In addition to the aforementioned theories regarding values, ACT also works well along side or in conjunction with Shalom Schwartz’s circumflex of values which is illustrated below. Schwartz asserts that there are ten universal and cross cultural values that all human beings possess, such as: self direction, benevolence, hedonism, achievement, security, etc. Schwartz’s compilation of universal values form a circular structure and reflect the motivations that each value expresses. They sit closely along side one another in the circumplex to form a continuum of motivational similarities and dissimilarities which are simultaneously congruent and conflicting across two axes —Openness to Change versus Conservation and Self-Transcendence versus Self-Enhancement.
“Disentangling” Wall Street traders from their negative thoughts and feelings and encouraging them to implement a more authentic balancing of values in their lives will be challenging. However, recent qualitative research of what trading professionals value most in their lives indicates they have a strong desire for focused attention and re-ignition of what matters most to them. It appears that no one escapes suffering and that traders, whom are subject to unrelenting pressures of Wall Street’s expectations of profitability, are a vulnerable population that appear ready to undertake values based living.
* The author utilised the following reference materials for creation of this blog: Duff, T. (2103), The Buy Side: A Wall Street Trader’s Tale of Spectacular Excess; Flaxman, P. E., Bond, F. W., & Livheim, F. (2013), The mindful and Effective Employee: An acceptance and Commitment Therapy training manual for Improving well-being and performance;Potts, D. (2015, August 18). The Schwartz Theory of Basic Values and Some Implications for Political Philosophy. Retrieved online September 07, 2019; and Yadavaia, J. E., & Hayes, S. C. (2009). Values in Acceptance and Commitment Therapy: A Comparison With Four Other Approaches.