Job crafting refers to the proactive behaviours employees engage in to modify their job characteristics (Wrzesniewski & Dutton, 2001). This process is seen as an active way for employees to reshape their roles and find better alignment with their personal preferences and goals. This may involve taking on new responsibilities to enhance personal control, fostering connections with colleagues to secure social support, or eliminating technological barriers to reduce job demands (Holman et al., 2024; Tims & Bakker, 2010). Job crafting empowers employees to take charge of their work, helping to ensure it is meaningful (Berg et al., 2013; Noesgaard & Jørgensen, 2024).

Theoretical frameworks around job crafting suggest that these self-initiated changes could lead to favourable outcomes, such as improved well-being and enhanced performance (Bruning & Campion, 2018; Holman et al., 2024). These positive outcomes are often tied to how well employees engage in the job crafting process and to how well these changes align with their personal goals and organisational expectations. Job design theories also propose that alterations in job characteristics directly influence employee outcomes (Holman et al., 2024; Parker, 2014). However, despite the growing interest in job crafting, research exploring the mechanisms through which job characteristics influence job crafting remains limited and inconsistent, highlighting a significant gap in our understanding (Holman et al., 2024; Tims et al., 2013). There are two main theoretical frameworks examining job crafting: the job identity model (Wrzesniewski & Dutton, 2001) and the job demands-resources (JD-R) model (Bakker & Demerouti, 2016). Each offers insights into the behavioural dynamics of job crafting, emphasising different aspects of employee engagement.

The first of these frameworks, the job identity model, proposed by Wrzesniewski and Dutton (2001), outlines three proactive employee behaviours aimed at enhancing job satisfaction and alignment with personal characteristics (De Gennaro, 2019):

This model highlights both the physical and cognitive alterations employees make to shape their work experiences (De Gennaro, 2019). In contrast, the JD-R model, developed by Bakker and Demerouti (2016), is framed around the concept of job crafting within the context of job demands and resources (De Gennaro, 2019). Job demands are characteristics of the job that require employee effort, and job resources are factors that help employees cope with job demands by promoting personal growth and development.

This model posits four forms of job crafting:

As the framework suggests, by balancing job demands and resources effectively, employees can optimise their work experiences, leading to greater satisfaction and personal growth. The model emphasises the importance of job crafting in navigating workplace challenges and achieving a more fulfilling work life (De Gennaro, 2019). As the study of job crafting continues to grow, it has emerged as a key area of focus in contemporary organisational behaviour research, offering valuable insights into job design (Lazazzara et al., 2020). Managers, however, face the challenge of tailoring roles to suit every individual. Job crafting provides a framework for employees to tailor their responsibilities to reflect their unique strengths while maintaining the core functions of their roles (Tims et al., 2012; Zhang et al., 2021).

Furthermore, Holman et al. (2024) suggest that job crafting influences employee outcomes (well-being and positive job attitudes), implying that organisations should foster an environment that encourages these behaviours. However, while the positive outcomes of job crafting are clear, there remains a gap in understanding the underlying motivations driving employees to engage in job crafting (Lin & Meng, 2024). Job crafting is not merely spontaneous; it requires deliberate effort and employee motivation (Randel et al., 2024). While it could lead to improved performance and professional growth, it might also provoke negative reactions from colleagues because of potential disruptions in established workflows (Dong et al., 2023).

Lazazzara et al. (2020) conducted a meta-synthesis that categorised job crafting motives into proactive (motivated by personal or job-related goals) and reactive (motivated by coping with challenges). While this synthesis contributed significantly to the field, it lacked clarity in defining individual and job-related goals, which led to theoretical overlap (Lazazzara et al., 2020). Furthermore, while some quantitative studies have incorporated motivational perspectives to predict job crafting behaviours, such as the influence of external rewards (Masood et al., 2023), most have focused solely on intrinsic or extrinsic motivations, often neglecting the nuances of introjected regulation. This lack of nuance in understanding motivation hinders the field’s ability to comprehensively explain why job crafting occurs in the workplace (Masood et al., 2023). Moreover, as job crafting becomes increasingly interconnected with colleagues’ influences and perceptions, this area remains underexplored (Dong et al., 2023; Tims & Parker, 2020). Given the complexities surrounding motivation in job crafting, understanding how individual traits and skills align with job demands becomes crucial. This is where the concept of person-job fit plays a pivotal role.

