Job Crafting and Intent to Leave: The Mediating Role of Meaningful Work and Engagement

Abstract

Managing turnover is an essential human resource practice. One of the modern approaches that could have the potential to increase staff retention is the stimulation of employees’ job crafting, the set of changes regarding job demands and job resources that employees proactively make. Based on self-concept theory, we expected meaningful work and work engagement to serially mediate the negative relationship between job crafting and intent to leave. A cross-sectional study was conducted on a sample of 235 Romanian employees who responded to questionnaires about all variables. The mediation hypotheses were tested with bootstrapping procedures using structural equation modeling. Meaningful work and work engagement serially mediated the negative link between job crafting and intent to leave. Our results suggest that implementing job crafting interventions could reduce employees’ intentions to leave the organization. Future studies could verify whether these interventions may represent a new management practice to effectively control turnover.

Keywords

job crafting intent to leave turnover work engagement meaningful work

Introduction

Managing turnover is an essential human resource practice, as high turnover rates can impact organizational success in several defective ways (Heavey et al., 2013). High amounts of financial resources are usually lost in replacing former employees (Cascio, 2006). Turnover also affects the company’s overall performance by causing the loss of valuable knowledge, skills, and abilities (Shaw et al., 2005) and by disrupting the existing coordination patterns between people (Summers et al., 2012). Some researchers perceive employees as the most valuable competitive asset of organizations and consider their retention to be a top priority (Cardy & Lengnick-Hall, 2011) in the “war for talent” caused by globalization and growing competition (Harvey, 2013). Indeed, most organizations are interested in retaining their high performers or difficult-to-replace employees (Allen et al., 2010).

The unemployment rate in Romania is approximately 4% (Eurostat, 2020). Turnover is high in times of low unemployment (Carsten & Spector, 1987); therefore, Romanian organizations are forced to find solutions for employee retention. Part of the employee retention strategies recommended by the literature refers to job design for increasing meaningfulness, engagement, autonomy, variety, and coworker support (Allen et al., 2010) or matching jobs to employees’ personal values and life interests to ensure that work is interesting, challenging, and meaningful (Aguinis et al., 2012). One of the modern approaches by which these suggestions can be implemented is through stimulation of employees’ job crafting behaviors. Job crafting represents the changes regarding job demands (e.g., seeking interesting and challenging new tasks) and job resources (e.g., increasing autonomy and variety) that employees proactively make according to personal needs and interests (Tims et al., 2012). Recent studies support a negative relationship between job crafting and intent to leave (Dominguez et al., 2018; Esteves & Lopes, 2017; Lichtenthaler & Fischbach, 2016), but these studies have certain limitations related to their samples, and they do not provide an explanatory mechanism or a theoretical framework for the relationship between these variables.

Considering these limitations, the purpose of this study is to investigate the link between job crafting and turnover intention based on self-concept theory (Shamir, 1991). This theory postulates that job motivation comes from the congruence among employee’s self-concept, the job, and the work context (Duchon & Plowman, 2005). Therefore, we expect the employees who craft their jobs based on their personal needs and interests to perceive their work as being more meaningful (Wrzesniewski et al., 2013), which in turn makes them more engaged (Bakker et al., 2016). Ultimately, their high level of work engagement would diminish their intention to leave the organization. This article contributes to theoretical development of turnover literature by proposing bottom-up job design as an important factor in predicting the intentions of leaving the organization. Most theoretical approaches explain personnel turnover through embeddedness (Mitchell et al., 2001), job attitudes (Griffeth et al., 2000), or the employees’ perceptions of their fit with the job (Carless, 2005) or organization (Hoffman & Woehr, 2006). These approaches usually regard employees as passive occupants of the jobs, ignoring their proactive role in changing aspects of the workplace which influence their intention to leave. We address this gap by analyzing the relationship between self-initiated job crafting behaviors and turnover intentions.

This study has practical implications for both organizational psychologists and vocational counselors. For organizational psychologist, we explore the potential of job crafting interventions as a new human resources management strategy for retaining valuable employees. On the other hand, career counseling practices in Romania were described as being limited to providing occupational and labor market information, trait-based career self-assessments, improving job search skills, and enhancing occupational placement (Hartung, 2005). Some authors argue that this description is due to the impact of communism on career development and education before Romania became a democratic country (Whitmarsh & Ritter, 2007). By adopting job crafting interventions, Romanian counselor can use a new method, adapted to the present times, to help employees decide whether they can craft their current job based on their own preferences or whether it is more appropriate to change their career path.

Job Crafting and Intent to Leave

One of the most common approaches for reducing turnover, commonly referred to as job redesign, focuses on modifying work activities in order to better fit the needs or preferences of employees (Hackman, 1980). Traditionally, job redesign has been done in a top-down manner, where the management planned a certain set of job changes and administered them to all employees in a formal manner (Jones & Harter, 2005). As Berg et al. (2013) note, this can be referred to as a “one-size-fits-all” approach, which implies that there is a universal solution for all employees in an organization. Unfortunately, these interventions don’t always meet the desired outcomes (Oldham & Fried, 2016). This might be due to various reasons including resistance (Nielsen et al., 2010) or different work preferences related to personality (Berings et al., 2004).

