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The relationship between employees, co-workers, and the company is crucial because it determines its success in achieving its goals. This engagement is strongly influenced by job demands and work resources at the company, affecting how employees feel about their workplace’s physical, psychological, and mental conditions. High job demands with supportive work resources can increase employee motivation and create an employee’s high commitment to the company. Digitalizing all human resources information systems will make it easier for employees to achieve their work targets, so digitalization has a role in strengthening or weakening the influence of work demands and resources on employee engagement. The concept is that existing job demands should be balanced with the availability of appropriate job resources to minimize or even eliminate psychological disturbances and improve employee health. This physically and psychologically healthy condition greatly supports the ability of employees to use digital technology in the human resources management (HRM) process.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

Several job characteristics have been suggested to influence workers’ well-being. For example, Herzberg (1968) differentiated job characteristics that offset dissatisfaction such as social relations from job aspects that foster job satisfaction such as opportunities for advancement. While Hackman and Oldham (1976) focused on the motivational potential of job characteristics such as task identity and feedback, Karasek (1979) accentuated time pressure as a pivotal job demand. Together these models point out that various job characteristics may influence workers’ functioning.

Recent years have seen an explosion in the study of emotions in organizations, and although emotions play a central role in the job stress process, their role is largely neglected in empirical stressor–strain studies. Our chapter aims to build consensus in the literature by showing that discrete emotions provide a mechanism through which stressors exert their impact on well-being. By examining a larger domain of stressors, emotions, and well-being, we begin to develop and expand upon the nomological network of emotions. In an effort to build on the job demands–resources (JD-R) model, which includes both job demands (i.e., negative stimuli such as time pressure) and resources (i.e., positive stimuli such as autonomy), we include both negative and positive discrete emotions with the expectation that negative emotions will generally be linked to demands and positive emotions will be linked to resources. We also propose that there may be circumstances where demands trigger negative discrete emotions and lead to greater experienced strain, and conversely, where resources arouse positive discrete emotions, which would positively affect well-being. The model in our chapter sheds light on how discrete emotions have different antecedents (i.e., job demands and resources) and outcomes (e.g., satisfaction, burnout, performance), and as such, respond to calls for research on this topic. Our findings will be of particular interest to organizations where employees can be trained to manage their emotions to reduce the strain associated with job stressors.

Digital technologies comprehensively change work processes and working conditions. However, the use of digital technologies and the modes of collaboration between technologies and human workers differ in terms of specific work organization and automatization. Referring to the job demands-resources model (JD-R), this paper investigates job demands and resources from the workers' perspectives and develops a digital work typology according to dimensions of digitalization and forms of human–computer interaction (HCI).

The authors conducted a qualitative-empirical study with 49 interviews in four German production and logistics organizations, emphasizing different job demands and job resources for five digital work types identified.

The results indicate that job demands and resources are to be differentiated in relation to specific work contexts. In this sense, this paper presents an analysis of dimensions of technology use and the impact of technology use on working conditions through empirically analyzing job demands and resources in digital work settings.

The contribution of this paper is to empirically analyze job demands and resources in digital work settings from the workers' perspectives and to develop a digital work typology based on the dimensions of digitalization and form of HCI. This typology can set the basis for further research insights as well as management practice measures in human resources management (HRM).

Employees need a sustainable career to prolong their working lives. The ability, motivation and opportunity to work form an important basis for sustainable careers across the lifespan. However, over the lifespan of their careers employees are likely to experience several career shocks (e.g. becoming chronically ill or being fired) which might result in unsustainable trajectories. This study aims to contribute to the literature on sustainable careers by unraveling the process through which careers shocks relate to career (un)sustainability and what role perceptions of human resource practices play in the process.

Thirty-three in-depth retrospective interviews with participants of 50 years and older were conducted and analyzed using a template analysis.

Results showed that career shocks influence career sustainability through a process of changes in demands or changes in resources, which in turn, relate to changes in person–job fit. When person-job–fit diminished, the ability, motivation and opportunity to continue working decreased, whereas when person–job fit improved, the ability, motivation and opportunity to continue working improved as well. Organizations appear to be able to diminish the negative consequences of career shocks by offering job resources such as HR practices in response to career shocks.

A limitation of this study is the retrospective nature of the interviews, which could have resulted in recollection bias.

This study gives HRM practitioners insight into the HR practices that are effective in overcoming career shocks.

This study extends existing literature by including career shocks as possible predictors of sustainable careers.

