Inspiring teacher creativity through leader-teacher exchange (LMX): a job demands-resources perspective

Objectives: We examined the associations among job demands and resources, work engagement, and psychological distress, adjusted for time-invariant individual attributes. Methods: We used data from a Japanese occupational cohort survey, which included 18,702 observations of 7,843 individuals. We investigated how work engagement, measured by the Utrecht Work Engagement Scale, was associated with key aspects of job demands and resources, using fixed-effects regression models. We further estimated the fixed-effects models to assess how work engagement moderated the association between each job characteristic and psychological distress as measured by Kessler 6 scores. Results: The fixed-effects models showed that work engagement was positively associated with job resources, as did pooled cross-sectional and prospective cohort models. Specifically, the standardized regression coefficients (β) were 0.148 and 0.120 for extrinsic reward and decision latitude, respectively, compared to -0.159 and 0.020 for role ambiguity and workload and time pressure, respectively (p < 0.001 for all associations). Work engagement modestly moderated the associations of psychological distress with workload and time pressure and extrinsic reward; a one-standard deviation increase in work engagement moderated their associations by 19.2% (p < 0.001) and 11.3% (p = 0.034), respectively. Conclusions: Work engagement was associated with job demands and resources, which is in line with the theoretical prediction of the job demands-resources model, even after controlling for time-invariant individual attributes. Work engagement moderated the association between selected aspects of job demands and resources and psychological distress.

Aim/purpose – This study aims to develop a model of the relationships between job resources (autonomy, recognition), personal resources (self-efficacy), and work engage- ment among academic staff. Moreover, the moderation of job demand was also exam- ined in relation to the association between these constructs. Design/methodology/approach – In the context of survey research, 554 questionnaires were distributed using a simple random sampling technique in public secondary schools of seven districts across Punjab, Pakistan, out of which 398 questionnaires were consid- ered usable for the research. To analyze the data, the structural equation modeling meth- od was applied through PLS-SEM software. Findings – This study found that recognition and self-efficacy have a significant and positive impact on work engagement. Furthermore, the study revealed that academic staff’s work engagement was not significantly affected by job autonomy. Regarding the moderation analysis, no moderating effect was found on the association between job resources, self-efficacy, and work engagement. Research implications/limitations – This study contributes to the existing knowledge on the JDR model of work engagement and has several implications. The current study holds practical importance for individuals in all fields, especially those in the educational industry. It is recommended that future studies expand the relationship between these variables across a range of industries. Future research may consider other relevant fac- tors and longitudinal studies as alternatives to cross-sectional observational studies. Originality/value/contribution – This study makes a significant contribution to the work engagement literature by examining how job resources and self-efficacy affect work engagement while moderating job demands. To increase the work engagement of academic staff, this study presents a fresh approach to optimal management, enhancing the implementation of job and personal resources that increase work engagement. Keywords: Job resources, self-efficacy, job autonomy, recognition, job demand, work engagement. JEL Classification: M10, M12, M19

Purpose The purpose of this study is to shed light on the job resources and demands of employees working in virtual teams and the impact of these job factors on their work engagement levels. Specifically, the authors focus on identifying the differing significance of employee job resources and demands on their virtual work engagement levels. Design/methodology/approach A qualitative approach grounded on abductive analysis is used to arrive at the findings. The methods for data collection include participant observation and semistructured interviews of 27 software engineers in the Indian information technology sector, working with virtual teams. Findings The authors identified the virtual-work-induced job demands and resources. Primarily, the authors found 14 job factors related to high and low levels of individual virtual work engagement, and classified them under eight aggregate dimensions: psychosocial hurdles, collaboration challenges, leadership and operational issues, dehumanization under job demands, supportive leadership, personal resources, alternate sources of income and learning goal orientation under job resources. Consequently, the authors built an importance–frequency work engagement map based on how these job factors are related to low and high levels of work engagement. Research limitations/implications This study’s qualitative nature limits the generalizability of the findings. Hence, further studies are encouraged to corroborate the findings. There is also a possibility of the social desirability bias that could have affected the results as participants may have perceived an element of risk in sharing all their honest feelings and perceptions. This may have especially been the case for those with higher status or positions in the company. Practical implications The findings suggest practical measures either to engage employees in their free time or to improve loyalty. There is a clear potential for the organization and virtual leader to communicate effectively about the expected goals, arrange informal interactions and reduce scrutiny of monitoring, thereby increasing the remote workers’ resources. Originality/value The originality of this study comes from multiple factors. First, the authors highlight ta contextual adaptation of the job demands-resources (JD-R) model into a virtual team context. By extension, the authors examine “how much” does both the job resources and demands contribute to the wellbeing of the employees working in virtual teams. Second, the authors construct an importance–frequency work engagement map (specifically for the virtual work context) based on the findings, which categorizes the observed resources and demands into four quadrants. The authors propose that this map could be a possible extension to the JD-R model, highlighting the differing significance of each resource and demand to employee work engagement.