Considering the limitations and the risk of failure associated with top-down interventions (Aust et al., 2010), the need for more individualized approaches has emerged, thus leading to bottom-up redesign (Tims & Bakker, 2010). Bottom-up redesign is based on the employee’s own capacity to modify their job boundaries in accordance with their needs and preferences (Grant & Parker, 2009). One particular form of bottom-up redesign is job crafting (Demerouti, 2014). There are two main conceptualizations of job crafting (Lichtenthaler & Fischback, 2018), but the most popular belongs to Tims and Bakker (2010), who take a resource-based approach of the concept (Lichtenthaler & Fischbach, 2018). According to their perspective, job crafting should be understood as framed in the Job Demands-Resources model (Bakker & Demerouti, 2007) as reestablishing the equilibrium between demands and resources in order to promote motivation, health, and performance (Lichtenthaler & Fischbach, 2018). This approach proposes four fundamental ways for job crafting (Tims et al., 2012): increasing social job resources (e.g., asking a colleague for help), increasing structural job resources (e.g., asking for a training), increasing challenging job demands (e.g., volunteering in new projects), and decreasing hindering job demands (e.g., communicating less with rude colleagues).

A negative connection between increasing job challenges and turnover intention was found in a recent study (Esteves & Lopes, 2017). Increasing resources and increasing challenges are also associated with higher motivation to work past the retirement age (Lichtenthaler & Fischbach, 2016), and job crafting is negatively related to leaving intentions among trainee surgeons (Dominguez et al., 2018). Besides studies being scarce, we note that the samples used in these previous ones have certain limitations. Both Esteves and Lopez (2017) and Dominguez et al. (2018) studied health care workers, who are more prone to experience a sense of calling toward their job (Cardador et al., 2011), thus possibly buffering the effect of job crafting on turnover intentions. Further, the sample used by Lichtenthaler and Fischbach (2016) was composed of mainly elderly employees, making it hard to generalize the results to younger populations. Based on existing research, we expect to replicate the negative relationships between job crafting (i.e., increasing structural resources and increasing challenging demands) and intent to leave on an extensive sample, including people with different professions and within differentiated age categories.

Hypothesis 1: Increasing structural resources and increasing challenging demands are negatively associated with intent to leave.

The Mediating Role of Meaningfulness and Work Engagement

Recent literature reviews of meaningfulness at work suggest that some job characteristics relate to task significance and meaningful work (e.g., Lysova et al., 2019). Furthermore, employees who proactively craft these characteristics experience greater work meaningfulness (Rosso et al., 2010). These statements are supported by studies indicating a positive association between job enrichment (high levels of skill variety, autonomy, or feedback) and meaningfulness (Johns et al., 1992; May et al., 2004; Renn & Vandenberg, 1995). The relationship between job characteristics and meaningfulness at work can be explained by the self-concept theory (Shamir, 1991), which suggests that humans are not only goal-oriented but also expressive of self-concepts (first underlying motivational assumption of the theory). Other underlying assumption of the theory is that people are also motivated to retain and increase their sense of self-consistency. According to the theory, job is motivating when there is a high level of congruence among a person’s self-concept, the job, and the work context (Duchon & Plowman, 2005). Theory suggests that individuals interpret workplace activities in ways that allow them to estimate whether their need for affirmation of the self is met (Leonard et al., 1999), and when they see their roles as opportunities to express themselves, they will experience a sense of meaning (Shamir, 1991).

Employees assess the congruence between themselves and the work based on two sources of information: task feedback and social feedback (Leonard et al., 1999). According to the self-concept theory (Shamir, 1991), individuals make choices among behavioral alternatives in order to obtain feedback consistent with the self-concept from these two sources (Leonard et al., 1999). Therefore, it is expected that employees who craft their jobs in accordance with their interests and needs will receive task feedback (e.g., a higher level of perceived autonomy and variety) and social feedback (by receiving input from colleagues and supervisors) that indicate a higher congruence between self-concept and work. Indeed, job crafting has been regarded as a way of redefining work activities in personal meaningful ways, Wrzesniewski and Dutton (2001) argue that “job crafting changes the meaning of work by changing job tasks or relationships in ways that allow employees to reframe the purpose of the job and experience the work differently” (p. 186). By crafting their jobs, employees use information about themselves and their jobs in order to incorporate elements that they find intrinsically meaningful or enjoyable in their work, thus achieving a closer version of their ideal job and a greater congruence with the self-concept (Berg et al., 2013; Wrzesniewski et al., 2010). As expected, job crafting is related to meaningfulness at work (Tims et al., 2016), and increasing structural resources is positively associated with meaning-making at work (Petrou et al., 2017).

Kahn (1990) and Albrecht (2013) argued that work meaningfulness is one of the possible explanatory mechanisms by which job characteristics lead to work engagement. May and colleagues (2004) found that meaningfulness mediated the effects of job enrichment on engagement. As self-concept theory (Shamir, 1991) predicts, meaningfulness at work is positively associated with employees’ engagement (Fairlie, 2011; May et al., 2004; Soane et al., 2013). Finally, meta-analytical findings indicate a negative association between engagement and turnover (Halbesleben, 2010). Therefore, based on self-concept theory (Shamir, 1991), we expect employees who increase their resources and challenges according to their needs and interests to want to stay longer at the current workplace because they will perceive jobs as being more meaningful and they will be more engaged.

Hypothesis 2: Work meaningfulness and work engagement mediate the relationship between job crafting and intent to leave.

