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The Spanish Journal of Psychology (2023), 26, e17, 1–15.
© The Author(s), 2023. Published by Cambridge University Press on behalf of Universidad Complutense de
Madrid and Colegio Oficial de la Psicología de Madrid
doi:10.1017/SJP.2023.17
The Role of Job Crafting and Psychological Capital in
the Relationship between Job Autonomy and Work
Engagement: A Serial Mediation Model
Sonia García-Merino
1,2
, Noemy Martín
1
and Carlos-María Alcover
2
1
Universidad Francisco de Vitoria (Spain)
2
Universidad Rey Juan Carlos (Spain)
Abstract. Work engagement is a scientifically consolidated variable, due to its fundamental role in business practice. To
increase work engagement in companies, it is necessary to know which variables are antecedents and how they relate to
each other. These variables include job autonomy, job crafting, and psychological capital. This research evaluates the
relationships between job autonomy, job crafting, psychological capital, and work engagement. Specifically, based on the
job demands and resources model and the conservation of resources theory, the study examines these relationships in a
sample of 483 employees, through a serial mediation model. The results show that job crafting, and psychological capital
mediates the relationship between job autonomy and work engagement. These results have practical implications for
interventions to promote employee work engagement.
Received 15 August 2022; Revised 11 May 2023; Accepted 17 May 2023
Keywords: job autonomy, job crafting, mediation, psychological capital, work engagement
The 21
st
-century world of work is characterized by high
levels of uncertainty and flexibility, with a rapidly chan-
ging labor market (Kim & Beehr, 2021). In this context,
companies are increasingly dependent on their people
and need to care about their well-being (Robijn et al.,
2020; Schaufeli, 2017). For their part, workers have to
cope with high demands, which impel them to work
harder and put more energy into their tasks (Shimazu
et al., 2020). To be more committed to their work and to
experience high levels of work engagement (Xi et al.,
2020), they need high levels of task concentration and
dedication (Beal et al., 2005). Evidence shows that
workers with high work engagement feel more ener-
getic, show higher enthusiasm for their work, and
are fully involved in their work activities; thus, they
respond to work demands more effectively and opti-
mally (Bakker, 2022; Bakker & Albrecht, 2018; Schaufeli
& Salanova, 2011).
Previous research has shown that in addition to
organizational factors, such as job autonomy (Taipale
et al., 2011), personal factors are crucial in fostering
positive states at work (e.g., Shin et al., 2018; Vogt
et al., 2016). Specifically, job crafting behaviors can
facilitate the development of psychological capital
(Kerksieck et al., 2019; Uen et al., 2021) and predict it
over time (Vogt et al., 2016), which in turn can promote
decent work and more job satisfaction for employees
(Svicher & Di Fabio, 2021), as well as increase their work
engagement. From the perspective of people manage-
ment, it is crucial to identify organizational practices
that can promote work engagement (Bakker & Albrecht,
2018). Thus, Albrecht et al. (2015) suggest the need to
How to cite this article:
García-Merino, S., Martín, N., & Alcover, C.-M. (2023). The role of
job crafting and psychological capital in the relationship between
job autonomy and work engagement: A serial mediation model.
The Spanish Journal of Psychology,26. e17. Doi:10.1017/SJP.2023.17
Correspondence concerning this article should be addressed to Sonia
García-Merino. Facultad de Educación y Psicología de la Universidad
Francisco de Vitoria. Pozuelo de Alarcón. Madrid (Spain). Programa de
Doctorado en Ciencias Sociales y Jurídicas de la Escuela Internacional de
Doctorado de la Universidad Rey Juan Carlos. Vicálvaro. Madrid
(Spain).
E-mail: s.gmerino@ufv.es
Acknowledgement: We would like to thank the Universidad
Francisco de Vitoria for the support given to the research and
Mr. Carlos Puente Costales for his work as a statistical advisor.
Funding Statement: This research received no specific grant from any
funding agency, commercial or not-for-profit sectors.
Conflicts of Interest: None.
Data Sharing: Data will be shared on request.
Authorship credit: The conceptualization of the study was performed
by SGM under coordination of CMA. The data collection was conducted
by SGM under coordination of NM. Statistical analyses were performed
by SGM under coordination of NM. SGM wrote the original draft.
Further review, editing and supervision were performed by NM and
CMA. Specifically, NM coordinated the editing and supervision of the
statistical analyses and CMA coordinated the editing and review of the
rest of the paper.
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
integrate work engagement into human resource man-
agement policies and practices. It is necessary to know
which variables, personal and organizational, are ante-
cedents of work engagement, which variables are medi-
ators, and how their combination can promote the
achievement of higher levels in the workforce.
Work engagement is a positive and satisfying work-
related state of mind (Schaufeli & Bakker, 2004) and
consists of three dimensions: Vigor, dedication, and
absorption (Schaufeli et al., 2002). According to previous
research, some of the most relevant work engagement
antecedents are job autonomy, considered as a job
resource (Halbesleben, 2010), job crafting, considered
as a set of individual strategies for designing and
redesigning one’s work (Bakker, Rodríguez-Muñoz,
et al., 2012; Demerouti, 2014; Tims et al., 2015), and
psychological capital, considered as a personal resource
(Arasli et al., 2019).