This chapter outlines the building blocks of the job demands–resources (JD‐R) theory, a theory that has been inspired by job design and job stress theories. Whereas job design theories have often ignored the role of job stressors or demands, job stress models have largely ignored the motivating potential of job resources.JD‐R theory combines the two research traditions, and explains how job demands and (job and personal) resources have unique and multiplicative effects on job stress and motivation. In addition,JD‐R theory proposes reversed causal effects: whereas burned‐out employees may create more job demands over time for themselves, engaged workers mobilize their own job resources to stay engaged. The chapter closes with a discussion of possibleJD‐R interventions.

Introduction: The growth of gig work has transformed the contemporary labor market, provided flexibility and independence but also subjected workers to high stressors like job insecurity, economic uncertainty, and irregular workloads. Gig workers work in various sectors, such as ridesharing, food delivery, freelancing, and on-demand services, and usually encounter distinctive occupational hazards. Gig Workers' Well-being (GWW) Model, based on the Job Demands-Resources (JD-R) model and Psychological Capital (PsyCap) theory, presents a systematic approach to understanding job demands and resources and their effect on stress resilience, mental well-being, and job performance among gig workers. This research explores how resilience interventions can reduce stress and improve work engagement and productivity among gig workers. Objectives: The main aim of this research is to create and test a multi-dimensional stress resilience framework that explains the dynamic interaction of multiple influences on wellbeing among gig workers. More specifically, the research intends to explore how job demands can intensify burnout while job resources promote work engagement, and to investigate the dual nature of gig-related factors that can benefit or detract from job performance. Furthermore, the study aims to investigate the contribution of technostress in exacerbating burnout, evaluate the effectiveness of boundary management in enhancing work engagement, and identify the degree to which resilience is responsible for enhanced job performance. Through this holistic examination, the study aims to offer detailed insights into the stress and coping processes in the gig economy, ultimately guiding strategies to enhance the wellbeing and performance of gig workers. Methods: A qualitative research design was used to obtain rich insights into the well-being of gig workers. A stratified random sampling strategy provided representative diversity across work categories, demographics, and geographic regions. Data were collected through structured online questionnaires distributed through LinkedIn, social media groups, and gig work platforms. The questionnaire contained validated scales assessing stress levels, financial security, work-life balance, resilience, and well-being. 400 questionnaires were distributed and 338 returned (84.5% response rate). After excluding incomplete or invalid responses, the final sample of 323 gig workers was analyzed. Statistical analysis using IBM SPSS 25.0, including correlation and regression analysis, was conducted to examine the relationships between job demands, burnout, resilience, and work engagement. Results: Correlation analysis indicated significant relationships between the most important variables. Job demands were positively correlated with job resources (r =.900, p &lt;.01), indicating that as stressors, resource needs also increased. Burnout had significant correlations with job demands (r =.489, p &lt;.01) and technostress (r =.804, p &lt;.01), supporting the negative effect of workload unpredictability. Regression analysis showed that job demands strongly predicted burnout (β = 0.489, R² = 0.239, p &lt;.000), whereas job resources positively affected work engagement (β = 0.415, R² = 0.172, p &lt;.000). Gig-specific factors also significantly contributed to the formation of job performance (β = 0.368, R² = 0.135, p &lt;.000). In addition, technostress strongly raised levels of burnout (β = 0.476, R² = 0.227, p &lt;.000), whereas resilience helped job performance to the extent of β = 0.499, R² = 0.289, p &lt;.000, highlighting its significance when managing stress. Conclusions: The results highlight the intricate interaction between job demands, resilience, and performance in the gig economy. Digital stressors and high job demands are sources of burnout, which is detrimental to well-being. Nevertheless, job resources such as autonomy, skill development, and social support improve work engagement and reduce stress. The GWW Model highlights the importance of resilience in mediating stress outcomes and proposes that interventions like boundary management, adaptive coping, and financial security programs can enhance mental health and performance. Policy measures should aim to augment gig workers' access to social security, training, and mental health care. By building resilience, gig platforms can establish a more sustainable and supportive work culture, guaranteeing long-term well-being and productivity.