Method

Participants and Procedure

Participants in this study included 235 Romanian employees of various professions and different age ranges. Our sample consisted of 159 (67%) women, 75 (32%) men, and 1 gender nonconforming individual aged between 18 and 60 (M = 31; SD = 9.42). Among them, 51 (21.7%) worked in the science and technology field, 30 (12.76%) in information and communication, 28 (11.91%) in education, 14 (6%) in commerce, 13 (5.53%) in finances, 6 (2.55%) in goods production, 5 (2.12%) in health care, 5 (2.12%) in national defense, and 83 (35.31%) declared they worked in another domain. They were recruited and completed the measures online, therefore consisting a convenience sample. Participants were informed about the purposes of the study as well as assured of their responses’ confidentiality. All participation was voluntary as the subjects were informed they could withdraw from the study at any time without suffering any consequences. In general, the completing duration of the questionnaire was between 5 and 8 min. There were no missing data. After collecting our data, we used the Mplus Version 7 software (Muthén & Muthén, 1998–2012) to test our hypotheses.

Measures

Job crafting

To assess individuals’ job crafting behaviors, we used the Job Crafting Scale (Oprea & Ştefan, 2015; Tims et al., 2012). Although this scale covers all four dimensions of job crafting mentioned before, we selected only the items referring to increasing challenging job demands (e.g., “When there’s not much to do at the workplace, I see this as an opportunity to start new projects”) and increasing structural job resources (e.g., “I try to learn new things at my workplace”) for the purpose of this study. As stated in the Introduction, based on prior research, we concluded that these would be the best predictors for our model. Ten items were used in total, requiring responses on a 5-point Likert-type scale. For the Romanian version of the scale, Oprea and Ştefan (2015) reported moderate correlations between work engagement and both increasing structural resources (r = .41) and increasing challenging demands (r = .53) and between job performance and both job crafting dimensions (r = .49 and r = .55, respectively).

Work engagement

In order to measure the participants’ work engagement, we used the Utrecht Work Engagement Scale (UWES-9, Schaufeli et al., 2006; Vîrgă et al., 2009). This includes three factors, vigor (e.g., “At my work, I feel bursting with energy”), dedication (e.g., “I find the work that I do full of meaning and purpose”), and absorption (e.g., “I am immersed in my work”) with 3 items attributed to each of them that required response on a 7-point Likert-type scale. For the Romanian version of the scale, Vîrgă et al. (2009) reported significant correlations between work engagement and organizational citizenship behavior (r = .42), counterproductive work behavior (r = −.24), positive affect at work (r = .47), and negative affect at work (r = −.26).

Work meaningfulness

For measuring participants’ perception of meaning of work, we used the Work and Meaning Inventory (Steger et al., 2012). The inventory is composed of three subscales measuring Positive Meaning (e.g., “I have found a meaningful career”), Meaning-Making through Work (e.g., “My work helps me better understand myself”), and Greater Good Motivations (e.g., “The work I do serves a greater purpose”). All items require responses on a 5-point Likert-type scale. The instrument was translated into Romanian independently by two of the authors, then the translations were compared to choose the most appropriate version of the items. The developers of the scale (Steger et al., 2012) reported significant correlations with calling (r = .54), job satisfaction (r = .56), and intrinsic work motivation (r = .27).

Turnover intentions

In order to measure employee’s turnover intentions, we used 2 items adapted and translated from Hom and Griffeth (1991) and Jaros (1997) studies, namely “I often think about quitting this organization” and “I intend to search for a position with another employer within the next year.” These were also scored on a 5-point Likert-type scale. This 2-item measurement was used by Bentein et al. (2005), with good psychometric properties in terms of reliability and validity. Bentein et al. (2005) reported significant correlations with affective commitment (r = −.34), normative commitment (r = −.25), and continuance commitment (r = −.27).

Results

Measurement Model

The first step in our analysis was testing the factor structure of the measures. We conducted confirmatory factor analysis using Mplus. In our measurement model, 5 items loaded the increasing structural resources factor, 5 items loaded the increasing challenging demands factor, 10 items loaded the three components of meaningful work (i.e., 4 loaded positive meaning, 3 loaded meaning-making through work, and 3 loaded greater good motivation), 3 items loaded each component of work engagement (i.e., vigor, dedication, absorption), and 2 items loaded the intent to leave factor. Meaningful work and work engagement were declared as second-order factors, each loaded by their specific components. After allowing small error correlations within items suggested by the modification indices, the fit indices for the five factors measurement model (χ² = 760.13, df = 411, χ²/df = 1.85, root mean squared error of approximation [RMSEA] = .06, comparative fit index [CFI] = .92, Tucker–Lewis Index [TLI] = .91, standardized root mean squared residual [SRMR] = .06) showed a good fit with the data. This model fitted the data better than any alternative model, for example, the model where all items loaded on a single-factor model (χ² = 1,498.91, df = 427, χ²/df = 3.51, RMSEA = .10, CFI = .75, TLI = .73, SRMR = .08) or the model where items from work engagement and meaningful work loaded on a single factor (χ² = 1,006.38, df = 421, χ²/df = 2.39, RMSEA = .08, CFI = .87, TLI = .85, SRMR = .07). The originally proposed model showed a good fit as CFI and TLI were above .90 (Bentler, 1990), the RMSEA was .06, and the SRMR was lower than .08 (Hu & Bentler, 1999). Therefore, the measures adopted in our study were valid.

Descriptive Statistics and Correlations Between the Variables

Table 1 shows the means, standard deviations, reliabilities, and zero-order correlations among the variables included in the study (i.e., increasing structural resources, increasing challenging demands, meaningful work, work engagement, and intent to leave).

