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The job design happiness
scale ( JDHS)
Georg Dutschke and Lia Jacobsohn
Universidade Atlântica, Lisbon, Portugal
Alvaro Dias
Universidade Lusófona and ISCTE, Lisbon, Portugal, and
Jaime Combadão
Universidade Atlântica, Lisbon, Portugal
Abstract
Purpose –The purpose of this paper is to identify the factors that individuals consider necessary to be
happy in their job. Based on these factors, a measure of job design happiness ( JDH) is proposed.
Design/methodology/approach –Two methods were applied: a qualitative study with content
analyses (n¼969) to develop an exploratory questionnaire; and exploratory and confirmatory factor
analysis by applying structural equations models. In this second study the questionnaire was sent to a second
sample (n¼1,079).
Findings –Five first-order factors were identified: self-fulfillment; group working, attaining goals;
leadership; and sustainability and job/family balance. These factors are explained by a second order
factor: JDH.
Research limitations/implications –Further research is needed to determine how the identified
“job design happiness”components may interact with one another. Testing the measure of different
industries and national cultures is also suggested.
Practical implications –Managers and human resources practitioners can improve job and organizational
performance by applying the scale in several moments in time measuring the job happiness “pulse,”
monitoring their decisions.
Social implications –The adoption of this measure for decision making in organizational and job design
can contribute to the improvement of living standards and firm sustainability.
Originality/value –Research on organizational happiness has been increasing but instruments to measure
JDH, considering organizational factors, are limited.
Keywords Happiness, Job design happiness, Job happiness factors, Job well-being
Paper type Research paper
Introduction
The scientific concept of wellness is achieving particular relevance since the World Health
Organization (WHO, 1946) defined health, not just through physical medical parameters,
but, in a broader way, including the bio-psychosocial well-being perspective. The happiness
concept benefits from this perspective. The concepts of well-being and happiness have been
used interchangeably (Blanch et al., 2010; Warr, 2013; Ong and Lin, 2016), or linked to
others, depending on the theory considered, as the subjective well-being (Diener, 2000;
Strack et al., 1991) or psychological well-being (Bryce and Haworth, 2003; Ryff and Keyes,
1995; Warr, 1987, 1990). A review of the different definitions reveals that they are supported
by each theory they have been built from (Veenhoven, 2012). Like most happiness
definitions, the subjective well-being mostly refers to positive feelings associated to positive
subjective assessments (Diener et al., 1991). In its broadest sense, happiness is a general term
for all the good in life. According to Blanch et al. (2010), instruments to evaluate well-being
(happiness) are, among others: the general health questionnaire (Goldberg and
Williams, 1996), beck depression inventory (Beck et al., 1961), satisfaction with life scale
(Diener, 1994; Diener et al., 1985), Oxford happiness questionnaire (Hills and Argyle, 2002),
Journal of Organizational Change
Management
Vol. 32 No. 7, 2019
pp. 709-724
© Emerald Publishing Limited
0953-4814
DOI 10.1108/JOCM-01-2018-0035
Received 30 January 2018
Revised 6 May 2019
Accepted 5 October 2019
The current issue and full text archive of this journal is available on Emerald Insight at:
www.emeraldinsight.com/0953-4814.htm
JEL Classification —J280, J2803A
709
The job design
happiness
scale
quality of life enjoyment and satisfaction questionnaire (Endicott et al., 1993), scales of
psychological well-being (Ryff and Keyes, 1995; Van Dierendonck, 2004) and the WHO
quality of life assessment instrument (De Vries and Van Heck, 1997). These instruments
consider, mostly, health and pathologic factors as the discriminating criteria and, in
particular, psychopathologic factors.
Happiness at work is a multidimensional concept including transient moods and
emotions, relatively stable attitudes and highly stable individual dispositions, aggregated at
an individual level (Fisher, 2010). According to Bakker et al. (2011), happinessat work could
be conceptualized as a framework, considering that the professional is satisfied with his job
and experiences frequent positive emotions, such as joy and happiness, and infrequent
negative emotions, like sadness and anger.