Current research finds a relationship between job
crafting, psychological capital, and work engagement
(Shin et al., 2018; Vogt et al., 2016), However, no previ-
ous research has been found that includes job autonomy
in this relationship; this is, even more, the case when job
autonomy is an antecedent to work engagement
(Taipale et al., 2011). As job demands-resources theory
postulates, work engagement experiences cannot
depend exclusively on personal resources, but should
also be considered as work resources provided by the
organization (Bakker & Demerouti, 2007; Demerouti
et al., 2001; Schaufeli, 2017). Consequently, this research
aims to identify the relationships between job auton-
omy, job crafting, psychological capital, and work
engagement. The main contribution of this study lies
in extending the analysis of the antecedents of work
engagement by exploring the joint role of job autonomy
(i.e., an organizational resource), job crafting, and psy-
chological capital (i.e., personal resources).
Theoretical Background and Hypothesis
Relationships between Job Autonomy, Job Crafting, and
Psychological Capital
Autonomy is a work resource that provides the
employee with decision latitude and independence in
planning work and determining the procedure to be
used to carry it out (Hackman & Oldham, 1975). Job
autonomy can lead to a psychological state of experi-
enced responsibility, which in turn can lead to favorable
work attitudes and behaviors (Deci et al., 2017). High job
autonomy at work implies a high level of discretion in
making decisions, such as the methods of task execution,
the choice of procedures to follow, and the scheduling
of work (Ng et al., 2008). In short, when the organization
provides workers with job autonomy, it is allowing
them to make decisions about: (a) How they do it
(method autonomy); (b) when they do it (working time
autonomy); and (c) how they make decisions (decision-
making autonomy) (Kubicek et al., 2017).
Job crafting is a specific form of proactive work
behavior that involves employees actively modifying
the perceived characteristics of their jobs (Tims &
Bakker, 2010; Wrzesniewski & Dutton, 2001). It consti-
tutes the changes that workers make to balance their
resources and job demands with their personal capabil-
ities and needs (Tims et al., 2012). Job crafting is a
proactive employee-initiated work behavior that
involves job redesign (Demerouti & Bakker, 2014;
Parker, 2014). It consists of four dimensions: a) Increas-
ing challenging job demands; (b) decreasing hindering
job demands; (c) increasing structural job resources; and
(d) increasing social job resources (Tims & Bakker, 2010;
Tims et al., 2012). Previous research shows relationships
between job autonomy and job crafting, which seems to
indicate that job autonomy is one of the main ante-
cedents of job crafting (Leana et al., 2009; Slemp et al.,
2015). A high degree of job autonomy stimulates job
crafting, by signaling to employees that they have the
freedom and opportunity to take the initiative (Petrou
et al., 2012).
Psychological capital is a positive psychological state,
a second-order construct that comprises four dimen-
sions: (a) Self-efficacy; (b) optimism; (c) hope; and
(d) resilience (Luthans & Youssef-Morgan, 2017). Con-
sistent with conservation of resources (COR) theory
(Hobfoll, 2011), psychological capital is consistent
with the notion of ‘resource caravans’–in other words,
psychological resources that can travel together and
interact synergistically to produce differentiated mani-
festations over time and across contexts (Luthans &
Youssef-Morgan, 2017). There is evidence of relation-
ships between job autonomy and psychological capital
(e.g., Peral & Geldenhuys, 2016; Shahzad, 2021).
Employees who perceive high levels of job autonomy
(considered as a job resource) tend to exhibit higher
psychological capital, a personal resource (Hobfoll,
2011).
Previous research shows the existence of a relation-
ship between job crafting and psychological capital
(e.g., Cenciotti et al., 2017; Sesen & Ertan, 2020; Uen
et al., 2021). The implementation of the work tasks on
which job crafting is based depends to a large extent on
the personal resources that constitute psychological
capital (Christian et al., 2011; Rich et al., 2017). In this
sense, based on job crafting and the dimensions of
psychological capital, employees are more likely to craft
their jobs and tasks when they are optimistic (Luthans,
Avolio, et al., 2007). In addition, employees are more
2S. García-Merino et al.
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
flexible to challenging demands when they have high
levels of resilience (Minseo & Beehr, 2021). On the other
hand, internal locus of control and the need for achieve-
ment, both of which are necessary for job crafting, are
associated with employees who show high levels of
hope (Luthans, Youssef, et al., 2007). In this regard,
some interventions in business settings to enhance job
crafting increase employee self-efficacy (van den Heu-
vel et al., 2015).
From all the above, it can be seen the existence of
scientific evidence on the direct relationships between
job autonomy and job crafting, job autonomy and psy-
chological capital, and job crafting and psychological
capital. However, no previous research has been found
that relates job autonomy, job crafting, and psycho-
logical capital together.
Relationships between Job Autonomy, Job Crafting,
Psychological Capital, and Work Engagement
Job autonomy is an important work resource that fosters
work engagement (Schaufeli & Salanova, 2007a). It has
been identified as a significant antecedent of work
engagement (Bakker et al., 2014), and there is strong
evidence of the relationship between the two constructs
(Bakker & Demerouti, 2007; de Lange et al., 2008;
Hakanen & Roodt, 2010; Schaufeli & Salanova, 2007a).
In this sense, the job demands and resources model
(JD-R) (Bakker & Demerouti, 2007; Demerouti et al.,
2001) postulates that job autonomy, as a job resource,
initiates a motivational process in employees that
results in a higher level of work engagement. Therefore,
when challenging job demands are combined with valu-
able job resources such as job autonomy, work engage-
ment levels increase (Bakker & Demerouti, 2017). Based
on these rationales and the empirical evidence also
mentioned in the previous section, we formulate the
following hypothesis:
H
1
:There will be a positive relationship between job
autonomy and employee work engagement.