Table 1.

Means, Standard Deviations, Reliabilities, and Correlations Among Study Variables.

Variables	M	SD	1	2	3	4	5
1. Increasing structural job resources	4.38	0.48	(.65)
2. Increasing challenging job demands	3.75	0.80	.54***	(.80)
3. Meaningful work	3.79	0.80	.50***	.49***	(.90)
4. Work engagement	4.00	1.08	.56***	.59***	.71***	(.92)
5. Intent to leave	2.83	1.44	−.29***	−.21**	−.47***	−.58***	(.89)

Note. N = 235. Cronbach’s α reliabilities are in parentheses on the diagonal.

**p < .01. ***p < .001.

Hypotheses Testing

The mediation hypotheses were tested with bootstrapping procedures using Mplus. Standardized direct and indirect effects were computed for 5,000 bootstrapped samples. The hypothesized model included direct effects from increasing structural job resources and increasing challenging job demands to meaningful work. We have declared a path from meaningful work to work engagement and direct paths from job crafting components to work engagement. Finally, our model included an effect from work engagement to intent to leave and direct effects from job crafting components and meaningful work to intent to leave. The total effect from increasing structural resources to intent to leave was not significant (β = −.21, p > .05) as well as the direct effect (β = .11, p > .05). However, significant indirect effects can occur in the absence of significant total or direct effects (Rucker et al., 2011). The indirect effect was significant (β = −.32, p < .01). The relation between increasing structural resources and intent to leave, serially mediated by meaningful work and work engagement, was the only significant specific indirect effect (β = −.23, p < .01) as predicted by our hypothesis. Regarding seeking challenging demands, the total effect was not significant (β = −.21, p > .05), but we found significant relationships for the indirect effect (β = −.44, p < .001) and the direct effect (β = .32, p < .01). Two specific indirect effects were significant, the one from seeking challenges to intent to leave, through work engagement (β = −.23, p < .05) and the one that was serially mediated by meaningful work and work engagement (β = −.20, p < .01). The model, represented in Figure 1, showed a good fit to the data (χ² = 734.20, df = 409, χ²/df = 1.85, RMSEA = .06, CFI = .93, TLI = .92, SRMR = .06) supporting our hypotheses.

Figure 1.

Standardized estimates for the relationships between job crafting, meaningful work, work engagement, and intent to leave.**p < .01 and ***p < .001.

Based on the recommendations of Kelloway (2015), we tested alternative models in order to compare them with the hypothesized model. The first alternative method included paths from intent to leave to job crafting components, from job crafting components to meaningful work, and from meaningful work-to-work engagement. The fit with the data for this model was weaker than that of the original model (χ² = 801.93, df = 410, χ²/df = 1.96, RMSEA = .06, CFI = .91, TLI = .90, SRMR = .10). The second model included paths from work engagement to job crafting components, from job crafting to meaningful work, and from meaningful work to intent to leave. The fit with the data for this model was also weaker compared with the original model (χ² = 754.21, df = 410, χ²/df = 1.84, RMSEA = .06, CFI = .92, TLI = .91, SRMR = .06). Therefore, the originally proposed model had the best fit with the data. The standardized values for structural path estimates of the model are presented in Figure 1.

Discussion and Conclusions

This study investigated the relationship between two types of job crafting behaviors (i.e., increasing structural resources and challenging demands) and employees’ intention to leave their organization. The mediating roles of work meaningfulness and engagement were also tested. Our findings were in line with the hypotheses, indicating that work meaningfulness and work engagement serially mediate the relationship between job crafting and turnover intentions. Our results support the assumptions of the self-concept theory (Shamir, 1991). As expected, employees who craft their jobs according to their interests and motivation perceive their jobs as being more meaningful. These findings indicate that employees are not only goal-oriented but also expressive of self-concepts. They assess the congruence between self-concept and job by getting information from tasks and social environment (Leonard et al., 1999). When employees perceive their work activities as opportunities to express themselves, they will experience a sense of meaning, and, as the theory predicts (Shamir, 1991), they will be more engaged and want to stay in the current job for a longer period of time. Our results are in line with those of Dominguez et al. (2018), Esteves and Lopes (2017), and Lichtenthaler and Fischbach (2016) in regard to the negative association between job crafting and turnover intentions. Bakker et al. (2003) also found that job resources resulted from job crafting are predictors of commitment, which is in turn negatively related to turnover. Also, our results are in line with other studies regarding the positive association between job crafting, meaningfulness, and turnover (Sun et al., 2019; Tims et al., 2013; Wrzesniewski & Dutton, 2001).

Theoretical Implications

Bottom-up job design and work meaningfulness are often ignored as relevant predictors for intent to leave (Rubenstein et al., 2018), but our findings highlight the need to integrate these variables into the theoretical models from turnover literature. Classical models, such as job embeddedness theory (Mitchell et al., 2001), consider only the strength of the links between employees and institution, colleagues, or community. Attitudinal approaches regarding organizational commitment and job satisfaction (Griffeth et al., 2000) focus only on employees’ perceptions of work environment, supervision, coworkers, or pay. The closest perspectives to our findings are person–organization fit (Hoffman & Woehr, 2006) and person–job fit (Carless, 2005). These models refer to the match between individual characteristics and organizational characteristics or to the match between employees’ competencies/needs and jobs’ demands/benefits. However, our results indicate that employees can proactively influence the extent to which the work activity matches their own interests and motivations. Therefore, the established models in turnover literature could better explain the departures from organizations by taking into account bottom-up job design.