Person-job fit is one of the most crucial concepts discussed in organisational psychology. It denotes the closeness between a person’s qualifications or abilities and the job requirements (Rodgers, 2000). A strong person-job fit means people have enough knowledge, skills, and ability (KSAs) to meet job demands (Basher et al., 2024). Recent studies indicate that factors such as personality traits, organisational culture, and career goals significantly influence person-job fit. Therefore, organisations prioritising person-job fit in their recruitment processes are more likely to attract and retain talented employees who thrive in their roles (Basher et al., 2024; Rodgers, 2000).

The multifaceted nature of person-job fit encompasses multiple definitions, enhancing its relevance in the workplace. For instance, Stich (2021) emphasises the alignment between job characteristics and individual traits, suggesting that person-job fit is assessed based on how well job attributes resonate with personal preferences (Langgeng et al., 2021). According to Pudjiarti and Hutomo (2020), person-job fit is the alignment between an individual’s technical competencies and a job’s requirements (Chhabra, 2015; Enwereuzor et al., 2018).

Expanding on this, Yang et al. (2019) define person-job fit as the compatibility between a person’s abilities and job demands, while Rajper et al. (2019) describe it as the intersection of job requirements and KSAs. Together, these definitions emphasise that individuals with strong person-job fit are more likely to perform, thereby increasing organisational productivity (Langgeng et al., 2021). Sylva et al. (2019) introduce a dual dimension of person-job fit: needs-supplies fit (NSF), and demands-abilities fit (DAF), with NSF focusing on how well individual needs align with job benefits, and DAF addressing the match between abilities and job demands (Chhabra, 2015; Enwereuzor et al., 2018).

There are many antecedents of person-job fit, which can be categorised into five categories: individual, organisational, leadership, customer, and technology factors (Langgeng et al., 2021). For example, job crafting enables individuals to reshape their roles to align with their strengths, leading to greater job satisfaction and performance (Langgeng et al., 2021). Similarly, research by Djaganata and Pusparini (2024) highlights the importance of aligning employees’ values, skills, and work culture with their roles. This alignment mediates the relationship between person-job fit and the decision to stay at a job (Djaganata & Pusparini, 2024).

Organisational strategies that align employee values, skills, and culture with their roles also play a crucial role in shaping employees’ reasons for staying, as retention remains a problem for management (Allen et al., 2010). Positive person-job fit is linked to enhanced job satisfaction, work engagement, and employee retention; individuals who perceive a strong fit are more likely to invest effort and commitment, resulting in improved performance and greater job tenure (Mulyani & Pareke, 2024). Conversely, poor person-job fit can lead to negative outcomes, such as job stress, burnout, and turnover intentions, as misalignment fosters feelings of inadequacy (Mulyani & Pareke, 2024). Therefore, addressing person-job fit is vital for both individual well-being and organisational effectiveness.

By fostering an environment that aligns individual and job characteristics, organisations can enhance their competitive advantage and cultivate a positive workplace culture (Khan et al., 2023). Given the significant impact of person-job fit on attitudes and behaviours, organisations should strategically leverage this concept to optimise their work environments. This leads us to consider the literature on job embeddedness, which can be promoted by person-job fit, as highlighted by Mulyani and Pareke (2024).

Job embeddedness is a multifaceted concept that refers to the forces that keep employees attached to their jobs, encompassing three primary dimensions: links, fit, and sacrifice (Mitchell et al., 2001; Peltokorpi & Allen, 2024). Job embeddedness is further defined as the interconnectedness of employees within their social networks, which binds them in their roles (Fuchs, 2022; Ramaite et al., 2022).