On the other hand, there is evidence that job crafting
also acts as a significant antecedent of work engage-
ment (Bakker, Tims, et al., 2012; Bakker et al., 2016;
Mäkikangas, 2018;Vogtetal.,2016). Employees who
work in a position where they can design their work
procedures and strategies are more likely to experience
high levels of work engagement (Bakker, Rodríguez-
Muñoz, et al., 2012; Halbesleben, 2010;Vogtetal.,
2016). The proactive behavior involved in job crafting
makes them more likely to experience a positive mood,
characterized by vigor, dedication, and absorption
(Schaufeli et al., 2002). As can be seen from the results
obtained in these studies, the relationship between job
crafting and work engagement is well established in
previous research, both in cross-sectional and longitu-
dinal studies, and using samples from diverse work
contexts (Letona-Ibañez et al., 2021) Based on this evi-
dence, we propose the following hypothesis:
H
2
:There will be a positive relationship between job
crafting and employee work engagement.
Previous evidence shows that psychological capital
has a direct association with work engagement (Bakker
& Demerouti, 2014; Luthans et al., 2006;Xietal.,2020).
Employees with personal resources such as self-efficacy,
hope, optimism, and resilienceare characterized by high
work engagement scores (Adil & Kamal, 2016; Luthans
et al., 2008). Personal resources help employees feel
involved in their work (Arasli et al., 2019), which con-
tributes to them coping with prevailing work demands
and achieving work goals. When employees have a more
positive view of themselves through personal resources,
they feel better able to meet work demands and achieve
their goals, despite adversity (Bakker & van Wingerden,
2021). For example, the longitudinal study by Alessandri
et al. (2018) found that both absolute levels and growth
over time in psychological capital predicted subsequent
work engagement growth, demonstrating the dynamic
relationship between these variables. Based on these
rationales and previous empirical evidence, we formu-
late the following hypothesis:
H
3
:There will be a positive relationship between
psychological capital and employee work engage-
ment.
In short, the accumulated empirical evidence strongly
supports direct relationships between job autonomy
(work resource), job crafting, psychological capital (per-
sonal resources), and work engagement. If job auton-
omy is an antecedent of job crafting behaviors, and if job
crafting is related to psychological capital, as recent
research shows (e.g., Kerksieck et al., 2019; Svicher &
Di Fabio, 2021; Uen et al., 2021), it seems necessary to
investigate whether these two personal resources can
play a mediating role between job autonomy and work
engagement.
The Mediating Role of Job Crafting and Psychological Capital
There is scientific evidence that identifies job crafting as
a mediator between work engagement and job perform-
ance (Robledo et al., 2019); it is also the mediator in the
relationship between psychological capital and job sat-
isfaction (Cenciotti et al., 2017). However, no studies
have been found that analyze the mediation of job
crafting in the relationship between job autonomy and
Antecedents of Work Engagement through a Serial Mediation Model 3
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
work engagement. In terms of psychological capital,
some studies introduce this construct as a mediator
but only considered the relationship between job craft-
ing and work engagement (Arasli et al., 2019; Uen et al.,
2021). Some research provides early indications that
psychological capital mediates the relationship between
job autonomy and work engagement (Ahsan et al., 2019;
Muneeb & Maochun, 2019) but the evidence is not yet
strong. The established research relationship between
job crafting and psychological capital (e.g., Cenciotti
et al., 2017; Sesen & Ertan, 2020; Uen et al., 2021) sug-
gests that both constructs may mediate the relationship
between job autonomy and work engagement (Bakker
& Demerouti, 2007; Hakanen & Roodt, 2010; Schaufeli &
Salanova, 2007b). But as already mentioned, there are
no studies that jointly include job crafting and psycho-
logical capital as mediators in the relationship between job
autonomy and work engagement. Thus, the assumption is
that psychological capital and job crafting mediate the
relationship between job autonomy and work engage-
ment. The JD-R model is used as a basis to justify that
both job and personal resources are proposed as important
predictors of work engagement outcomes (Halbesleben,
2010). The JD-R model assumes a motivational process
in which job resources, such as job autonomy, influence
work engagement and are its antecedent (Airila et al.,
2014;Bakker,Tims,etal.,2012; Schaufeli et al., 2008;
Xanthopoulou et al., 2009b). In addition to the JD-R model,
the model we propose is based on the COR theory
(Hobfoll, 2011), which postulates that work resources
(job autonomy) foster the creation of personal resources
(psychological capital) that lead to higher levels of work
engagement over time (Xanthopoulou et al., 2009a).
Recently, the need to analyze the relationships
between the antecedents and consequences of job craft-
ing, as well as the concurrence of other variables in
those relationships, has been emphasized (Zhang &
Parker, 2019). In particular, these authors stress the
relevance of analyzing the interactive effects of context-
ual and individual resources (Zhang & Parker, 2019). In
this regard, Cenciotti et al. (2017) found reciprocal rela-
tionships between job crafting and psychological cap-
ital, while Vogt et al. (2016) found that approach crafting
predicted psychological capital and work engagement.
As a first approach to exploring these possible relation-
ships to guide further longitudinal studies (Zhang &
Parker, 2019), this study, based on these recommenda-
tions and still limited empirical evidence, aims to test the
serial mediation of job crafting and psychological capital
in this sequence (Vogt et al., 2016), on the already proven
relationship between the antecedent of job autonomy
and its outcome on work engagement.
In addition, recent research has inquired into the
variables that mediate the relationship between vari-
ousantecedentsofdemandsandresourcesandwork
engagement (Mazzetti et al., 2021), in particular
through moderated-mediated mechanisms analysis
(e.g., Tziner et al., 2019), which has yielded a more
precise and complex approach to these relationships.