Different authors have been working on the emotional well-being at work. However,
measures specifically dedicated to evaluating “job design happiness”( JDH) are focused
on health and pathology factors as the discriminating criteria, in particular,
psychopathology factors as work-related emotions, by applying dimensions of
pleasantness and arousal (Warr, 1987, 1990). The job-related affective well-being model
(Warr, 1990) consists of four interrelated factors: anxiety, comfort, depression and
enthusiasm. Another instrument, the work-related quality of life scale (Van Laar et al.,
2007) evaluates six factors: job satisfaction and career, working conditions, general
well-being, work family life balance, work stress and control at work. With the positive
psychology development, the concept of “work engagement”is increasing its
importance, being evaluated based on dimensions as vigor, dedication and absorption,
stable indicators of the occupational well-being (Rodríguez-Muñoz et al., 2014), included in
the Utrecht work engagement scale (Schaufeli et al., 2002).
The decisions taken during the job design definition will have a determinant influence on
employee’s satisfaction and engagement, with direct implications on the productivity and
quality of work output (Wall and Parker, 2001). Considering that “job design”is the
employee’s way to satisfy globally, personal, family and social, needs (Rush, 1971), can be
defined as a structure, content and professional’s work tasks and roles configuration
(Parker and Ohly, 2008).
Due to economic and social implications, research in job design, has been prolific and
heuristics for the past 30 years. With a focus both on theory and models, became
prominent the job characteristics model (Hackman and Oldham, 1976), the socio-technical
systems theory and the action regulation theory (Hacker, 2003). During this period, an
extensive new knowledge on the physical characteristics of the tasks, their psychological
effects and the factors moderating these effects were accumulated. The interest in the job
design research plummeted recently as major changes on job reality are occurring
(Ambrose and Kulik, 1999). Among others, teams are much more heterogeneous in gender,
culture and backgrounds, teleworking/homeworking is becoming normal and millennials
have a different relation with the organizations. These relevant changes at the workplace
are contributing for the increasing interest oftheacademyinthejobdesignresearch,with
a major focus on the social and relational job design characteristics (Grant, 2007).
Grant et al. (2010) propose the incorporation of cross-disciplinary, cross-level and
cross-cultural perspectives. Erez and Earley (1993) refers that job design should be
conceived in the organizations by considering regional- and national-level cultural values,
as may not be possible to have the same job design in two different cultures without
confirming, first, whether the workers will (or not) feel well-being.
Despite the increasing interest in the job design research, there is a gap on identifying
instruments measuring factors and components related to JDH, particularly factors
related with the socio-cultural variability of wellness. Proposing a measure for JDH would
be relatively simple by reviewing the well-being hedonic dimensions. However, it is much
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more difficult to propose an instrument that absorbs the eudemonic aspects of happiness
(Ryan and Deci, 2001). Fisher (2010) refers that these large and complex factors are
located at three levels: transient, psychological and the unit. These factors could be
biological (Diener and Works, 2009), motivational (Deci and Ryan, 2008), relational
(Biggio and Cortese, 2013), personality (Emmons, 1986), developmental, cognitive and
affective (Galinha and Pais-Ribeiro, 2011) and ethical (Krant, 2009). In psychology
and social psychology exists multiple paradigms related with reality. However, motive
(in opposition to the theories of motivation) is a major concept, managed and accepted by
most of the paradigms that tends to be consensual. The concept in which cross-cultural
differences were found is the motive. This concept is scientifically accepted as being the
one mediating the job design and well-being. In psychology, motive means a personality
trait that tends to determine which actions take an individual’s values over others’.
Motives are part of the self-control process allowing the individual to meet his/her needs.
Pleasure is often related with active satisfaction and, as demonstrated by McClelland
(1988), with dominant motives that change according to culture. More recently, a
self-determination theory based on a four-stage motivational sequence (Deci and Ryan,
2000) is been used to explain how autonomy-supportive environments influence people’s
health and well-being (Ng and Feldman, 2012). Other theories have also studied the
relationship between motives and well-being, but with an emphasis on other dimensions
beyond the self-determination issue. Some authors have postulated about the existence of
motivational orientations (Maslow, 1954) or objectives orientation: category intentions
guiding action interpretation (Ames, 1992; Galand and Grégoire, 2000). The relationship
between the satisfaction of psychological needs, motivation and well-being is well
established in different areas of knowledge, as education, health and workplace (Deci and
Ryan, 2008; Ng and Feldman, 2012).
Despite the increasing interest in the job design research, there is a gap on identifying
instruments measuring factors and components related to JDH. With this research we aim
contributing to reduce this gap, by proposing a model that identifies and measures the
components and factors that may have influence on the JDH, also considering factors related
with the socio-cultural variability of wellness.