Self-concept has been used in career development literature by Gottfredson’s (2002) theory of self-creation, circumscription, and compromise. The theory argues that individuals go through three stages in their careers: self-creation (developing a self-concept based on abilities, personality, gender, etc.), circumscription (eliminating occupation alternatives that do not fit the self-concept), and compromise (giving up alternatives that fit their self-concept, but which are not accessible). Another theory that uses self-concept as a central construct is Super’s career construction theory (for a review, see Savickas, 2002). From this perspective, self-concept is a set of self-perceived characteristics that individuals consider relevant to work roles. Both theories underline the importance of the congruence between the self-concept and the occupation chosen by the individual. Our findings could provide a new direction for the development of the two theories, emphasizing not only choosing an occupation congruent with the self-concept but also the proactive behaviors by which employees can craft their current job to fit with the way they perceive themselves.

Practical Implications

Interventions aimed at improving employee retention focus on many aspects such as job enrichment, realistic job previews (McEvoy & Cascio, 1985), preemployment screening (Kettlitz et al., 1997), and job design (Teresi et al., 1993). Our results suggest that implementing job crafting interventions could reduce employees’ intentions to leave the organization. Unfortunately, the existing studies regarding job crafting–based interventions do not measure employees’ intention to quit as an outcome (Oprea et al., 2019). Future studies could verify whether these interventions may represent a new human resource management practice to effectively control turnover. More than involving employees in job crafting interventions as a solution to staff retention difficulties, organization can invest in training programs that teach managers leadership styles associated with followers’ job crafting behaviors. For example, existing research identified positive relationships between transformational (Wang et al., 2017), empowering (Thun & Bakker, 2018), and servant (Harju et al., 2018) leadership and followers’ job crafting. Teaching managers to adopt these leadership styles may have the potential to reduce employee departures because they stimulate them to craft their jobs. Our results should also be considered by career counselors. In order to address career development concerns, counselors may stimulate job crafting behaviors (i.e., increasing resources and challenging demands according to preferences based on self-concept), instead of directing employees’ attention to possible future vocational alternatives (Esteves & Lopes, 2017). This approach can lead to the matching of vocational interests with the current job.

Limitations and Future Directions

Despite this study’s contributions, certain limitations are also worth mentioning. First, the study was cross-sectional; therefore, the results do not allow us to assume causality between job crafting and turnover intentions because reverse relationships are possible. It is recommended that future studies adopt a more rigorous design based on multiple measurements over time. Second, variables were measured through self-report questionnaires. Thus, future studies may consider measurements other than self-reports in order to avoid the risk for common method bias (Tehseen et al., 2017). Third, we did not measure the actual turnover rates, but instead, we focused solely on employees’ intention to quit. Future studies could also opt for measuring actual turnover rates, as they offer a more accurate view of how job crafting actually contributes to employee retention. Fourth, the cognitive crafting dimension mentioned by Wrzesniewski and Dutton (2001) was not measured in our study. This is due to adopting the JD-R framework (Bakker & Demerouti, 2007) in understanding workplace situations, which does not include this prior component. It is possible that changing the way one thinks about their job could have some effects on their leaving intentions, so future studies could address the role cognitive crafting might have in employees’ turnover intention. Last, further studies could undergo certain financial analyses to identify the economic value of job crafting–based interventions in relation with turnover-associated costs. Utility analyzes were used only to estimate the financial benefits of job crafting interventions for the increase of employee performance in the health care sector (Oprea et al., 2019). By carrying out utility analyzes regarding the savings from personnel retention as a result of job crafting interventions, managers and human resource departments would be offered a clearer view of their future monetary benefits after implementing such interventions and become more prone to take action toward adopting bottom-up job design approaches (Macan & Foster, 2004).

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

Bogdan Oprea

References

Aguinis

Gottfredson

R. K.

Joo

(2012). Using performance management to win the talent war. Business Horizons, 55, 609–616. https://doi.org/101016/j.bushor.2012.05.007

Albrecht

S. L.

(2013). Work engagement and the positive power of meaningful work. In Bakker

A. B.

(Ed.), Advances in positive organizational psychology (Vol. 1, pp. 237–260). Emerald Group Publishing Limited.

Allen

D. G.

Bryant

P. C.

Vardaman

J. M.

(2010). Retaining talent: Replacing misconceptions with evidence-based strategies. Academy of Management Perspectives, 24, 48–64. https://doi.org/105465/AMP.2010.51827775

Aust

Rugulies

Finken

Jensen

(2010). When workplace interventions lead to negative effects: Learning from failures. Scandinavian Journal of Public Health, 38, 106–119. https://doi.org/101177/1403494809354362

Bakker

A. B.

Demerouti

(2007). The job demands-resources model: State of the art. Journal of Managerial Psychology, 22, 309–328. https://doi.org/101108/0268394071073311

Bakker

A. B.

Demerouti

De Boer

Schaufeli

W. B.

(2003). Job demands and job resources as predictors of absence duration and frequency. Journal of Vocational Behavior, 62, 341–356.

Bakker

A. B.

Rodríguez-Muñoz

Sanz Vergel

A. I.

(2016). Modelling job crafting behaviours: Implications for work engagement. Human Relations, 69, 169–189. https://doi.org/101177/001872671558169

Bentein

Vandenberg

Vandenberghe

Stinglhamber

(2005). The role of change in the relationship between commitment and turnover: A latent growth modeling approach. Journal of Applied Psychology, 90, 468–482. https://doi.org/101037/0021-9010.90.3.468

Bentler

P. M.

(1990). Comparative fit indexes in structural models. Psychological Bulletin, 107, 238–246. https://doi.org/101037/0033-2909.107.2.238

10.