This construct comprises three dimensions:

This concept is often analysed through the lens of Conservation of Resources (COR) theory, which posits that individuals are motivated to acquire, protect, and allocate valued resources, such as employment status and personal skills (Hobfoll, 1989; Peltokorpi & Allen, 2024). Factors influencing job embeddedness include on-the-job elements, such as positive work relationships and supportive management, as well as off-the-job factors, such as strong community ties and personal life circumstances (Allen et al., 2016; Kiazad et al., 2015). Furthermore, research within the JD-R framework shows that when employees adjust their tasks and relationships, it leads to higher engagement levels and a more profound sense of job embeddedness (Arasli et al., 2019). In addition, empirical evidence has demonstrated that stronger person-job fit is associated with increased job embeddedness (Van Vianen, 2018). These findings collectively suggest that job crafting not only enhances person-job fit but also contributes to deeper job embeddedness.

Previous literature indicates that mediation analysis is crucial in studying associations between independent variables and dependent variables. A study by Marange et al. (2025) determined the mediating effects of job crafting on the relationships between workplace social support and employee mental health. Similarly, employees who craft in their work are seen as more embedded in their roles, as they are fulfilled and engaged (Teng & Chen, 2025). Job embeddedness and job crafting are influenced by various direct and indirect effects (Yun et al., 2024). This study investigates the indirect mechanisms through which job crafting leads to job embeddedness.

Based on the above information, the following objectives and hypotheses are formulated:

The general objective of this study was to investigate the relationships between job crafting, person-job fit, and job embeddedness among employees within an agricultural organisation. Specifically, the study aimed to:

The following hypotheses were formulated for the study:

This study employed three primary measures to assess the constructs of job crafting, person-job fit, and job embeddedness. In addition, basic demographic information was collected to characterise the study sample. Job crafting was assessed using the Job Crafting Scale created by Tims et al. (2012). The scale includes 21 items across four dimensions: increasing structural job resources, increasing social job resources, increasing challenging job demands, and decreasing hindering job demands. Each item is rated on a 5-point Likert scale: 1 = never, 2 = seldom, 3 = regularly, 4 = often, and 5 = very often. Previous studies, such as Rudolph et al. (2017), have confirmed the scale’s reliability and validity, with Cronbach’s alpha coefficients ranging from 0.79 to 0.88 for its dimensions.

Person-job fit was measured using the Person-Job Fit Scale developed by Cable and DeRue (2002), which evaluates the subjective alignment between individuals and their jobs. This scale utilises a 5-point Likert scale ranging from 1 = strongly disagree to 5 = strongly agree. The scale has consistently demonstrated strong reliability and validity, with Cronbach’s alpha coefficients typically exceeding 0.80 in earlier research (Ehrhart, 2006; Lu et al., 2014).

Job embeddedness was evaluated through the Job Embeddedness Scale developed by Clinton et al. (2012). This scale consists of 12 items measuring four dimensions: job fit, job links, job sacrifice, and community fit. It employs a 5-point Likert scale, where 1 = strongly disagree and 5 = strongly agree. The scale has exhibited high internal reliability and strong test-retest reliability in prior studies (Clinton et al., 2012). In the results section, measuring instruments used to measure job crafting, person-job fit, and job embeddedness were analysed individually to provide a comprehensive overview of the findings.

The target population for this quantitative study comprised permanently employed white-collar staff members across various subsidiaries of a single agricultural umbrella company, ranging in age from 18 years to 64 years. A stratified random sampling technique was employed to ensure a representative sample from each subgroup within the target population. The sample was accessed through established communication channels managed by the Human Resources Department, in which a Microsoft Forms link was sent out via email to staff to answer this anonymous survey. This approach was intended to maximise response rates and enhance the diversity of the sample. Consequently, a total of 225 responses were incorporated into the analysis for this study, all of which met the established inclusion criteria, thereby enhancing the overall reliability and validity of our findings.

