Development and validation of the job crafting scale
Highlights
► We developed and validated a generic job crafting scale. ► Job crafting is about self-initiated changes in job demands and job resources. ► Job crafting is helpful to attain and/or optimize employee's personal (work) goals. ► Job crafting scale shows convergent validity with proactive behavior constructs. ► Job crafting scale shows criterion validity with peer-rated outcome measures.
Section snippets
Theoretical background
Although the term ‘job crafting’ was coined by Wrzesniewski and Dutton in 2001, the idea of job crafting was already mentioned over 20 years ago by Kulik, Oldham, and Hackman (1987). The latter authors suggested that employees may redesign their jobs on their own initiative with or without the involvement of the management, which is in line with the definition that Wrzesniewski and Dutton proposed (see also Oldham & Hackman, 2010). Accordingly, job crafting may take several forms. First,
Study 1: scale development and explorative test
The goal of the first study is to develop and test a generic scale that can be used to quantitatively measure employee job crafting. Although job crafting is conceptually appealing, there has been little systematic effort to empirically examine job crafting behaviors. In developing a scale that is applicable to different occupations, we aim to encourage more empirical research on job crafting. We first describe the process of constructing the scale and then present the exploratory results of
Procedure and participants
Data on the Dutch job crafting scale (JCS) were collected using an online questionnaire on a Dutch website. The study was announced on the homepage of the website that is well-known in The Netherlands for its online self-tests and coaching to people who are employed or searching for a job. Via a link provided on the homepage, participants were directed to the introduction of the study and invited to participate in the survey. The questionnaire was in Dutch and online available for one month.
Exploratory factor analysis
We used principal factor analysis (maximum likelihood) with oblique rotation in SPSS to examine whether the three factors could be meaningfully distinguished from each other. As a criterion to retain factors, those factors that had an Eigenvalue > than 1 were retained. In addition, within factors we retained items that loaded .35 or higher on the expected factor (Costello and Osborne, 2005, Floyd and Widaman, 1995). Factors that consisted of only one or two items were deleted and also items that
Study 2: confirmatory factor analysis and convergent validity of the JCS
In this study, we first examine whether the four-factor structure (i.e., increasing social job resources, increasing structural job resources, increasing challenging job demands, and decreasing hindering job demands) can be reliably replicated in two new samples using confirmatory factor analysis. We hypothesize that the four-factor model will fit the data best as compared to two alternative models: a one-factor model and the originally hypothesized three-factor model (Hypothesis 1). We
Procedure and participants
We collected data in two new Dutch samples. For Sample 1, data were collected through a link on the homepage of a Dutch website that offers a wide variety of psychological tests. The website is daily visited by people interested in personality tests, intelligence tests, and/or career interest tests. The questionnaire was announced in the newsletter from the website. Participants could start the questionnaire by clicking on the respective link in the newsletter. Participants in this sample
Confirmatory factor analysis
In order to test Hypothesis 1, whether the four-factor solution also fits best in these two new samples, we used multigroup confirmatory factor analysis within the AMOS software package (Arbuckle, 2005). With multigroup analysis it is possible to test the same model in two separate samples simultaneously. The results of this analysis yields one set of fit statistics for overall model fit (Byrne, 2004).
To assess model fit, five indices were used: chi-square/df ratio (χ²/df), as well as the
Conclusion and discussion
The first goal of Study 2 was to examine whether we could replicate the four-factor structure of the JCS found in Study 1 in two new samples. Using confirmatory factor analysis we indeed found that this four-factor model is the best fit to the data compared with the initial three-factor model and a one-factor model. Furthermore, the JCS showed to be highly invariant, indicating robustness of the scale. Only two covariances were not invariant in the samples meaning that they showed a different
Study 3: criterion validity of the JCS
The aim of the final study was to examine the criterion validity of the JCS. Criterion validity will be achieved when the scale relates to an external criterion that seems to be a result of job crafting (cf. Cronbach & Meehl, 1955). We focused on work engagement, employability, and in-role performance, all rated by colleagues. Work engagement is expected to be an outcome of job crafting. This hypothesis is based on the findings that job resources and challenging job demands predict high levels
Participants and procedure
Several organizations in The Netherlands were contacted to participate in Study 3. A contact person within each organization formed dyads of two colleagues who regularly worked together. The contact persons were instructed to form dyads of employees who would be able to rate each other on work behaviors and performance. The participants knew that they would fill out a questionnaire about the colleague but did not know the content of the questionnaire. Both employees first filled out the
Results
To test the hypotheses, we calculated partial correlations to control for supervisory position and educational level. We found partial support for Hypothesis 1, in which we predicted significant positive correlations between the job crafting dimensions and work engagement. The results showed that the dimensions increasing social and structural job resources and increasing challenging job demands correlated significantly with work engagement (see Table 4). Overall, the correlations varied
Conclusion and discussion
In Study 3, we examined the correlations of self-ratings of job crafting behavior with peer-ratings of the outcome variables work engagement, employability, and job performance. In general, we can conclude that the dimensions increasing social and structural job resources and increasing challenging job demands correlated significantly positively with work engagement, employability, and performance. The fourth dimension, decreasing hindering job demands, showed a different pattern of
General discussion
A literature review by Tims and Bakker (2010) revealed that there is no valid measure of job crafting yet whereas more and more researchers report about the necessity of proactive employee behaviors for employee well-being (Berg et al., 2008, Wrzesniewski and Dutton, 2001) and organizational performance (Crant, 2000, Parker, 2000). The newly developed and validated generic job crafting scale (JCS) may help researchers to empirically examine this phenomenon more often and to gain more knowledge
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