In a similar vein, our study attempts to shed light on
these work engagement mediators variables through
serial mediation analysis. In doing so, we hope that our
results can be used to identify the variables that con-
tribute to facilitating work engagement and for work-
ers and organizations to enhance them according to
their capabilities.
In summary, based on the fulfillmentoftheassump-
tions analyzed in the previous section, which demon-
strate the direct relationships between the constructs
included in this study and the two theoretical models
mentioned, the following general hypothesis is proposed:
H
4
:Job crafting and psychological capital mediate
the relationship between job autonomy at work as an
antecedent of the work context and work engage-
ment as a personal outcome.
Job Crafting
(M1)
Job
Autonomy
(X)
Work Engagement
(Y)
Psychological
Capital
(M2)
Figure 1. Mediation Model of Job Crafting and Psychological Capital in the Relationship between Job Autonomy and Work
Engagement
4S. García-Merino et al.
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
Figure 1 summarizes the relationships between the
various constructs of the present research.
Method
Procedure and Sample
The sample was selected by non-probabilistic conveni-
ence sampling. Once voluntary participation in the
study had been accepted, the informed consent form
was sent to the company’s management committee,
which, although it was attached to the questionnaire
itself, was considered appropriate for it to be read by the
company’s management before the start of the study.
The distribution and application of the questionnaires
were conducted in computerized format, through the
Qualtrics platform, where the general objectives of the
study, the request for participation, and the informed
consent for the use of the data, as well as the battery of
questions in the questionnaire, were set out. The link to
the questionnaire was sent from the company’s Human
Resources department. The data were collected during
the month of November 2020.
Participation was voluntary and anonymous. Con-
sent was obtained from the participants before the ques-
tionnaire was administered. Ethical approval for this
study was granted by the Ethics Research Committee
of Rey Juan Carlos University, with the Registration
Number 211020202019120. 501 workers from a com-
pany in the telecommunications sector in the Commu-
nity of Madrid participated, of which 18 were discarded
for not completing the questionnaire in its entirety.
Therefore, the final sample was 483 workers, 65.98%
of the total company workforce.
Of the 483 participants, 300 were men (62%) and
183 were women (38%), with an average age of 40 years
(SD = 8.09), the minimum age being 23 years, and a
maximum of 71 years. The levels of education were
secondary education (1%), baccalaureate (7.7%), inter-
mediate vocational training (4.8%), higher vocational
training (15.4%), diploma (14.7%), degree (27.04%),
undergraduate (2%), postgraduate (27.3%), doctorate
(0.04%), and others (0.02%). 47.8% have been with the
company for between one and three years, 20.5% for
between three and five years, and 30.9% for more than
five years, all of them with an open-ended employment
contract and a full working day in teleworking mode.
The jobs were distributed as a technician (21.70%),
senior technical specialist (44.50%), coordinator
(20.70%), director (13.09%), and CEO (0.01%).
Measures
Work Design Questionnaire (WDQ). Developed by Mor-
geson and Humphrey (2006) and validated in the
Spanish sample by Fernández Ríos et al. (2017). The
items that assess the characteristics of the task were
used, specifically the items related to job autonomy.
This subscale consists of nine items that assess the three
dimensions of the construct: Method autonomy
(example item: “My job allows me to make decisions
about what methods I use in doing my job”), work time
autonomy (example item: “My job allows me to plan
how to do my job”), and decision-making autonomy
(example item: “My job gives me the opportunity to
exercise my personal initiative or judgment in doing
my job”). They were rated on a Likert-type scale from
1=strongly disagreeto5=strongly agree.
Work Engagement (UWES–3). The initial scale that
measured work engagement was the Utrecht Work
Engagement scale (Schaufeli et al., 2002), which con-
tains 17 items. Subsequently, Schaufeli et al. (2006)
developed an abbreviated scale (UWES–9) with nine
items. Years later, Schaufeli et al. (2019) abbreviated
the scale, resulting in the UWES–3, validated in five
countries, including Spain. The scale includes three
items assessing the three dimensions of work engage-
ment: Vigor (example item: “I feel energized at work”),
dedication (example item: “I am enthusiastic about my
work”), and absorption (example item: “I am immersed
in my work”). The participants were asked to rate each
statement using a Likert-type scale from 0 = never to 6 =
always/every day.
Job crafting (JCS). The Job Crafting scale (JCS), devel-
oped by Tims et al. (2012) and validated in Spanish in a
short version by Sora et al. (2018), was used. The scale
includes 12 items that assess the four dimensions of job
crafting: Increasing structural job resources (example
item: “In my job, I try to develop my capabilities”),
decreasing job demands (example item: “In my job, I
try to make my emotional activity less intense”),
increasing social job resources (example item: “In my
job, I ask my supervisor for advice”), and challenging
job demands (example item: “In my job, when there is
an interesting project, I offer to participate in it”). The
participants were asked to rate each statement using a
Likert-type scale from 1 = never to 5 = always.
Psychological capital (PCQ–12). It is a multidimen-
sional scale, consisting of unidimensional constructs
already used in the past: Hope (Peterson & Byron,
2008)efficacy (Stajkovic & Luthans, 1998); optimism
(Luthans & Youssef, 2007), and resilience (Maddi,
1987). These four positive psychological resources have
been conceptually and empirically combined by
Luthans and colleagues into the higher-order construct
called psychological capital (Luthans, Avolio, et al.,
2007). The initial scale that measures psychological cap-
ital was created by Luthans, Avolio, et al. (2007) under
the name of the Psychological Capital Questionnaire
(PCQ–24), and contained 24 items. Subsequently, an
Antecedents of Work Engagement through a Serial Mediation Model 5
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
abbreviated version of the scale was created by Avey
et al. (2011), with 12 items (PCQ–12), validated in a
Spanish sample by León-Pérez et al. (2017). This scale
includes 12 items that assess the four dimensions of
psychological capital: Self-efficacy (example item: “I feel
confident in contributing to discussions about my com-
pany’s strategies”), resilience (example item: “At the
present time, I consider that I have considerable job
success”), optimism (example item: “At the present
time, I am achieving the work goals I have set for
myself”) and hope (example item: “I can overcome
difficult moments at work because I have done it
before”). The participants were asked to rate each state-
ment using a Likert-type scale from 1 = strongly disagree
to 6 = strongly agree.