To address the research questions and hypotheses, this study employed a quantitative approach, utilising both descriptive and inferential statistical analyses. Data analysis was conducted using JASP software 0.19.1 (JASP software 0.19.1 [Computer software] (2024). JASP Team). Descriptive statistics were used to summarise the sample characteristics, assess reliability, examine the distribution of variables, and evaluate discriminant validity. Inferential statistics were then applied to test the hypotheses and explore the relationships between the study variables. Specifically, correlation analysis was conducted to assess the associations between job crafting, person-job fit, and job embeddedness. Multiple linear regression was used to investigate the predictive relationships among job crafting, job embeddedness, and person-job fit. Finally, mediation analysis was performed to examine the indirect effect of job crafting on job embeddedness through person-job fit.

The research sample included 102 female and 123 male white-collar participants. The average tenure of the participants in the research study was 8 years and 3 months, with the shortest employment period being 1 month and the longest reaching 38.5 years.

The study involved a diverse participant pool comprising 140 white participants, 43 black African participants, 22 Indian participants, 17 mixed-race participants, two Asian participants, and one participant classified as ‘Other’.

Ethical clearance to conduct this study was obtained from the North-West University Economic and Management Sciences Research Ethics Committee (Ref. No. NWU-00567-24-A4).

Table 1 presents the descriptive statistics for job crafting, person-job fit, and job embeddedness. The mean scores for the three constructs suggest relatively positive perceptions of job-related factors among respondents. The mean score is determined by the Likert scale (1–5) used to measure the constructs. The mean score of 3.63 indicates a moderately positive level of job embeddedness, suggesting that respondents do feel a sense of embeddedness in their work. The descriptive statistics indicate a mean of 3.39 for job crafting, indicating a moderate level of engagement among participants. A relatively higher aligning person-job fit mean score of 3.89 suggests that satisfactory job fit is more readily perceived. The standard deviations are comparable across the measures of job embeddedness (0.57), job crafting (0.53), and person-job fit (0.57).

Cronbach’s alpha ranges from 0 to 1, with ideal values typically between 0.7 and 0.9 (Cresswell & Cresswell, 2018). To ensure that the data are reliable, the Cronbach’s alpha coefficient should exceed 0.70 (Cronbach, 1951; DeVellis, 2017). The job crafting scale demonstrated strong reliability with a Cronbach’s alpha of 0.88, indicating consistent measurement of the intended construct. The person-job fit scale showed the highest internal consistency among the three constructs, with a Cronbach’s alpha of 0.90, suggesting highly reliable items for assessing the construct. Lastly, the job embeddedness scale achieved a Cronbach’s alpha of 0.81, indicating good internal consistency.

Table 2 includes the results of the correlation analysis, which revealed significant positive relationships between job embeddedness, job crafting, and person-job fit. Specifically, the correlation between job embeddedness and person-job fit was the strongest (r = 0.56, p < 0.001), followed by the relationship between job crafting and person-job fit (r = 0.45, p < 0.001), and the correlation between job embeddedness and job crafting (r = 0.40, p < 0.001). All three relationships were statistically significant, indicating a positive association between the variables. In terms of effect size, the correlation between job embeddedness and person-job fit (r = 0.56) represents a medium to large effect, according to Cohen’s (1992) criteria, while the correlations between job crafting and person-job fit (r = 0.45) and job embeddedness and job crafting (r = 0.40) indicate medium effects. These findings offer strong evidence for the hypothesised relationships and suggest that higher levels of job crafting and person-job fit are associated with greater job embeddedness, with the strongest association observed between person-job fit and job embeddedness.

Based on these results, H1 is supported.

To test the predictive capacity of job crafting and person-job fit in explaining job embeddedness, a regression analysis was utilised. This provided a deeper understanding of how well these predictors explain the variability in job embeddedness, beyond the relationships identified by the correlation analysis (Beers, 2024). To explore this possibility, Table 3 presents results from a multiple linear regression examining the relationships between job crafting and person-job fit as predictors of job embeddedness, providing a deeper understanding of how these variables contribute to the overall explanation of job embeddedness.