The aim of this study was to gain insight in the importance of job demands and resources and the validity of the Job Demands Resources Model across sectors. We used one-way analyses of variance to examine mean differences, and multi-group Structural Equation Modeling analyses to test the strength of the relationships among job demands, resources, burnout, and work engagement across the health care, industry, service, and public sector. The four sectors differed in the experience of job demands, resources, burnout, and work engagement, but they did not vary in how (strongly) job demands and resources associated with burnout and work engagement. More attention is needed to decrease burnout and increase work engagement, particularly in industry, service, and the public sector. The Job Demands-Resources model may be helpful in this regard, as it is valid across sectors.

Work engagement within hospitals may be impacted by job demands and job stress, underscoring the necessity to augment work resources as a protective measure. Initial investigations conducted at Hospital X have revealed a deficiency in work engagement, particularly in the absorption aspect. This study seeks to assess the effects of job demands and job resources on work engagement, with job stress serving as a mediating factor. Employing a quantitative survey methodology with a cross-sectional design, the study involved 104 inpatient nurses as participants. The method used is the Three Box Method and statistical analysis. The findings indicate that work engagement escalates with increased job resources, while higher job demands correlate with decreased work engagement. Furthermore, enhancing job resources has the potential to alleviate job stress, whereas elevated job demands are associated with heightened job stress levels. Notably, work engagement diminishes with escalating job stress. Through the mediation of job stress, job resources, and job demands, there is a discernible impact on work engagement.

Job demands, resources, and stress among staff in after school programs: Neighborhood characteristics influence associations in the job demands-resources model

PurposeThis paper sets out to examine proactive personality in relation to job demands, job resources and engagement.Design/methodology/approachThe current study employed a two‐wave complete panel study among 794 Dutch government employees. Based upon the Job Demands‐Resources (JD‐R) model, previous studies, job crafting theories, and Conservation of Resources (COR) theory, hypotheses on the associations of proactive personality with job demands, resources, and engagement were developed.FindingsAnalyses revealed that proactive personality was associated with an increase in engagement 18 months later. Moreover, proactive employees perceiving high social support reported the highest levels of engagement over time.Research limitations/implicationsA first shortcoming is that proactive personality was only measured at one point in time, which restricted the testing of causal relationships of proactive personality with engagement. Second, this study only measured engagement as outcome measure and third variables may have affected the associations of proactive personality with job demands and resources and engagement. Third, only small effect sizes of proactive personality (and job demands and resources) on engagement over time were found. With regard to theoretical implications, this study suggests a refinement of the JD‐R model by perceiving proactive personality as a personal resource which coincides with job resources such as social support and/or is triggered by (low) external job demands in increasing engagement.Practical implicationsSince this study's findings suggest that proactive personality is a personal resource with beneficial effects on employees' levels of work‐related engagement, employers are advised to promote the behavior expressed by proactive employees. When employees are under challenged due to a low level of quantitative job demands or when they want to optimize their work environment in case of high job demands, proactive personality may have a positive impact on their engagement over time, in particular when combined with high levels of support from their colleagues and supervisor.Originality/valueThis study's value consists of its innovative effort to relate proactive personality to engagement 18 months later. In addition, the longitudinal design of this study made it possible to examine the associations of proactive personality, job demands and resources with engagement over time.

Key drivers of nurse burnout and work engagement in Europe: A cross-sectional dominance analysis.

Organisations within the banking industry are increasingly confronted with attraction and retention challenges within their Information Technology (IT) divisions, driven by an increase in demand for skilled resources within the market. Therefore, the primary objective of the study was to explore the impact of job resources and job demands on work engagement and employee turnover intentions within the IT division of a South African bank. The Job Demands-Resources (JD-R) model was applied as theoretical framework to identify the unique job resources and job demands driving work engagement and turnover intentions of employees within this highly specialised section of the South African banking industry. Quantitative data was collected from 239 IT professionals via a self-administered, web-based survey measuring work engagement, job demands and resources, and turnover intentions. After confirmation of the factor structures of each of the variables, the direct and indirect relationships between the variables were analysed. The results indicate statistically significant relationships between job resources, work engagement and turnover intentions. Job demands moderated the relationship between job resources and work engagement, whilst work engagement mediated the relationship between job resources and turnover intention. By applying the JD-R model as a theoretical framework for the study, the unique job resources and job demands as drivers of work engagement and turnover intentions of IT employees could be highlighted to direct the development of focused work engagement and retention strategies.

