The study investigated the applicability of the job demands-resources model to career development and work engagement, and examined potential gender differences. It found that career-related resources like development opportunities and supervisor support were positively associated with work engagement, which in turn was positively related to career commitment and satisfaction. There were no significant gender differences found in these relationships. The study provided support for linking job resources and engagement to career outcomes, but noted future research could examine additional career-related variables and analyze gender differences between companies.

1. An application of work engagement in the job
demands–resources model to career
development: Assessing gender differences
Yunsoo Lee ,SunHee J. Eissenstat
NUR MARDHIAH BINTI MOHD RASHID
MPP191064
Lecturer : Dr Aqeel Khan
Course : MPPB1343

2. Introduction
• Career development is one of the focal components of HRD (Swanson &
Holton, 2001), and organizations offer career development opportunities that
take the forms of internal promotion, enhanced skills and competencies, and
professional development; in return, they expect certain performance-
enhancing attitudes from their employees,such as commitment (Tansky &
Cohen, 2001).
• If one’s current job is consistent with one’s desired career development path
(good person–job fit), this may facilitate commitment and engagement, as the
job itself is helpful for personal career development.
• If this is not the case (poor person–job fit), one is more likely to explore other
jobs (Briscoe, Henagan, Burton, & Murphy, 2012). If this happens, one’s
dedication to his or her current job also decreases (Bakker & Leiter, 2010).

3. Background of study
• The purpose of this study is to investigate the
applicability of the job demands–resources (JD-R)
model to work engagement and career development
based on the extended conceptual model proposed by
Lee, Kwon, Kim, and Cho (2016).
• This study also aims to examine gender differences
within this model.
• This study adopts a multigroup analysis using a sample
from the Generations of Talent data set, which is
composed of 1,997 employees in 11 countries.

4. Researh Objective
• to empirically examine whether the JD-R model and
work engagement can be used to explain the career
development of the employees within a company. T
• to reveal whether there are gender differences. The
theories supporting this study are the JD-R model
(Bakker, Demerouti, & Sanz-Vergel, 2014) and Lee et al.’
(2016) conceptual model that extended the JD-R model
to the realm of career development.

5. Literature Review
1. The relationship between work engagement and
career-related job resources
• Bakker & Leiter, 2010 ,Using the JD-R model, many
scholars have empirically shown that work engagement
mediates the relationship between job resources and
specific outcome variables such as organizational
commitment and turnover intentions.
• Hypothesis 1: Career development opportunities are positively associated with
work engagement after controlling for perceived supervisor support and
career identity.
• Hypothesis 2: Supervisors’ support, as perceived by employees, is positively
associated with employees’ levels of work engagement after controlling for
career development opportunities and career identity.

6. Literature Review
2. The relationship between work engagement and
personal resources
• Hobfoll, Johnson, Ennis, & Jackson, Personal resources
refer to “aspects of the self that are generally linked to
resiliency”.
• Savickas, 2005, According to career construction theory,
career adaptability refers to “the attitudes,
competencies, and behaviors that individuals use in
fitting themselves to work that suits them
• Hypothesis 3: Career identity is positive associated with work engagement
after controlling for career development opportunities and perceived
supervisor support.

7. Literature Review
3. The relationship between work engagement and
outcome variables: Career commitment and career
satisfaction
• Harter, Schmidt, & Hayes, 2002, the JD-R model, work
engagement is assumed to produce desired outcomes
such as job satisfaction
• Ng, Ely, Sorensen, & Feldman,2005, Career
commitment and career satisfaction are strongly
related to each other
• Hypothesis 4: Work engagement is positively associated with career
commitment.
• Hypothesis 5: Work engagement is positively associated with career
satisfaction.

8. Literature Review
4. Gender differences in career development and work
engagement
• According to the meta-analysis of Konrad, Ritchie, Lieb,
and Corrigall (2000), men tend to rate their career
success through objective indicators, while women tend
to assess their career success in a subjective way.
• In many models that explain career success (e.g., Judge
et al., 1995), gender was an important consideration
• Hypothesis 6: There are gender differences in the paths among research
variables.
• Hypothesis 6a: There are gender differences in the effect of career
development opportunities on work engagement when controlling for
perceived supervisor support and career identity.