Control variables: Sociodemographic variables that
could be covarying with the proposed mediation model
were included, such as age, gender, educational level,
seniority, and job position. A preliminary analysis was
conducted to determine the effects of these socio-
demographic variables and, if significant effects were
found, to control for them. The results indicated a sig-
nificant relationship between age and psychological
capital (F= 59.77, p= .01), for age and work engagement
(F= 31.79, p= .015), and seniority and work engagement
(F= 23.25, p= .023). Therefore, the variables age and
seniority were included in the subsequent analysis as
control variables. Previous studies have shown that age
shapes employee attitudes and behaviors (Paul, 2012;
Zhao et al., 2021). On the other hand, job seniority
predicts employee outcomes (Boğan & Dedeoğlu,
2017; Karatepe et al., 2019).
Strategy of Analysis
A descriptive analysis of the data, reliability analysis
(Cronbach’s alpha) and McDonald’sOmegafor
scales with scores (α= < .70), EFA for multidimen-
sional scales, one-factor Harman analysis to examine
common method variance (CMV), Pearson’s bivariate
correlation analysis, and multiple serial mediation
analysis controlling for age and seniority were per-
formed. The values of the standardized normal distri-
bution (Z) have been used. To analyze whether the
direct effect between job autonomy and work engage-
ment could be mediated by job crafting and psycho-
logical capital, or whether, in the absence of direct
effects, indirect effects arise, a multiple serial medi-
ation analysis (Model 6) was conducted. Model
6 refers to the serial mediation model of the Hayes
process macro model (Hayes, 2013). The assumptions
of the serial mediation analysis were met.
SPSS Statistics v.21 was used, and for the multiple
serial mediation analysis, the same program was used,
including the PROCESS Procedure for SPSS v.2.16
module (Hayes, 2013), with 10,000 bootstrap samples
(95% confidence interval). The AMOS software was
used to evaluate the fit and parsimony indexes of the
complete measurement model and the structural model.
Results
Preliminary Analysis
Due to cross-sectional data collection, following Pod-
sakoff et al. (2003), to control for common method bias,
Harman’s test was performed for a single factor, with
10 different factors explaining 64.8% of the total vari-
ance. The first factor only captured 25.4% of the variance
of the total data, so since no single factor emerged from
the factor analysis, nor did any single factor explain
more than half of the total variance, the results suggest
that there is no CMV problem in this study (Podsakoff
et al., 2003). In addition, because of the cross-sectional
data collection, alternative models were tested to ensure
that the hypothesized model was the most parsimoni-
ous. In addition to the direct effect between autonomy
and work engagement, Model 2 hypothesized the indir-
ect effect serial mediation role of job crafting and psy-
chological capital, and model 3 did not consider direct
effect at all. The model fit was estimated using max-
imum likelihood path analysis (Hu & Bentler, 2009). Fit
indices recommended by Hu and Bentler (2009) were
used for comparison (comparative fit index [CFI] > .95
and root mean square error of approximation [RMSEA]
< .08). To compare the relative fit of the model and the
two model variations the information criterion of
Akaike (1987) was used, as recommended by Loehlin
(1998). Regarding the comparative fit, the best fitted
model according to Akaike’s information criterion was
Model 1 (the original model), which explains 24.6% of
Table 1. Fit Indices for the Three Variation Model
Models χ
2
df CFI TLI RMSEA SRMR AIC R
2
M1 6.70*2.99 .93 .07 .02 30.70 .246
M2 98.34*2 .73 .35 .31 .13 122.34
M3 102.29*3 .72 .07 .26 .12 124.29
Note. N = 483. Figures in bold meet Hu & Bentler (2009)
criteria for good fit for small samples. M1 = Multiple serial
mediation model of job crafting and psychological capital in
the relationship between job autonomy and work engagement;
M2 = Multiple serial mediation model with direct effect; M3 =
Multiple serial mediation model without direct effect; AIC =
Akaike information criterion; CFI =comparative fit index; TLI =
Tucker Lewis index; RMSEA = root mean square error of
approximation; SRMR = standardized root mean square
residual.
*p< .05.
6S. García-Merino et al.
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
the variance of work engagement. As for the overall fit,
the fit indices of the three models are presented in
Table 1. Model 1 is the only one of the three models that
shows a good fit, meeting the criteria of (Hu & Bentler,
2009) for a good fit with small samples. Models 2 and
3 had a worse fitasTable 1 shows.
Measurement Model
The reliability of the constructs was analyzed using
Cronbach’s alpha: Job autonomy (α= .81), job crafting
(α= .68), psychological capital (α= .85), and work
engagement (α= .61). McDonald’s Omega was also
calculated for scales with scores (α= < .70), obtaining
acceptable values for both of them (W
engagement scale
= .74
and W
job crafting scale
= .70).