Bank DKI melakukan perubahan sistem kerja demi terjaganya produktivitas kerja selama Pandemi COVID-19 yang berpotensi mengurangi keterikatan kerja. Penelitian ini bertujuan melihat peran variabel job demand, job resources, job satisfaction, terhadap work engagement. Peneliti melakukan regresi terhadap variabel job demand, job resources, job satisfaction, dan work engagement. Mediasi dilakukan antara job demand dan job resources terhadap work engagement oleh job satisfaction. Purposive sampling dilakukan dengan jumlah 181 karyawan Bank DKI. Hasil penelitian menunjukkan bahwa seluruh variabel, baik job demand, job resources, dan job satisfaction signifikan memprediksi work engagement. Efek mediasi kepuasan terjadi baik pada variabel job demand maupun job resources. Bank DKI has changed the work system in order to maintain work productivity during the COVID-19 Pandemic so that it has the potential to reduce employee attachment. This study aims to see the role of variables of job demand, job resources, job satisfaction, and employee work engagement. Researchers regression of the variables of job demand, job resources, job satisfaction, and work engagement. Mediation is carried out between job demand and job resources for work engagement mediated by job satisfaction. Purposive sampling was carried out with a total of 181 employees of Bank DKI. The results showed that all variables, both job demand, job resources, and job satisfaction significantly predicted work engagement. The satisfaction mediation effect occurs both on the job demand and job resources variables.

The purpose of this study is to examine the relationship between contextual work-related factors on the one hand, in terms of job demands (i.e., risk factors) and job resources (i.e., protective factors), and work-family conflict (WFC) in teachers on the other. Building on the Job Demands-Resources (JD-R) model, we hypothesized that job demands, namely qualitative, and quantitative workload, are positively associated with WFC in teachers. Moreover, in line with the buffer hypothesis of the JD-R, we expected job resources, in terms of support from supervisor (SS), job autonomy (JA), and participation in decision making (PDM), to affect this association, which is expected to be stronger when job resources are low. The study was conducted in an Italian secondary school. Overall, 122 teachers completed a self-report questionnaire aimed at determining WFC, as well as job demands and resources. The hypothesized relationships were tested using moderated multiple regression. The results of this study largely support our predictions. First, both aspects of workload were positively associated with WFC. Secondly, job resources, including SS and PDM, buffered this association, which was stronger when resources were low. On the contrary, JA did not buffer the association between workload and WFC. Overall, the results of this study are consistent with the JD-R model and contribute to the understanding of work–family conflict among teachers. More specifically, our study suggests that teachers with high levels of job resources, namely SS and PDM, can effectively cope with job demands, in terms of both qualitative and quantitative workload, thus preventing negative consequences such as conflict between work and family domains. Interventions aimed at preventing WFC among teachers should encourage organizations to optimize the balance between job demands and resources, as well as the identification and training of the workers at risk of WFC.

PurposeThe purpose of this paper is to investigate how just-in-time (JIT)-related job demands, problem-solving job demands and soft lean practices (SLPs) jointly influence employee well-being in terms of work engagement and exhaustion.Design/methodology/approachBased on the job demands-resources model, lean-related job characteristics were classified as resources or demands, and a set of hypotheses was developed to test their effect on work engagement and exhaustion, including the potential interaction between job resources and demands. The hypotheses were tested using moderated hierarchical regression and structural equation modelling, based on data from 138 workers.FindingsSLPs act as job resources in a lean company, increasing work engagement and reducing exhaustion. Conversely, JIT-related job demands act as a hindrance, reducing work engagement and increasing exhaustion. However, SLPs can reduce the effect of JIT-related job demands on exhaustion, and JIT-related job demands may enhance the positive effects of SLPs on work engagement.Research limitations/implicationsThe study provides no conclusive evidence on the hypothesized role of problem-solving as a challenge job demand.Practical implicationsThe results can guide practitioners’ understanding of how to implement lean without harm to employee well-being.Originality/valueBy employing a well-grounded psychological model to test the link between lean and well-being, the study finds quantitative support for: the buffering effect of SLPs on exhaustion caused by JIT-related job demands, and for the role of JIT as a hindrance. These novel findings have no precedent in previous survey-based research. In addition, it reveals the importance of studying SLPs at an individual level, as what matters is the extent to which workers perceive SLPs as useful and supportive.

Objective This research examined the work-related ill- and well-being of Finnish sport coaches and the associations of job demands and resources with burnout and work engagement. Our study was based on the Job Demands-Resources (JD-R) model. The JD-R model proposes that job demands relate especially to burnout and job resources relate especially to work engagement. Methods Finnish coaches (N = 499) within top-level sports completed a questionnaire measuring burnout, work engagement, job demands and resources. Results The results of hierarchical regression analyses showed that burnout was explained with job demands, but also lack of job resources added the explanation rate almost equally. The most important single contributor to burnout was lack of positive challenge at work. Work engagement was explained by job resources, from which positive challenge at work together with mastery of work were the strongest contributors. In addition, decision demands contributed slightly to the explanation of work engagement. Conclusions The results suggest that in the work of sport coaches, job resources or lack of them are more essential than job demands to explain both burnout and work engagement.