9. Hypothesis 6b: There are gender differences in the effect of perceived
supervisor support on work engagement when controlling for career
development opportunities and career identity.
Hypothesis 6c: There are gender differences in the effect of career identity on
work engagement when controlling for perceived supervisor support and
career development opportunities.
Hypothesis 6d: There are gender differences in the effect of work
engagement on career commitment.
Hypothesis 6e: There are gender differences in the effect of work
engagement on career satisfaction.
Hypothesis 7: There are gender differences in career development
opportunities, career identity, perceived
supervisor support, work engagement, career commitment, and career
satisfaction.

10. Method : Sample
• This study utilized the Generations of Talent (GOT) study data set
collected by the Sloan Center on Aging and Work at Boston
College. These data were collected to investigate how country-
and age-related factors affect the quality of individuals’
employment.
• The data consist of four modules and contain 718 variables. This
study analyzed Module 3, which measured all of the research
variables (e.g., work engagement) used in this study.
• A total of 2,484 employees responded to Module 3, and among
the respondents, atotal of 1,997 provided their gender. Since
gender is one of the major concerns of this study, the final
sample, then,consisted of these 1,997employees

11. Method : Sample

12. Method : Measures
1. Career development opportunity
• Career development opportunity was measured using
the knowledge scale developed by Vandenberg,
Richardson,and Eastman (1999).
• The reliability coefficient of this measurement in their
study was .90. The GOT data used one out of a possible
eight items: “I have opportunities to improve my skills
through education and training.” The present study
created a dummy variable (0 = no, 1 = yes) because this
item used a nominal scale.

13. Method : Measures
2. Perceived supervisor support
• Perceived supervisor support was measured with a scale
developed by Greenhaus, Parasuraman, and Wormley(1990). The
reliability coefficient of this measurement in their study was .93.
• The GOT data used four items out of a possible eight items:
-“My supervisor gives me helpful feedback about my performance”;
-“My supervisor assigns tasks that offer opportunities to develop skills”;
-“My supervisor cares about whether or not I achieve my career goals”; and
-“My supervisor makes sure I get the credit when I accomplish something.”
• All of the above were measuredusing a 6-point Likert scale
ranging from 1 (strongly disagree) to 6 (strongly agree).

14. Method : Measures
3. Career identity
• Career identity was measured with a scale developed by
Carson and Bedeian (1994). The reliability coefficient of
thismeasurement in their study was .81.
• The GOT data used one out of a possible four items:
“My line of work/careeris an important part of who I
am.”
• Career identity was measured using a 6-point Likert
scale ranging from 1 (stronglydisagree) to 6 (strongly
agree).

15. Method : Measures
4. Work engagement
• Work engagement is defined as “a positive, fulfilling, work-
related state of mind that is characterized by vigor,
dedication,and absorption” (Schaufeli, Salanova, González-Roma,
& Bakker, 2002, p. 74).
• Work engagement was measured with the Utrecht Work
Engagement Scale (UWES-9) developed by Schaufeli, Bakker, and
Salanova (2006).
• The reliability coefficient of this measurement in their study was
between .85 and .92 in 10 different countries.

16. Method : Measures
4. Work engagement
• The GOT data used all the items of the UWES-9:
• “At my work, I feel bursting with energy”;
• “At my job, I feel strong and vigorous”;
• “I am enthusiastic about my job”;
• “My job inspires me”;
• “When I get up in the morning, I feel like going to work”;
• “I feel happy when I am working intensely”;
• “I am proud of the work that I do”;
• “I am immersed in my work”;
• “I get carried away when I am working.”
• All of the above were measured using a 7-point Likert
scale ranging from 1 (never) to 7 (always).

17. Method : Measures
5. Career commitment
• Career commitment was measured with a scale
developed by Blau (1989). The reliability coefficients of
this measurement in Blau’s (1989) study were between
.87 and .85 at different time points.
• The GOT data used two of a possible seven items:
-“I like this line of work/career too well to give it up”;
-“If I had all the money I needed, I would still continue to
work.”
• All of the above were measured using a 6-point Likert
scale ranging from 1 (strongly disagree)to 6 (strongly
agree).