Methods
Proposing a model for JDH is a challenging task. It needed the description of a tacit mental
model, however, tacit knowledge is not easily verbalized (Batra et al., 2012). JDH has deeper
roots than job satisfaction, with stronger links to employee attitudes as loyalty, and is based
on respondents’own perspective on what makes them happy in the job (Ong and Lin, 2016).
To identify the respondent’s verbalization, individual and subjective, of the components
contributing for their JDH was, first, applied a qualitative and exploratory methodology
(Study 1), followed by a second order factor confirmatory analysis, aiming to validate the
model (Study 2).
Study 1
Participants. This study, developed in 2012, consisted of 969 interviews. Respondents were
active professionals from the APG (Portuguese Human Resources Association) database and
answered as individuals (not as employees from an organization). This method allowed them
to respond according to their own believes. In each interview, the study was explained and
was asked for the permission to use the data. All responses were confidential.
No personal professional data were asked. The sample was segmented by gender
(61 percent male, 39 percent female), hierarchy (20 percent directors, 80 percent non-directors),
age (50 percent up to 39 years, 50 percent more than 40), years in the organization (33 percent
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The job design
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scale
up to five years, 67 percent more than five), years performing the same job (48 percent up to
five years, 52 percent more than five) and organization sector of activity.
Design and procedure. For the interview, an open question was made: What do you need
to be happy in your job design? The methods used for the analyses were: data collection;
data storage; coding; indexing system refinement; code relationship; and identify categories.
For the Stages 3, 4, 5 and 6, a content analysis was applied, by using the software Atlas Ti
V6.0, which combines a friendly use and a major ability to encoding and draws conclusions
(Miles and Huberman, 1994). The codes enable the identification of occurrence patterns, bias
control, alternative or opposite directions and the level of consistency. After identifying the
codes, we proceeded to evaluate their interrelation, the frequency of occurrence and the
number of relation with other codes. This allowed the establishment of the importance and
strength of each code.
Results
A total of 1,000 references were categorized. In total, 26 components where identified:
Ilikemyjob;IfeelIhaveautonomyinperformingmyjob;Ihavethenecessaryresources
to perform my job; my job is in my area of study; the organization allows me to have new
challenges in my job; my job allows me to develop as an individual and a professional; my
job allows continuous learning; my job allows me to be involved in the organization
strategy; I am recognized by performance merit; my job allows me to feel respected; there
is a good team spirit in the organization that facilitates my job; there is a good ambiance in
the organization that facilitates my job; most of my colleagues are motivated in their job;
there is a good integration between the different departments that facilitates my job; my
financial conditions are fair for the job I perform; the goals approved for my job are clear
and fair; I always try to achieve the goals set for my job; the organization is able to have
new projects enabling my job sustainability; have a good performance in my job is
important for the organization to achieve global objectives; I believe that my job is
important for the organization; I feel that my boss has confidence in the way I perform my
job;anytimeIfeeltheneed,Ihavemyboss’s support; I feel that by boss’sleadership
inspires the way I perform my job; my job allows a good professional/personal life
balance; my job allows me to be creative and entrepreneur; I am able to perform my job
with organization and without bureaucracy.
Considering these components, an initial questionnaire was developed. The validity was
verified through three complementary methods: the questionnaire was designed considering
a qualitative research with content analysis; it was sent to three experts (professor, CEO, HR
expert); and a pre-test with ten respondents was applied (Rust and Cooil, 1994).
Study 2
Participants. The questionnaire developed in Study 1 was e-mailed directly to the active
professionals of the APG database during 2013. By doing this, respondents felt more
confident in sharing their true believes, without concerning their organization judgment.
All responses were confidential.
We have received 1,200 answers, considering 1,079 as valid (83.6 percent). The sample is
segmented by gender (52 percent male, 48 percent female), hierarchy (18 percent directors,
82 percent non-directors), age (35 percent up to 39 years, 65 percent more than 40), years in
the organization (47 percent up to five years, 53 percent more than five), years performing
the same job (45 percent up to five years, 55 percent more than five) and industry. These
figures (gender and age) reflect the Portuguese active population (Pordata, 2015). Even
though no data were found for other segments, these values were considered as valuable for
the Portuguese reality.
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Data analysis
An exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was
conducted using software R (R Core Team, 2014) and the packages lavaan, psy, psych, sem,
e1071. The EFA input data were raw data and the package psych was used for the
estimation of the parameters. For CFA, the covariance matrix was used, through the
package lavaan. The components used in these analyses were the 26 previously identified in
the content analysis developed in Study 1. Skewness and kurtosis were assessed through
e1071 package for R.