Multiple linear regression (MLR) generalises simple linear regression by allowing multiple predictor variables in a model to account for a single outcome dependent variable (Bottenberg & Ward, 1963; Marill, 2004). Linearity and homoscedasticity were assessed through visual inspection of scatterplots and residual plots, which indicated linear relationships and constant residual variance. Independence of errors was assumed based on the cross-sectional nature of the data and participants’ independent responses.

Multicollinearity was examined using tolerance and variance inflation factor (VIF) values. The tolerance values for both job crafting and person-job fit were 0.80, while the VIF values were 1.25. These values fall within the acceptable thresholds, indicating that multicollinearity was not a concern in the regression model.

The results indicate that both job crafting and person-job fit are statistically significant predictors of job embeddedness. Specifically, the unstandardised regression coefficients show that job crafting has a positive effect on job embeddedness (β = 0.21, p = 0.002), while person-job fit has a stronger positive effect (β = 0.48, p < 0.001). Standardised coefficients (Betas) reinforce these findings, with job crafting having a moderate effect on job embeddedness (β = 0.19) and person-job fit showing a stronger effect (β = 0.47).

For H2a, the unstandardised coefficient for job crafting is β = 0.21 (p = 0.002), indicating a positive relationship between job crafting and job embeddedness after controlling for person-job fit. The standardised coefficient (β = 0.19) suggests a moderate effect. This supports the hypothesis that job crafting plays an important role in explaining variations in job embeddedness.

Similarly, the results for H2b, the unstandardised coefficient for person-job fit, indicate β = 0.48 (p < 0.001), indicating a strong positive impact on job embeddedness after controlling for job crafting. The standardised coefficient (β = 0.47) is larger than job crafting’s Beta, suggesting that person-job fit has a stronger relative effect on job embeddedness. This finding suggests that when employees’ skills and abilities align more closely with their job requirements, they experience greater job embeddedness. Therefore, person-job fit not only significantly predicts job embeddedness but also has a more substantial effect compared to job crafting.

For H3 (Job Crafting will indirectly influence job embeddedness through person-job fit), a mediation analysis was used to investigate the indirect mechanisms through which job crafting leads to job embeddedness. Mediation analysis is a statistical technique used to determine whether the effect of an independent variable on a dependent variable is transmitted through a mediator variable (MacKinnon et al., 2012).

The results of the mediation analysis are presented in Table 4. This analysis also aimed to examine whether person-job fit is a mediator between job crafting and job embeddedness in this study. More specifically, this study examined whether the influence of job crafting on job embeddedness is indirect through person-job fit, thus casting light on the mechanism linking job crafting to job embeddedness. It was found that person-job fit relates strongly to job embeddedness, with a path coefficient of 0.47, indicating a positive, strong relationship: the higher the perception of person-job fit, the higher the job embeddedness. This relation is significant with a z-value of 7.75 and a p-value of < 0.001. This positive effect is corroborated by a 95% CI (0.35–0.59).

In addition to this direct relationship, job crafting also directly influences job embeddedness, with a path coefficient of 0.37. This suggests that while job crafting does have a positive effect on job embeddedness, the relationship is somewhat weaker than the one between person-job fit and job embeddedness. The z-value for this path is 3.20 with a p-value of 0.001, indicating statistical significance. The 95% confidence interval (0.14–0.59) confirms that the effect is meaningful and reliable, although not as strong as the indirect effect through person-job fit.

The estimated indirect effect is 0.40, indicating that job crafting positively influences job embeddedness by affecting person-job fit. The statistical significance of this mediation effect is strong, with a z-value of 5.39 and a p-value of < 0.001. The 95% confidence interval (0.25–0.54) does not include zero, confirming that the mediation effect is both statistically significant and practically meaningful. Because both the direct and indirect effects are significant and are similar in size, the pattern reflects partial mediation.

The path coefficient between job crafting and person-job fit indicates a strong positive association (0.85). This suggests that job crafting may be strongly related to perceived PJF, with those who engage in job crafting reporting higher PJF than those who do not. In addition, the association between person-job fit and job embeddedness is also moderate, with a path coefficient of 0.47. Workers who feel a stronger fit with their work are more likely to feel embedded in their positions.