For those multidimensional scales (Work Design
Questionnaire, job crafting scale, and psychological cap-
ital scale), a comparison was carried out between a
factorial model based on an initial Exploratory Factor
Analysis (EFA), an unifactorial model, and the one
based on the theoretical framework.
All the theoretical models used for measuring the
variables became the most parsimonious, following
Akaike’s information criterion (Akaike, 1987). In add-
ition, parsimony norm fit index (PNFI) results ranged
between .55 to .70, what means an acceptable fit (Mulaik
et al., 1989), and the appropriate use of multidimen-
sional measurements models in this research. The the-
oretical models showed the following results: The Work
Design Questionnaire, showed an arguable fit(χ
2
=197.39;
df = 24; CFI = .96; TLI = .92; RMSEA = .12; SRMR = .0597)
because the RMSEA is well above the cutoff (< .08), but
considering the sample size and the small degree of
freedom, the RMSEA is known to not fully perform
(Kenny et al., 2015). The job crafting scale showed an
adequate adjustment (χ
2
= 126.38; df = 48; CFI = .90;
TLI = .84; RMSEA = .06; SRMR =.0483) and conse-
quently confirm the validity of the instrument. Finally,
for the psychological capital scale, the results also
accounted for right adjustment (χ
2
=136.43; df = 48;
CFI = .95; TLI = .93; RMSEA = .06; SRMR =.0385).
Structural Model - Hypothesis Testing
Table 2 presents the descriptive and correlational ana-
lysis for the main variables and control variables. Cor-
relation analyses showed positive, low and significant
correlations between job autonomy and work engage-
ment (r= .29; p< .01), a result that allows for verify H
1
,
and between job autonomy and job crafting (r= .27; p<
.01). The correlation between job autonomy and psy-
chological capital was positive, moderate and signifi-
cant (r= .48; p< .01). On the other hand, there was a
positive, low and significant correlation between job
crafting and work engagement (r= .26; p< .01) and a
positive, moderate and significant correlation between
psychological capital and work engagement (r= .49; p<
.01), results that verify H
2
and H
3
, respectively. Finally,
the correlation between job crafting and psychological
capital was positive, moderate and significant (r= .39;
p< .01). Therefore, correlation analyses showed that
all correlations between the main variables of the
research were significant, which allows us to verify that
the assumptions of relationships between variables
required to test a multiple serial mediation model were
met (Hayes, 2013). Regarding control variables, correl-
ation analyses showed positive, low and significant
correlations between age and job autonomy (r= .29;
p< .01), between age and work engagement (r= .18;
p< .01), between age and psychological capital (r= .19;
p< .01) and between seniority and age (r= .30; p< .01).
To test our mediation hypothesis, a multiple serial
mediation analysis was performed with Macro Process
(Model 6), developed by Hayes (2013) with 10,000 boot-
strap samples (95% confidence). A graphical represen-
tation of the model is shown in Figure 2.
Regarding Hypothesis 4, as shown in Table 3,we
employed a multistep process to test the double medi-
ation model. In the first step (model on job crafting) job
Table 2. Descriptive and Correlational Analysis
Variables MSD1. 2. 3. 4. 5. 6.
Main variables
1. Job autonomy 4.09 .79 –
2. Work engagement 5.91 .96 .29** –
3. Job crafting 5.38 .65 .27** .26** –
4. Psychological capital 4.68 .67 .48** .49** .39** –
Control variables
5. Age 40.48 8.09 .12** .18** .02 .19** –
6. Seniority 2.83 0.87 –.01 –.05 –.05 .02 .30** –
Note. N= 483.
*p< .05. **p< .01.
Antecedents of Work Engagement through a Serial Mediation Model 7
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
autonomy reflected a positive and significant relation-
ship with job crafting (M
effect
= 0.225, SE = 0.349, t=
6.442, p< .01). In the second step (model on psycho-
logical capital), the direct effect of job autonomy on
psychological capital was significant (M
direct effect
=
.339, SE = 0.03, t= 10.25, p< .01), and the indirect effect
through job crafting was significant, M
indirect effect
= .067,
SE
boot
= 0.019, 95% CI [0.035, 0.107], suggesting that the
job autonomy-psychological capital is mediated by
job crafting. In third step (model on work engagement),
job autonomy had no significant relationship with work
engagement (M
effect
= 0.092, SE = 0.053, t= 1.729, p=.08),
job crafting had no significant relationship with work
engagement (M
effect
= 0.06, SE = 0.063, t= 0.968, p= .33),
Job Crafting
(M1)
Job Autonomy
(X) Work e n g a g e m e n t
(Y)
.08* (.35*)
.22** .61**
.29**
Psychological capital
(M2)
.33** .06*
Figure 2. Summary of the Multiple Serial Mediation Analysis Model of Job Crafting and Psychological Capital in the Relationship
between Job Autonomy and Work Engagement
Note. N = 483. The dashed line represents non-significant effects.
*p< .05. **p< .01
Table 3. Multiple Serial Mediation Analysis Model
Models and Variables BSEt p95% IC R
ajusted2
Correspondence
with hypotheses
Model on job crafting .78**
Constant 4.47 .15 30.70 < .01**
Job autonomy .23 .35 6.44 < .01**
Model on PsyCap .30**
Constant 1.69 .23 7.45 < .01**
Job crafting .298 .04 7.25 < .01**
Job autonomy .339 .03 10.25 < .01**
Indirect effect job autonomy-job crafting- PsyCap
Indirect effect .067 (Boot) .002 [.035, .107]
Model on work engagement .26**
Constant 2.37 .35 6.78 .00
Job crafting .06 .06 .97 .33 H
2
PsyCap .61 .07 9.29 .00 H
3
Job autonomy .09 .05 1.73 .09 H
1
Total effect job autonomy on work engagement
Job autonomy .35 .05 6.95 .00
Direct effect job autonomy on work engagement
Job autonomy .08 .05 1.73 .08
Indirect effect job autonomy-job crafting-PsyCap-work engagement
Standarized indirect effect .22 (Boot) .26 [.17, .27] H
4
Ratio of indirect effect to total direct effect
Job autonomy-job crafting- PsyCap -work
engagement
.74
Note: N= 438. H
1
= Hypothesis; H
2
= Hypothesis 2; H
3
= Hypothesis 3; H
4
= Hypothesis 4.