All components in the EFA were allowed to have loadings with all the factors. In CFA
loadings were allowed between factors and its components, according to the relationships
hypothesized. In both analyses, all factors were allowed to have non-zero covariance
between factors.
Several indices were used to assess the goodness-of-fit of the models: χ
2
value
(Bollen, 1989), bearing in mind that the sample size of the study alone could be indicative of
the tendency to produce significant results; RMSEA, using the limit of 0.06, or lower, as
indicative of good/adequate fit (Schermelleh-Engel et al., 2003); CFI, which is usually used
with a lower limit of 0.95 (Bentler, 1990; Schermelleh-Engel et al., 2003); a lower value than
0.08 in SRMR as adequate fit (Hu and Bentler, 1999) and Akaike information criteria
(Akaike, 1987). After the CFA initial assessment, and by the analysis of the modification
indices, the variance of the errors of some of the items in each factor was allowed to vary.
Results
Cronbach’sαwas used to assess the internal consistency of the questionnaire, resulting in
the value 0.9745, 95 percentCI (0.9727, 0.9762) (confidence interval was calculated by
bootstrap), a very good result. Pearson’s correlation coefficient and correlation network
(Figure 1) showed a moderate to strong correlation between the 26 components.
Exploratory factor analysis
EFA with varimax rotation permitted to assess how the components could cluster together.
Accordingly, we also analyzed factors’eigenvalues, which indicated the possibility of as
many as seven factors, although the decrease in eigenvalues after five factors is minimal. So,
we started by assessing an EFA with seven factors, but because the loadings in two factors
17
19
20
4
1
2
7
25
6
5
8
21
26
3
18
24
13
15
23
11
14
12
16
9
22
10
Figure 1.
Correlation plot
(or correlation
network) between
the 26 items of the
questionnaire
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The job design
happiness
scale
were very low (explaining 5 percent of the variance), a model five factors with higher
loadings was obtained (69 percent of variance). Loadings lower than 0.3 were cut, for easier
visualization (Figure 2).
Confirmatory factor analysis
To test the fit, a first-order CFA model was run by maximum likelihood estimation
(sample ¼1,763). This fitted model had 72 free parameters, 31 variances, 15 covariances
(with 5 covariances between items), 26 paths. The model fit indexes were: χ
2
(284,
n¼1,757) ¼2,598.890, po0.001; RMSEA ¼0.068, 95%CI (0.066, 0.071); SRMR ¼0.035;
CFI ¼0.950; AIC ¼93,003.827.
The correlation coefficients between factors (Table I) were measured, showing a
moderate to strong correlation. As such, a second order CFA was designed, in which the five
factors that were connected with the items indicators are explained by a single second order
factor (Figure 3). This fitted model had 68 free parameters, 32 variances, 5 covariances and
31 paths.
The second order CFA model had a very good fit: χ
2
(289, n¼1,757) ¼2,748.149, po0.001;
RMSEA ¼0.070, 95%CI (0.067, 0.072); SRMR ¼0.038; CFI ¼0.947; AIC ¼93,143.086.
All loadings were significant (po0.001). The Cronbach’sαof each factor was: 0.951, 0.943,
0.952, 0.918 and 0.820, for factors one to five, respectively.
1
2
3
4
5
7
8
9
10
25
11
12
13
14
18
26
17
19
20
21
22
23
15
16
24
F5
F4
F3
F2
F1
Note: Loadings and variances are omitted for the sake of readability
Figure 2.
Results of
the exploratory
factor analysis
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Discussion
A first and cross-reading analysis of the factors permits to identify several dimensions
contributing to JDH, “understood as a function of both job and personal characteristics”
(Warr, 2013, p. 99). The individual dimensions are more related to a long-term perspective,
coexisting with other short-termed dimensions, giving to the model a superordinate concept
to happiness, as suggested by Ong and Lin (2016). Figure 4 outlines the results obtained and
the five dimensions of the JDH scale.
However, the factors related with individuals are the most numerous and seem to be
dominant when comparing with the social and more instrumental ones. The long-term
perspective is particularly visible in the first category of factors that could be considered as
personal self-fulfillment factors.