Berg

J. M.

Dutton

J. E.

Wrzesniewski

(2013). Job crafting and meaningful work. In Dik

B. J.

Byrne

Z. S.

Steger

M. F.

(Eds.), Purpose and meaning in the workplace (pp. 81–104). American Psychological Association.

11.

Berings

De Fruyt

Bouwen

(2004). Work values and personality traits as predictors of enterprising and social vocational interests. Personality and Individual Differences, 36, 349–364. https://doi.org/101016/s0191-8869(03)00101-6

12.

Cardador

M. T.

Dane

Pratt

M. G.

(2011). Linking calling orientations to organizational attachment via organizational instrumentality. Journal of Vocational Behavior, 79, 367–378. https://doi.org/101016/j.jvb.2011.03

13.

Cardy

R. L.

Lengnick-Hall

M. L.

(2011). Will they stay or will they go? Exploring a customer-oriented approach to employee retention. Journal of Business and Psychology, 26, 213–217. https://doi.org/101007/s10869-011-9223-8

14.

Carless

S. A.

(2005). Person-job fit versus person-organization fit as predictors of organizational attraction and job acceptance intentions: A longitudinal study. Journal of Occupational and Organizational Psychology, 78, 411–429. https://doi.org/101348/096317905X25995

15.

Carsten

J. M.

Spector

P. E.

(1987). Unemployment, job satisfaction, and employee turnover: A meta-analytic test of the Muchinsky model. Journal of Applied Psychology, 72, 374–381. https://doi.org/101037/0021-9010.72.3.374

16.

Cascio

W. F.

(2006). Managing human resources: Productivity, quality of work life, profits. McGraw-Hill/Irwin.

17.

Demerouti

(2014). Design your own job through job crafting. European Psychologist, 19, 237–247. https://doi.org/101027/1016-9040/a000188

18.

Dominguez

L. C.

Stassen

Grave

W. d.

Sanabria

Alfonso

Dolmans

(2018). Taking control: Is job crafting related to the intention to leave surgical training? PLoS ONE, 13, e0197276. https://doi.org/101371/journal.pone.0197276

19.

Duchon

Plowman

D. A.

(2005). Nurturing the spirit at work: Impact on work unit performance. The Leadership Quarterly, 16, 807–833. https://doi.org/101016/j.leaqua.2005.07.008

20.

Esteves

Lopes

M. P.

(2017). Crafting a calling: The mediating role of calling between challenging job demands and turnover intention. Journal of Career Development, 44, 34–48. https://doi.org/101177/0894845316633789

21.

Eurostat. (2020). Unemployment by sex and age—Monthly average [Data file]. https://ec.europa.eu/eurostat/en/web/products-datasets/-/UNE_RT_M

22.

Fairlie

(2011). Meaningful work, employee engagement, and other key employee outcomes: Implications for human resource development. Advances in Developing Human Resources, 13, 508–525. https://doi.org/101177/1523422311431679

23.

Gottfredson

L. S.

(2002). Gottfredson’s theory of circumscription, compromise, and self-creation. In Brown

(Ed.), Career choice and development (4th ed. pp. 85–148). Jossey-Bass.

24.

Grant

A. M.

Parker

S. K.

(2009). 7 Redesigning work design theories: The rise of relational and proactive perspectives. The Academy of Management Annals, 3, 317–375. https://doi.org/10.1080/19416520903047327

25.

Griffeth

R. W.

Hom

P. W.

Gaertner

(2000). A meta-analysis of antecedents and correlates of employee turnover: Update, moderator tests, and research implications for the next millennium. Journal of Management, 26, 463–488. https://doi.org/101177/014920630002600305

26.

Hackman

J. R.

(1980). Work redesign and motivation. Professional Psychology, 11, 445–455. https://doi.org/101037/0735-7028.11.3.445

27.

Halbesleben

(2010). A meta-analysis of work engagement: Relationships with burnout, demands, resources and consequences. In Bakker

A. B.

Leiter

M. P.

(Eds.), Work engagement: A handbook of essential theory and research (pp. 102–117). Psychology Press.

28.

Harju

L. K.

Schaufeli

W. B.

Hakanen

J. J.

(2018). A multilevel study on servant leadership, job boredom and job crafting. Journal of Managerial Psychology, 33, 2–14. https://doi.org/101108/JMP-08-2016-0237

29.

Hartung

P. J.

(2005). Internationalizing career counseling: Emptying our cups and learning from each other. The Career Development Quarterly, 54, 12–16. https://doi.org/101002/j.2161-0045.2005.tb00136.x

30.

Harvey

(2013). Victory can be yours in the global war for talent. Human Resource Management International Digest, 21, 37–40. https://doi.org/101108/09670731311296519

31.

Heavey

A. L.

Holwerda

J. A.

Hausknecht

J. P.

(2013). Causes and consequences of collective turnover: A meta-analytic review. Journal of Applied Psychology, 98, 412–453. https://doi.org/101037/a0032380

32.

Hoffman

B. J.

Woehr

D. J.

(2006). A quantitative review of the relationship between person–organization fit and behavioral outcomes. Journal of Vocational Behavior, 68, 389–399. https://doi.org/101016/j.jvb.2005.08.003

33.