*p< .05. **p< .01.
8S. García-Merino et al.
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
but psychological capital had a significant positive rela-
tionship with work engagement (M
effect
= .612, SE = 0.06,
t= 9.29, p< .01). The total effect of job autonomy on
work engagement was positive and significant (M
total
effect
= .354, SE = 0.05, t= 6.946, p< .01), as the indirect
effect of the job autonomy-job crafting-psycap-work
engagement relationship was significant, M
indirect effect
(Standardized)
= .221, SE
Boot
= 0.26, 95% CI
Boo
[0.17/0.27].
The ratio of the indirect effect to the total effect showed
that a significant proportion of the variability is
explained by the hypothesized double mediation model
(M
ratio effect
= 0.74). In conclusion, the job autonomy-
work engagement relationship is mediated by job craft-
ing and psychological capital, supporting Hypothesis 4.
Discussion
The present study has aimed to identify the relation-
ships between job autonomy, job crafting, psychological
capital, and work engagement.
Given the importance of work engagement as an
organizational outcome (Frederick & VanderWeele,
2020), it is necessary to deepen the antecedents of work
engagement by exploring the joint role of job autonomy
(i.e., an organizational resource), job crafting, and psy-
chological capital (i.e., individual resources).
The research begins by testing relationships among
variables. The results reveal that work engagement is
related to (a) job autonomy (Hypothesis 1); (b) job craft-
ing (Hypothesis 2) and (c) psychological capital
(Hypothesis 3). This would be in line with previous
literature on the relationships between (a) work engage-
ment and job autonomy (e.g., Bakker et al., 2006; Bakker,
Hakanen et al., 2007; Halbesleben, 2010; Kao et al., 2021;
Ng and Feldman, 2014), (b) work engagement and job
crafting (e.g., Frederick & VanderWeele, 2020; Letona-
Ibañez et al., 2021; Park et al., 2020; Tims et al., 2013),
and (c) work engagement and psychological capital
(e.g., Avey et al., 2008; Grover et al., 2018; Mazzetti
et al., 2021).
The following, based on the JD-R model (Bakker &
Demerouti, 2007) and COR theory (Hobfoll, 1989), this
research has proposed that job crafting, and psycho-
logical capital mediate the relationship between job
autonomy as an antecedent of the work context and
work engagement as a personal outcome (Hypothesis
4). The results confirmed the multiple serial mediation
hypothesis. These findings are in line with the JD-R
model (Bakker & Demerouti, 2007), which assumes a
motivational process in which job resources (job auton-
omy) and personal resources (psychological capital) are
antecedents of work engagement (Airila et al., 2014;
Bakker, Tims, et al., 2012; Schaufeli et al., 2008; Xantho-
poulou et al., 2009a). The JD-R model also explains job
crafting as being mediating, along with psychological
capital. Thus, job crafting is driven by job characteristics.
Although these characteristics may differ depending on
the job (Wang et al., 2017), employees can modify the
levels of job demands and job resources (job autonomy)
of their job to better match their own skills and prefer-
ences. Some previous studies have shown how job
crafting mediates the relationship between variables
such as work engagement and job performance
(Robledo et al., 2019), and/or the relationship between
psychological capital and satisfaction (Cenciotti et al.,
2017). However, no previous research has been found
that analyses job crafting as a mediating variable
between job autonomy and work engagement, which
represents an original contribution of this study, and
whose results should be verified in further longitudinal
research (Zhang & Parker, 2019).
In turn, the results show that the effect between the
independent variable (job autonomy) and the
dependent variable (work engagement) was exclusively
indirect through the other variables that acted as medi-
ators (job crafting and psychological capital), with the
direct effect not being significant (although it was very
close to significance, p= .08). This finding implies that
job autonomy is beneficial up to a certain level and, if not
managed or involves an excess in job resources, can turn
expected positive outcomes into negative ones (Kubicek
et al., 2017; Shahzad, 2021)). In turn, this result rein-
forces the mediation hypothesis put forward in the
present study: Job autonomy requires job crafting and
psychological capital to influence work engagement.
On the other hand, the results of this study have
shown that job crafting does not significantly mediate
the relationship between job autonomy and work
engagement. In turn, the direct effect of job crafting
on work engagement is not significant. This is because
job crafting requires psychological capital. This state-
ment can be explained on t he grounds that the personal
resources contained in psychological capital are
important for the performance of the work tasks on
which job crafting is based (Christian et al., 2011;Rich,
2017). In addition, dimensions of psychological capital
help to increase levels of job crafting: (a) Employees are
more likely to craft their jobs and tasks when they are
optimistic (Luthans, Youssef, et al., 2007), (b) are more
flexible to demanding demands when they have high
levels of resilience (Minseo & Beehr, 2021), (c) manifest
internal locus of control and need for achievement
when they have high levels of hope, both necessary
for job crafting (Luthans, Avolio, et al., 2007)and
(d) employees with high levels of self-efficacy, enhance
their job crafting (van den Heuvel et al., 2015).