F1 F2 F3 F4 F5
F1 1 0.908 0.751 0.816 0.920
F2 0.908 1 0.677 0.830 0.963
F3 0.751 0.677 1 0.638 0.677
F4 0.816 0.830 0.638 1 0.807
F5 0.920 0.963 0.677 0.807 1
Note: F, Factor
Table I.
Correlation
coefficients between
factors in the
first-order
factor model
1
2
3
4
5
7
8
9
10
25
11
12
13
14
18
26
17
19
20
21
22
23
15
16
24
F5
F4
F3
F2
F1
F6
Notes: F1 – self-fulfillment; F2 – group and organizational working; F3 – attaining goals;
F4 – leadership and F5 – sustainability and job/family balance. Loadings and variances
are omitted
Figure 3.
Schematics
of the second
order factor model
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Factor 1 –self-fulfillment
The most prominent factor was designated self-fulfillment. The relation between reasons
for self-fulfillment and job design may not seem obvious. But, when analyzing the
self-realization origins in psychology, this relation is clear. Self-realization is the main reason
for one’s action, a kind of a life sovereign purpose guiding all the other actions (Goldstein,
1939). But, being self-realization universal (motives are found in every culture in different
form and proportions), what each individual specifically searches, or the way each
individual wants to achieve, differs from individual to individual. Each individual has his
own innate potential that, naturally, originates different development paths. This is the best
way to identify the individual potential, what he does better to adequate the potential with
the job being done, and the way it is done (Goldstein, 1939).
The best way to achieve self-realization is doing what we like to do, and, do it as best as
we can. In this sense, respondents reported that they need to “develop a job that they like”to
be happy (C1). Do what we like is the epitome of free-will (free choice). As part of the
self-fulfillment dimension, free-will is part of the JDH construct. Studies indicate that
happiness is related with the possibility of exercise free-will. According to World Values
Survey (Inglehart et al., 2008) and European Values Survey (1981–2007), the feeling of free
choice and one’s life control, have a strong importance on explaining the change in social
well-being over time. This association seems to be universal (Welzel and Inglehart, 2010).
However, free-will is part of a major conception. The experience of doing things we like is
what Csikszentmihalyi (1990) has considered the flow experience. The flow concept is well
accepted and adopted since Burke (2010) studied the relationship between the flow at work
experience with indicators of satisfaction, engagement and psychological well-being.
The respondents also considered important the possibility of “having a continuous
learning”(C7) and “new challenges”(C5). Goldstein (1939) referred that a healthy and
normal individual is the one where the tendency to self-realization is due to the joy of
Job Design
Happiness
Self-
fulfillment
Group and
Organizational
Work Sustainability
and job/family
balance
Leadership
Attaining
Goals
• Develop a job that they like
• Continuous learning
• Challenging job
• Availability of resources for the job
• Availability of knowledge for the job
• Job autonomy and responsibility
• Possibility to be creative and entrepreneur
• Involvement in the organization strategy
• Recognition of merit
• Feelings respected
• Good team spirit
• Good work environment
• Motivated colleagues
• Good integration between departments
• New projects
• Well structured organization, without bureaucracy
• Objectives at individual level
• Objectives at institutional level
• Job importance recognition
• Leader trusting on
people
• Leadership gives
support
• Leadership is inspiring
• Job/Family balance
• Financial conditions
• Function must have clear/fair targets
Figure 4.
JDH dimensions
and components
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accomplishment. The “work must provide challenges”(C5) reveals that challenges can be
positively experienced when associated with performance-related behaviors (Ohly and
Fritz, 2010). Furthermore, a challenge is an opportunity of self-overcoming (Lazarus and
Folkman, 1984) and should be an important component of JDH. Lazarus and Folkman
(1984) realized that a situation could be perceived as challenging when offering potential
personal gain, such as mastery or learning. The relation between well-being and challenge
is a subject with high potential for future research. The components “need to have
resources”(C3) and “individuals have the knowledge for the job”(C4) also integrate this
dimension. On one hand, JDH must provide challenging activities. On the other hand, it
should provide the resources and adequate knowledge that enable individuals to
accomplish effectively the tasks.
The “possibility to be creative and entrepreneur”(C25) also contributes for personal
self-fulfillment. This can be associated with JDH. Goldstein (1939) considered that
auto-accomplishment is a natural creative trend. The relation between creativity and
proactivity in the labor context (entrepreneurship) is of special interest (Lazarus and
Folkman, 1984).