Hom

P. W.

Griffeth

R. W.

(1991). Structural equations modeling test of a turnover theory: Cross-sectional and longitudinal analyses. Journal of Applied Psychology, 76, 350–366. https://doi.org/101037/0021-9010.76.3.350

34.

Bentler

P. M.

(1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modelling: A Multidisciplinary Journal, 6, 1–55. https://doi.org/101080/10705519909540118

35.

Jaros

S. J.

(1997). An assessment of Meyer and Allen’s (1991) three-component model of organizational commitment and turnover intentions. Journal of vocational behavior, 51, 319–337. https://doi.org/101006/jvbe.1995.1553

36.

Johns

Xie

J. L.

Fang

(1992). Mediating and moderating effects in job design. Journal of Management, 18, 657–676. https://doi.org/101177/014920639201800404

37.

Jones

J. R.

Harter

J. K.

(2005). Race effects on the employee engagement-turnover intention relationship. Journal of Leadership & Organizational Studies, 11, 78–88. https://doi.org/101177/107179190501100208

38.

Kahn

W. A.

(1990). Psychological conditions of personal engagement and disengagement at work. Academy of Management Journal, 33, 692–724. https://doi.org/102307/256287

39.

Kelloway

E. K.

(2015). Using Mplus for structural equation modeling: A researcher’s guide (2nd ed.). Sage.

40.

Kettlitz

G. R.

Zbib

Motwani

(1997). Reducing nurse aide turnover through the use of weighted applications blank procedure. The Health Care Supervisor, 16(2), 41–47.

41.

Leonard

N. H.

Beauvais

L. L.

Scholl

R. W.

(1999). Work motivation: The incorporation of self-concept-based processes. Human Relations, 52, 969–998. https://doi.org/101177/001872679905200801

42.

Lichtenthaler

P. W.

Fischbach

(2016). Job crafting and motivation to continue working beyond retirement age. Career Development International, 21, 477–497. https://doi.org/101108/CDI-01-2016-0009

43.

Lichtenthaler

P. W.

Fischbach

(2018). A meta-analysis on promotion- and prevention-focused job crafting. European Journal of Work and Organizational Psychology, 28, 30–50. https://doi.org/101080/1359432X.2018.1527767

44.

Lysova

E. I.

Allan

B. A.

Dik

B. J.

Duffy

R. D.

Steger

M. F.

(2019). Fostering meaningful work in organizations: A multi-level review and integration. Journal of Vocational Behavior, 110, 374–389. https://doi.org/101016/j.jvb.2018.07.004

45.

Macan

T. H.

Foster

(2004). Managers’ reactions to utility analysis and perceptions of what influences their decisions. Journal of Business and Psychology, 19(2), 241–253. https://doi.org/101007/s10869-004-0550-x

46.

May

D. R.

Gilson

R. L.

Harter

L. M.

(2004). The psychological conditions of meaningfulness, safety and availability and the engagement of the human spirit at work. Journal of Occupational and Organizational Psychology, 77, 11–37. https://doi.org/101348/096317904322915892

47.

McEvoy

G. M.

Cascio

W. F.

(1985). Strategies for reducing employee turnover: A meta-analysis. Journal of Applied Psychology, 70, 342–353. https://doi.org/101037//0021-9010.70.2.342

48.

Mitchell

T. R.

Holtom

B. C.

Lee

T. W.

Sablynski

C. J.

Erez

(2001). Why people stay: Using job embeddedness to predict voluntary turnover. The Academy of Management Journal, 44, 1102–1121. https://doi.org/102307/3069391

49.

Muthén

L. K.

Muthén

B. O.

(1998–2012). Mplus user’s guide. Seventh edition. Muthén & Muthén.

50.

Nielsen

Taris

T. W.

Cox

(2010). The future of organizational interventions: Addressing the challenges of today’s organizations. Work & Stress, 24, 219–233. https://doi.org/101080/02678373.2010.519176

51.

Oldham

G. R.

Fried

(2016). Job design research and theory: Past, present and future. Organizational Behavior and Human Decision Processes, 136, 20–35. https://doi.org/101016/j.obhdp.2016.05.002

52.

Oprea

B. T.

Barzin

Vîrgă

Iliescu

Rusu

(2019). Effectiveness of job crafting interventions: A meta-analysis and utility analysis. European Journal of Work and Organizational Psychology, 28, 723–741. https://doi.org/10.1080/1359432X.2019.1646728

53.

Oprea

B. T.

Ştefan

M. C.

(2015). Scala pentru modificarea postului: Adaptare la limba română. Psihologia Resurselor Umane, 13, 39–52.

54.

Petrou

Bakker

A. B.

den Heuvel

(2017). Weekly job crafting and leisure crafting: Implications for meaning-making and work engagement. Journal of Occupational and Organizational Psychology, 90, 129–152. https://doi.org/101111/joop.1216

55.

Renn

R. W.

Vandenberg

R. J.

(1995). The critical psychological states: An underrepresented component in job characteristics model research. Journal of Management, 21, 279–303. https://doi.org/101016/0149-2063(95)90059-4

56.

Rosso

B. D.

Dekas

K. H.

Wrzesniewski

(2010). On the meaning of work: A theoretical integration and review. Research in Organizational Behavior, 30, 91–127. https://doi.org/101016/j.riob.2010.09.001

57.