18. Method : Measures
5. Career satisfaction
• Career satisfaction was measured with a scale
developed by Greenhaus et al. (1990). The reliability
coefficient of this measurement in their study was .88.
• The GOT data used two out of a possible five items:
-“How satisfied are you with the success you have
achieved in your career?”
-“How satisfied are you with the progress you have made
financially so far?”
All of the above were measured using a 6-point Likert
scale ranging from 1 (strongly dissatisfied) to 6 (strongly
satisfied).

19. Conceptual Model

20. Analysis
• This study used the AMOS 20.0 statistical package to perform the
latent mean analysis and multigroup analysis. A full-information
maximum likelihood (FIML) was applied for handling missing values.
• The chi-squared statistic is the most basic goodness-of-fit index to
assess a model, but its null hypothesis is too strict and highly
sensitive to the sample size.
• To compensate for these shortcomings, this study used the Tucker–
Lewis index (TLI), the comparative fit index (CFI), and the root mean
square error of approximation (RMSEA) as alternatives that bring
parsimony to the model and are relatively less sensitive to the
sample size.
• The TLI and CFI represent a good fit at greater than .90, and the
RMSEA is reasonable at less than .08 and indicates a good fit at less
than .05 (Browne &Cudeck, 1993).

21. Multigroup Analysis
1. Test of configural invariance
To test configural invariance, this study analyzed the fitness of the hypothesized model.
The goodness-of-fit indices of the configural invariance model are presented in Table 5.
These indices met the recommended criteria; thus, the configural invariance model
was supported (TLI = .905; CFI = .94; RMSEA = .053).

22. Multigroup Analysis
2. Test of metric invariance
• To test metric invariance, the analysis constrained the factor pattern
coefficients between each latent variable and its measurement variables to
be equal across the two groups.
• This study constrained seven coefficients: perceived supervisor support had
three, work engagement had two, and career commitment and career
satisfaction each had one unconstrained coefficient.
• As a result of constraining, the value of chi-square increased from 736.77 to
743.88,
gaining 7 degrees of freedom. A chi-squared difference test was conducted
in order to compare the baseline model and the metric invariance model
because the metric invariance model was nested within the baseline model.

23. Multigroup Analysis
2. Test of metric invariance
• The chi-square difference, 7.11, was lower than 14.07, the value of the chi-
square difference with 7 degrees of freedom at α = .05, which means that
full metric invariance was supported.
• This implies that there is no difference between men and women in
understanding each measurement variable. The goodness-of-fit indexes of
the metric model
were slightly better than those of the baseline model (TLI = .910, RMSEA =
.051).
• The value of CFI did not change; however, CFI is generally not used during
multigroup analysis because it does not consider the complexity of amodel
(Hong et al., 2003).

24. Multigroup Analysis
2. Test of metric invariance

25. Discussion
1. The results of this study support Lee et al.’s (2016) contention that work
engagement mediates the relationship between career-related resources
and career-related outcomes.
2. The findings of this study indicate that work engagement results in career
commitment and career satisfaction.
3. These results support the fact that perceived career support (Poon, 2013)
and supervisor support (Bakker et al., 2004; Sarti, 2014) are positively
related to work engagement.
4. The results also suggest that work engagement has a positive effect on
career commitment (Barnes & Collier, 2013) and career satisfaction
(Karatepe, 2012; Laschinger, 2012).

26. Discussion
5. This study found that there are no gender differences in the structural
relationships among career development opportunities, career identity, perceived
supervisor support, work engagement, career commitment, and career satisfaction.
6. This finding contradicts Hypothesis 6, but it is an encouraging finding in the sense
that there are no gender differences in career development in companies where
men and women are provided with the same resources.
7. The resultsof the latent mean analysis also showed that the women’s means for
all the variables tended to be lower than thoseof men.
8. These results can be interpreted as suggesting that women have to invest more of
themselves in their workthan men do in order to survive in the workplace.

27. • future research needs to consider other career-related
variables affecting career commitment. For
example,studies might examine career development
support systems and career-related coworker support
as job resources,career-related self-efficacy as a
personal resource, and role clarity and autonomy as
related to or helpful for career development as job
demands.
• future research may be able to reveal gender
differences within and between companies more clearly
by adopting hierarchical linear modeling
Recommendation for Future Research