Results indicate that time pressure and job control are related to daily creativity and
proactive behavior, supporting the consistency of this feature with those observed
previously, but, also, with the “feel to have autonomy and responsibility in the performance
of my job”(C2). The job characteristics theory model (Hackman and Oldham, 1976), central
in the job design concept, values factors as participation, learning and autonomy, and
increasing work motivation (Hackman and Oldham, 1976). The “importance of autonomy”
(C2) for the well-being is well studied, although usually mediated by factors like
performance avoidance objectives (Heidemeier and Wiese, 2014), existence of a quality
competitive ambiance and organizational commitment (Park and Searcy, 2014).
Another group of components, considered by the respondents, as being part of
self-realization and important for the well-being at work are “involvement in the
organization strategy”(C8), “recognition of merit”(C9) and “feeling respected”(C10). This
subgroup was titled “recognition, respect and consideration”or simply “personal account.”
Cullogh et al. (2002) referred that grateful disposition, self-ratings and observer ratings
are associated with positive affect, well-being, prosocial behaviors and traits, and
religiousness/spirituality. Same authors referred that gratitude is negatively correlated with
envy and materialism, and positively related with vitality and optimism. The “effect of
respect”(C10) on well-being seems to be less explored in the psychosocial literature. A recent
study (Ng and Diener, 2014) revealed that respect is a strong predictor of positive feelings.
The employee possibility to “contribute for organization strategy”(C8) was appreciated by
respondents, related with the possibility to influence, or having power, as a factor of
achievement. Jakson (1983) proposed a causal model to describe the effect of participating in
the decision, with the perceived influence, conflict, ambiguity, personal and job-related
communications, social support, emotional strain, overall job satisfaction, absenteeism and
turnover intention. Since then, little has been published relating to the contribution to the
organization’s strategy and occupational well-being.
Factor 2 –group and organizational working
Unlike the previous factor, happiness attribution is placed on group/organizational
components, not on individual motivations. This factor is based on psychosocial factors of
attribution, not just psychological. Although this is a widespread assumption, only
recently the relation between well-being and group dynamics was studied. Hackman et al.
(1992) considers that the participation in groups origins personal satisfaction. Freeney and
Fellenz (2013) suggest the inclusion of relational resources on models of work engagement
and job design.
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Results highlight the components of group and organizational dynamics associated with
well-being. This factor (F2) includes two levels of components: the group/relational level,
composed by C11 (good team spirit), C12 (good work environment) and C13 (motivated
colleagues), and the organizational/management level, composed by C14 (good integration
between departments), C18 (organization develop new projects) and C26 (well organized/
structured organization, without bureaucracy).
The interest on organization, informal and relational issues, is gaining importance, since
researchers were able to validate their close relation with organizational performance
(Venkataramani et al., 2013). Social well-being is being studied in different dimensions:
friendship, trust relations, social support, reciprocity relations, leadership and integration
relationships (Albrecht, 2012). Rego et al. (2009) have identified three relationships in
organizations: friendship, team spirit, and mutual concern. Social support in organizational
psychology is being used to designate the interactions between workers, and workers with
their supervisors (Luchman and González-Morales, 2013).
Human capital factors, like confidence, seem more related to well-being than other work
characteristics, as financial or technical factors (Helliwell and Huang, 2011). The relationship
between well-being and social and capital work is not always homogeneous (Zacher et al.,
2014). The ambiance, consisting in networks of interaction and communication, through
which workers help each other promoting positive affect, is high valuated in the social
capital (Karasek and Theorell, 1990) and facilitate the task accomplishment. Reis (1984)
stated that having health and good relationships are more likely in competent individuals.
Factor 3 –attaining goals
McClelland (1988) refers that motivation is related with behavior selection, energization and
direction. The relation between motivational method and tracing a list of objectives is well studied.
When a goal is achieved, especially if perceived as important or difficult, the individual feel a sense
of relief or extreme joy (McClelland, 1988). This factor (F3) consists, mainly, in the aggregation of
the C17 (objectives at individual level), C19 and C20 (objectives at institutional level). Research
suggests that objectives serve as an important reference for the affect system, in the sense that
individuals react positively when they achieve objectives, and negatively when they fail (Diener
and Works, 2009). Other studies suggest that achieving results enhanced well-being. A relation
between the promotions of necessity-satisfying experiences as been established with feeling
competent, self-determined and related to others (Sheldon and Elliot, 1999).