Figure 1 indicates that while job crafting has a direct positive effect on job embeddedness (a path coefficient of 0.37), it is also partially mediated by person-job fit. This finding suggests that job crafting enhances employees’ person-job fit, thereby increasing job embeddedness. When organisations encourage job crafting behaviours among their employees, they not only help them feel more integrated into their jobs but also strengthen their attachment to the organisation. H3 is therefore partially supported.

This study highlights job crafting as a proactive behaviour that enables employees to better match their jobs with their personal strengths, values, and interests (Tims et al., 2022). Organisations can promote job crafting by presenting job redesign methods that create space for employees to design their jobs and roles (Tims & Akkermans, 2020). Offering development programmes that suit employees and meet their personal objectives will increase employees’ satisfaction and job embeddedness. Job crafting is known to enhance attachment to one’s job, which organisations can build by enabling employees in their job crafting efforts (Tims & Akkermans, 2020).

Organisations should prioritise improving person-job fit by ensuring that recruitment processes align candidates’ abilities and values with job demands (Basher et al., 2024; Rodgers, 2000). Furthermore, offering opportunities for skill development and regular assessments of job fit will help employees feel more embedded in their roles. This approach will strengthen employee commitment and attachment to the organisation, reducing turnover. The study shows that job crafting indirectly influences job embeddedness through person-job fit. Incorporating job crafting activities can be combined with initiatives aimed at improving person-job fit by providing opportunities within their roles that employees would like to change, while ensuring those roles align with their capabilities (Tims & Akkermans, 2020). The organisations may design roles in accordance with employees’ personal goal commitment and virtues based on flexible work mobility and further task reassignments (Tims et al., 2022). Development programmes that aid employees in developing in their roles can enhance person-job fit, thereby embedding them in their roles within the organisation. A holistic approach that encourages not only job crafting but also person-job fit becomes mandatory to ensure high levels of job embeddedness. Fostering a culture that is open to job crafting, as well as making sure jobs fit with employees’ strengths and values could be beneficial (Arasli et al., 2019).

Essentially, organisations comprised of large white-collar workforces in agricultural domains may implement job crafting and fit-enhancing practices to strengthen job embeddedness. When all of these are interlinked, the organisation has a better chance of creating a culture in which employees are more committed to both their work and the organisation. In agriculture, for example, job embeddedness is critical to reducing turnover; in particular, these practices are indispensable (Shah et al., 2020). Organisations that promote job crafting and person-job fit will nurture more engaged, happy, and connected employees in their jobs and within the organisation.

The study used a cross-sectional design, which limits the ability to draw causal conclusions. Longitudinal studies would provide more insight into the direction and degree of change in these relationships (Caruana et al., 2015). The reliance on self-reported data introduces biases, such as social desirability bias and common method variance, which may distort the results (Podsakoff et al., 2003). The sample was drawn from a single agricultural organisation, limiting the generalisability of the findings. A more diverse sample would enhance the external validity of the results.

As job crafting is an emergent process, the mechanisms guiding the relationships among job crafting, person-job fit, and job embeddedness remain unclear. The directionality and temporal sequencing of these relationships are uncertain, and other indirect effects, such as whether person-job fit mediates the relationship between job crafting and job embeddedness, warrant more attention. Moreover, the study focuses on individual-level factors, although organisational and contextual factors are also significant, including leadership style and team dynamics, which have not been adequately investigated (Tims et al., 2013). The negative outcomes of job crafting, such as role ambiguity and burnout (Berg et al., 2013), are also understudied.

Future research should address these limitations by using longitudinal designs, incorporating multiple data collection methods to reduce bias, and exploring the dynamic nature of job embeddedness (Maxwell & Cole, 2007). Understanding the organisational context and potential negative consequences of job crafting will provide a more comprehensive view of these relationships (Wrzesniewski & Dutton, 2001). Despite these limitations, the study makes a significant contribution to understanding job crafting, person-job fit, and job embeddedness in the agricultural sector.