Rubenstein

A. L.

Eberly

M. B.

Lee

T. W.

Mitchell

T. R.

(2018). Surveying the forest: A meta-analysis, moderator investigation, and future-oriented discussion of the antecedents of voluntary employee turnover. Personnel Psychology, 71, 23–65. https://doi.org/101111/peps.12226

58.

Rucker

D. D.

Preacher

K. J.

Tormala

Z. L.

Petty

R. E.

(2011). Mediation analysis in social psychology: Current practices and new recommendations. Social and Personality Psychology Compass, 5, 359–371. https://doi.org/101111/j.1751-9004.2011.00355.x

59.

Savickas

M. L.

(2002). Career construction: A developmental theory of vocational behavior. In Brown

(Ed.), Career choice and development (4th ed., pp. 149–205). Jossey-Bass.

60.

Schaufeli

W. B.

Bakker

A. B.

Salanova

(2006). The measurement of work engagement with a short questionnaire: A cross-national study. Educational and Psychological Measurement, 66, 701–716. https://doi.org/101177/0013164405282471

61.

Shamir

(1991). Meaning, self and motivation in organizations. Organization Studies, 12, 405–424. https://doi.org/101177/017084069101200304

62.

Shaw

J. D.

Gupta

Delery

J. E.

(2005). Alternative conceptualizations of the relationship between voluntary turnover and organizational performance. Academy of Management Journal, 48, 50–68. https://doi.org/105465/AMJ.2005.15993112

63.

Soane

Shantz

Alfes

Truss

Rees

Gatenby

(2013). The association of meaningfulness, well-being, and engagement with absenteeism: A moderated mediation model. Human Resource Management, 52, 441–456. https://doi.org/101002/hrm.21534

64.

Steger

M. F.

Dik

B. J.

Duffy

R. D.

(2012). Measuring meaningful work: The work and meaning inventory (WAMI). Journal of Career Assessment, 20, 322–337. https://doi.org/101177/1069072711436160

65.

Summers

J. K.

Humphrey

S. E.

Ferris

G. R.

(2012). Team member change, flux in coordination, and performance: Effects of strategic core roles, information transfer, and cognitive ability. Academy of Management Journal, 55, 314–338. https://doi.org/105465/amj.2010.0175

66.

Sun

Lee

J. W.

Sohn

Y. W.

(2019). Work context and turnover intention in social enterprises: The mediating role of meaning of work. Journal of Managerial Psychology, 34, 46–60. https://doi.org/101108/JMP-11-2017-0412

67.

Tehseen

Ramayah

Sajilan

(2017). Testing and controlling for common method variance: A review of available methods. Journal of Management Sciences, 4, 142–168. https://doi.org/1020547/jms.2014.1704202

68.

Teresi

Holmes

Benenson

Monaco

Barrett

Ramirez

Koren

M. J.

(1993). A primary care nursing model in long-term care facilities: Evaluation of impact on affect, behavior, and socialization. The Gerontologist, 33(5), 667–674.

69.

Thun

Bakker

A. B.

(2018). Empowering leadership and job crafting: The role of employee optimism. Stress and Health, 34, 573–581. https://doi.org/101002/smi.2818

70.

Tims

Bakker

A. B.

(2010). Job crafting: Towards a new model of individual job redesign. SA Journal of Industrial Psychology, 36, 12–20. https://doi.org/104102/sajip.v36i2.841

71.

Tims

Bakker

A. B.

Derks

(2012). Development and validation of the job crafting scale. Journal of Vocational Behavior, 80, 173–186. https://doi.org/101016/j.jvb.2011.05.009

72.

Tims

Bakker

A. B.

Derks

(2013). The impact of job crafting on job demands, job resources, and well-being. Journal of Occupational Health Psychology, 18, 230–240. https://doi.org/101037/a0032141

73.

Tims

Derks

Bakker

A. B.

(2016). Job crafting and its relationships with person–job fit and meaningfulness: A three-wave study. Journal of Vocational Behavior, 92, 44–53. https://doi.org/101016/j.jvb.2015.11.007

74.

Vîrgă

Zaborilă

Sulea

Maricuţoiu

(2009). Roumanian adaptation of Utrecht Work Engagement Scale: The examination of validity and reliability. Psihologia Resurselor Umane, 7, 58–74.

75.

Wang

Demerouti

Le Blanc

(2017). Transformational leadership, adaptability, and job crafting: The moderating role of organizational identification. Journal of Vocational Behavior, 100, 185–195. https://doi.org/101016/j.jvb.2017.03.009

76.

Whitmarsh

Ritter

(2007). The influence of communism on career development and education in Romania. The Career Development Quarterly, 56, 85–94. https://doi.org/101002/j.2161-0045.2007.tb00022.x

77.

Wrzesniewski

Berg

J. M.

Dutton

J. E.

(2010). Managing yourself: Turn the job you have into the job you want. Harvard Business Review, 88, 114–117.

78.

Wrzesniewski

Dutton

J. E

. (2001). Crafting a job: Revisioning employees as active crafters of their work. Academy of Management Review, 26, 179–201. https://doi.org/105465/AMR.2001.4378011

79.

Wrzesniewski

LoBuglio

Dutton

J. E.

Berg

J. M.

(2013). Job crafting and cultivating positive meaning and identity in work. In Bakker

A. B.

(Ed.), Advances in positive organizational psychology: Vol. 1. Advances in positive organizational psychology (pp. 281–302). Emerald Group Publishing. https://doi.org/101108/S2046-410X(2013)0000001015