The results have also shown a statistically superior
indirect effect of the mediation of psychological capital
to the joint measurement of job crafting and psycho-
logical capital. These results are in line with those
Antecedents of Work Engagement through a Serial Mediation Model 9
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
obtained by Ahsan et al. (2019) and Muneeb and Mao-
chun (2019). On the other hand, there is research con-
firming psychological capital as a mediator in the job
crafting and work engagement relationship (Arasli
et al., 2019; Uen et al., 2021). This mediation is along
the lines of person-environment (P-E) fit (Edwards &
Cooper, 1990), which is based on the fact that the
strength of the relationship between job characteristics
and work behaviors depends on the level of personal
resources. P-E fit presents an individual’s desirable and
preferred work conditions (Edwards & Cooper, 1990).
Based on the JD-R model, personal resources
(i.e., psychological capital) provide individuals with
an ability to influence job demands, job resources, and
outcomes of work (Grover et al., 2018). Workers con-
sider cognitive resources as high-value assets, so they
try to preserve them (Hobfoll, 1989). Thus, when
employees strengthen their personal resources, they
will be more engaged at work. Furthermore, in accord-
ance with COR theory (Hobfoll, 2011), the results of the
present research indicate that labor resources and psy-
chological capital have created a resource caravan pro-
cess. According to this, the availability of job resources
(job autonomy) acts as a caravan passageway that trig-
gers a process of resource accumulation, which in turn
mobilizes personal resources (i.e., psychological cap-
ital). Job and personal resources foster the motivational
process, proposed by the JD-R model, which leads to a
positive state of work engagement. The fact that psy-
chological capital is a mediator with a superior indirect
effect in statistical terms also has to do with the fact that
job resources are a positive factor for work engagement,
but can act negatively if conditions such as psycho-
logical capital are not present (Muneeb & Maochun,
2019). As the level of job autonomy at work increases,
employees need more psychological resources to cope
with additional challenges in decision making
(O’Donnell et al., 2015). These results are in line with
recent research by Bakker and van Wingerden (2021), in
which personal resources intervention increases work
engagement.
This study has some limitations that should be con-
sidered. Although the sample is relatively large and
heterogeneous, it would have been interesting to be able
to apply it in other organizations, activity sectors, and
countries to assess occupational and cultural differences.
Our data are cross-sectional in nature, so the relation-
ships found should be confirmed in longitudinal studies
that include several temporal measures and test for pos-
sible causal relationships between variables. Thus, future
studies should test the present model longitudinally,
which would allow more definitive causal conclusions,
or perhaps reveal reciprocalrelationships (Cenciotti et al.,
2017). Another direction of future research could
include adding performance data, as this would provide
much information on how the investigated behaviors
influence worker outcomes. Regardless, the analyses
have revealed significant associations between the
study variables. This study extends knowledge on the
antecedents of work engagement, explaining that job
crafting, and psychological capital are factors for work
engagement. In addition, the present study sheds light
on the associations between job resources and work
engagement by providing evidence that job crafting
and psychological capital are new mediators explaining
the relationships between these variables. Moreover,
psychological capital being the strongest mediator in
statistical terms can be integrated into future research
and intervention programs to foster the influence of job
resources and improve work engagement levels in
organizations.
Business organizations need to act from a positive
level of psychology (Luthans & Avolio, 2009; Luthans,
2016; Seligman et al., 2005) and focused on increasing
work engagement. To achieve this, business environ-
ments must develop policies focused on encouraging
job crafting in work behaviors by employees. With
respect to job crafting, managers must cultivate a work
environment that fosters employee initiatives (Petrou
et al., 2012). Empowerment through job crafting, which
allows employees to adjust their work to their needs and
preferences, can promote desirable work behavior
(Demerouti et al., 2015). In addition, it is advisable to
work on developing this resource seeking and adapta-
tion that job crafting facilitates to challenge job demands
(Petrou et al., 2012). It can also be useful to strengthen
talent retention and development policies, as well as to
reduce turnover rates (Vogt et al., 2016). On the other
hand, it can be useful for HR departments to inform
employees on how to develop job crafting behaviors so
that they can modify their tasks by themselves, autono-
mously. In today’s world of work, it is not feasible for
managers to accurately predict changes and assign roles
correctly to their teams (Griffin et al., 2017). Conse-
quently, it might be interesting if job crafting could be
encouraged, rather than exhaustive task assignments.
In its favor, working on psychological capital could
become one of the business practices with more poten-
tial to be developed. Considering that psychological
capital may not be possessed by all employees, it could
be enhanced through specific training programs
(Luthans & Youssef-Morgan, 2017). Group training pro-
grams where positive psychology is used to extend
psychological capital behaviors are also recommended.
It is concluded that in order to foster work engage-
ment, it is necessary for workers to have more job
resources such as job autonomy (Bakker et al., 2014;
Bakker, 2015), as such resources enable them to pro-
actively design their tasks through job crafting
(Cenciotti et al., 2017; Kraimer et al., 2011) and to have
10 S. García-Merino et al.
https://doi.org/10.1017/SJP.2023.17 Published online by Cambridge University Press
personal resources such as psychological capital, which
allow them to cope with their daily lives (Sesen & Ertan,
2020).
The results of the present research have shown a sig-
nificant mediation of job crafting and psychological cap-
ital in the positive relationship between job autonomy
and work engagement. In this mediation, job crafting did
not mediate significantly if it was not associated with
psychological capital. On the other hand, psychological
capital had a statistically superior indirect effect than job
crafting as a mediator of the relationship between job
autonomy and work engagement.
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