It is increasingly important for organizations to respond effectively and promote positive outcomes under adverse and unstable conditions. Resilience is salient because reflects the dynamic process that enables successful results under stressful conditions. The purpose of this paper is to investigate the potential role of team resilience as the psychological mechanism that explains how job demands and job social resources are related to and enhance team performance.

Self-reported questionnaires were distributed to 1,633 employees, nested in 275 teams from 52 Spanish small and medium enterprises. Aggregated scores were employed for a team-level structural equation modeling analysis.

Results support a partial mediation model in which job social resources affect team resilience, and in turn impact team performance. No significant effects were found for job demands affecting team resilience. However, the demands×resources interaction influences team resilience, and thus the impact of resources on team resilience was attenuated by demands. In the same way, the demands×resources interaction influences team performance.

Job social resources are related to team performance, but team resilience is a significant mediator. Further research should investigate the effects of different job demands on team resilience.

The results suggest that managers should focus on developing job social resources to augment team resilience and team performance.

Managers could benefit from understanding how team resilience could be developed, given that team resilience aids to achieve positive team outcomes.

The purpose of this paper is to examine the influence of entrepreneurial orientation (EO) within the framework of the job demands-resources (JD-R) model.

The sample of N=597 white-collars in the German media and IT industry is drawn via the professional network XING. Cross-sectional mediator models are used to test the hypothesis.

The processes proposed by the JD-R model find empirical support. Job demands primarily cause exhaustion while job resources increase job satisfaction. Besides, job demands reduce job satisfaction and job resources lead to less exhaustion. An exception is found for cognitive workload which rather acts like a job resource. EO mediates these effects in a favorable way. High job resources foster EO, which in turn reduces exhaustion and enhances job satisfaction. For job demands, EO shows a negative mediation reducing the health-impairment process and increasing job satisfaction.

Future research should broach the issue of adverse effects related to extreme employee entrepreneurship and potential negative effects.

Supporting and supervising an EO may help employees to cope with modern job profiles in agile organizations.

The findings provide support for a favorable mediating role of an entrepreneurial personal resource within the JD-R model. This knowledge may be used to consider individual work orientations and to organize work in a “healthy” way.

This study aims to test the hypothesized moderated mediation process combining job resources, job demands, work engagement, job satisfaction and organizational engagement, which proposes that work engagement can be considered as a mediator between the relationship of job resources with job satisfaction and organizational engagement, and such mediation effect is moderated by level of job demand.

Data were collected from Junior Management Grade–Scale I officers of 442 branches of 27 public sector banks situated across four States in North India. The final responses stood at 704. Regression analyses was performed through the SPSS macro (developed by Preacher and Hayes, 2004) for testing of H1 and H2 on the mediation effects. H3 was tested by moderated hierarchical regression analysis. The last two H4 and H5 proposing the moderated mediation mechanism were examined in lines with the four conditions suggested by Muller et al. (2005) and Preacher et al. (2007).

It is suggested that job demands should ideally be adequate and job resources ample to deal with the former, because a suitable fit between these two aspects is related to work engagement, which would further contribute positively to job satisfaction and organizational engagement.

There is dearth of research hypothesizing the moderated mediation process proposing job demands as a moderator in job resources, work and organizational engagement and other work-related outcome relationships. Resting on various propositions and of job demands–resources (JD-R) model, and empirical outcomes of the studies of JD-R perspective, and research gaps identified, this study attempts to propose a unique model of engagement hypothesizing a moderated mediation process, where work engagement might be a mediator between the relationship of job resources with job satisfaction and organizational engagement; such mediation effect is moderated by the level of job demands.

The purpose of this paper is to gain more insight into the well‐being, health and performance of young intermediate educated employees. First, employees with low education (9 years or less), intermediate education (10‐14 years of education), and high education (15 years or more) are compared on a number of factors related to well‐being, health, and performance at work. Second, determinants of well‐being, health and performance are examined for the intermediate educated group, based on the Job Demands‐Resources model.

Data from The Netherlands Working Conditions Survey 2007 are used: the largest working conditions survey in The Netherlands. ANOVAs with post hoc Bonferroni corrections and linear regression analyses are used for the analyses.

Young intermediate educated employees differ from high educated employees with regard to job demands, job resources and health. They report less demands, but these demands still have an effect on well‐being and performance. They also report less resources, while these resources are important predictors of their health and performance: both directly and indirectly via job satisfaction and emotional exhaustion.

Cross‐sectional data are used and the theoretical model is tested using regression analyses. In a follow‐up study, longitudinal data and structural equation modelling will be used.

The study adds to the limited knowledge on young employees with intermediate education and gives insight into the processes that are important for their well‐being, health, and performance. The study shows that this group deserves the attention of both researchers and professionals.