Sheldon and Kasser (1995) demonstrate that the relation between objectives
achievement and well-being experience is only possible when the objectives are
coherent with the intrinsic necessity for competence, self-determination and relatedness.
Sheldon and Houser-Marko (2001) refer that the relation is bi-directional: objectives
achievement have a positive effect on the well-being, and well-being promotes the
establishment of more self-concordant goals.
F4 –leadership
Leadership (F4) is in the sequence of (F2) group and organizational working (good ambiance
and motivation within the group and organization), in the sense that it can be related to
social support components. F4 allows the transition between social, instrumental and
productive support. The leadership process has been deeply studied in the organizational
psycho-sociology. Skakon et al. (2010) reveal the impact of leaders and leadership styles on
employee’s well-being.
From the different leadership theories studied, the “transformational leadership theory”
(Burns, 1978) has more impact in well-being. Skakon et al. (2010) have clearly identified that
the relation between transformational leadership and employee well-being is explained
through the experience of having a meaningful work.
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Research demonstrates that individuals, in order to feel good within their job, need to
have a leader trusting them (C21), gives support whenever needed (C22) and be inspiring
(C23). Brown et al. (2005) described ethical leaders as being honest, trustworthy, fair and
caring. They lead employees with respect, keep promises, allow inputs, clarify expectations
and responsibilities. Kalshoven and Boon (2012) refer the existence of a relation between
ethical leadership, helping and well-being. Gilbreath and Benson (2004) demonstrate that the
leader’s support is associated with employee well-being and with a lower stress.
F5 –sustainability and job/family balance
Sustainability and job family balance factor is related with life and work. “Work/life balance”
factor is highly referred in the literature (Crain et al., 2014). “Job/family balance”(C24) means
that work allows family sustainability. From the motivational theory perspective,
sustainability means basic needs fulfillment. The C15 (financial conditions associated with
role) should be interpreted in this way. The C16 (function must have clear/fair targets) is
understood by the ability to achieve objectives without overexertion. Money gains define the
economic status. Is an overarching concept associated with income and material wealth
(Howell and Howell, 2008). There is relevant research on the relation between economic
prosperity and well-being, individually and global levels (Levine and Lombardi, 2014). The
material wealth, also associated with the well-being, is closer to the cognitive component of
well-being than to the affective component (Diener et al., 2010). From a trans-cultural
perspective, Tay and Diener (2011) studied the relation between needs fulfillment and
subjective well-being in 123 countries, concluding that this relation exists in all regions.
Conclusion
Although the JDH has recently emerged as an important concept among both practitioners and
academics, theoretical progress has been hampered. Using a grounded theory approach, this
research involved a qualitative and quantitative study, with the objective to identify
components and factors contributing for JDH. Thus, this work builds on prior research by
taking constructs that had previously been studied independently and demonstrating that JDH
canworkasanintegratedframework.Thequalitative study also demonstrates that research on
JDH derived directly from well-being and positive psychology theories. The second study was
able to validate a model, respective components and factors, by using a SEM analysis.
First-order and higher-order representations of JDH were estimated, demonstrating that JDH
depends on five factors: self-fulfillment, group and organizational working, attaining goals,
leadership, sustainability and job/family balance. The higher-order prototype model adds value
in several ways: leads to a higher comprehensive and integrated understanding on how
professionals experience the JDH, complementing existing studies with a main focus on
individual components; demonstrates how survey data can be collected and modeled; and
demonstrates how more lower-level, and concrete components, can be used to influence
higher-level and more abstract professionals perceptions. As such, top management may
promote employees’JDH, and, this way, obtain higher organizational performance. The
hierarchical model proposed, may assist managers in promoting lower-level actions to
maximize each component targeted, and this way, influence the higher-level, and more abstract,
JDH perceptions. By applying the proposed model, managers would be able to identify
organization strengths and weaknesses regarding JDH, establish effective actions, measure its
impact on productivity and implement, with a strategic vision, a culture of happiness on job.
Limitations and further research
Further research is needed to determine how the identified JDH components may interact
with each other. For that, experimental research manipulating the features of the JDH
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scale
prototype would complement this cross-sectional research, helping to more a more
unambiguously establish of causal directions. Longitudinal research on temporal
development –and possible waning –of JDH would be very useful, also, to validate
factors and components among different industries and national cultures. Finally, would be
high relevant to find the JDH effect on productivity.
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Corresponding author
Alvaro Dias can be contacted at: alvaro.dias1@gmail.com
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