The current study aimed to test how workload, via workaholism, impacts job performance along with the complex interplay of perfectionistic concerns and work engagement in this mediated relationship. A two-wave, first and second stage dual-moderated mediation model was tested in an SEM framework. Results based on a sample of 208 workers revealed a complex and nuanced relationship among the studied constructs, such that the simple mediation model was not significant, but the indirect effect was negative, nonsignificant, or positive conditional on both moderators. The results offer interesting theoretical and practical implications for future studies to be conducted in this area of research. In particular, lower levels of perfectionistic concerns were associated with a positive relationship between workload and workaholism, and lower levels of work engagement were related to a negative link between workaholism and job performance. Findings suggest work engagement should be monitored and promoted by managers, especially when workload, and consequently, the possible risk of workaholism, cannot be avoided.

The ongoing epidemiological crisis has suddenly steered us towards a new futuristic work scenario in which most service sector employees work remotely, which could be a permanent reality for most service sector employees. This paper focuses on the strategic role that leadership could play in the radical change process that is taking place in work environments. Particular attention was paid to the role of ‘middle managers’ who perform an important function as a link between the strategic vision of top management and the workforce. In addition, special attention was paid to gender differences in work-life dynamics, which are particularly relevant in countries with traditional cultural identities. As this is a conceptual contribution, the most recent studies on this specific role of middle managers have been taken into account and embedded in the current scenario. Therefore, the main contribution in terms of originality was that the current review aimed to leverage such a legacy of knowledge and create a system of evidence-based practical implications for effectively supporting change in organizational culture through the identification of the most appropriate middle management leadership models for remote working that could prevent and/or limit any psychosocial risks (e.g., workaholism and technostress) and longer-term outcomes such as sustainable work-life interface.

This study aimed to explore a possible process explaining the relationship between workaholism and sleep disorders, including two mediators: work–family conflict and emotional exhaustion. Moreover, since a possible buffering role of work engagement was recently proposed against the detrimental effects of workaholism, the aim was to examine the moderating role of work engagement in the relationship between workaholism and several outcomes such as work–family conflict, emotional exhaustion, and sleep disorders. Two models were tested using conditional process analysis for testing direct and indirect effects on a sample of 395 employees: (1) a serial multiple mediation model, and (2) the same serial multiple mediation model including the moderating role of work engagement. Results showed a significant mediating effect of both work–family conflict and emotional exhaustion. Moreover, work engagement moderated the relationship between workaholism and work–family conflict and the relationship between workaholism and emotional exhaustion. This work contributes to the understanding of the process underlying the relationship between workaholism and sleep disorders and to the literature reporting the possible protective role of work engagement on the negative outcomes of workaholism. Practical implications are also discussed.

Purpose: The purpose of this paper is to investigate the role of organisational career growth (OCG) in the process linking organisational work–family support and work–family conflict. Design/methodology/approach: Since previous contributions reported theoretical and empirical evidence of possible gender differences in this process, a moderated mediation model was examined including gender as moderating variable of both direct and indirect effects. Conditional process analysis was used to test the hypotheses on a sample of 507 Italian employees who were also parents. Findings: Results showed a significant mediation effect of OCG in the relationship between organisational work–family support and work–family conflict. Furthermore, evidence of a moderated effect of gender was found in the way that the negative direct effect of organisational work–family support on work–family conflict was stronger among women, whereas the direct effect of OCG on work–family conflict was significant only for men. Originality/value: This is the first study addressing the possible negative effect of OCG on a specific target of employees.

During the pandemic, the occurrence of extreme working conditions (e.g., the sudden shift to remote work, isolation, and the slowdown of the work processes) exacerbated several phenomena, such as increased workaholism and stress due to technological devices; that is, technostress. Literature on the onset of these phenomena during the pandemic highlighted a possible interplay among them; however, there is still a dearth of knowledge about the direction of the relationship between workaholism and technostress. The present study assessed the relationship between workaholism and technostress through a two-wave cross-lagged study using path analysis in SEM (Structural Equation Modeling). The study was conducted in Italy during the pandemic, and a total of 113 Italian employees completed the online survey at each wave. Results showed that workaholism at Time 1 was a significant predictor of technostress at Time 2 (β = 0.25, p = 0.049), while the reversed causation was not supported (β = 0.08, p = 0.22). These findings may help employees and organizations to better understand the phenomena of technostress and workaholism and develop strategies to prevent the consequences of excessive and compulsive work and to improve the balanced use of technology for their daily activities.

The rapid diffusion of Artificial Intelligence (AI) is transforming job characteristics, raising important questions about how to implement these technologies in organizations in ways that support employee well-being and performance. Drawing on the High-Involvement Management framework, this study examined employee-centered Artificial Intelligence implementation (ECAII) practices (defined as transparent communication, consultation, and training initiatives) as strategic levers to foster positive employee outcomes during Artificial Intelligence-driven transformations. Survey data were collected from 168 Italian white-collar employees who actively used Artificial Intelligence in their work. Structural equation modeling was employed to test direct and indirect relationships among employee-centered Artificial Intelligence implementation practices, work meaningfulness, job satisfaction, and job performance, as well as the moderating role of personal attitudes toward AI. Results showed that employee-centered Artificial Intelligence implementation practices had significant direct effects on both job satisfaction and performance, as well as indirect effects through work meaningfulness. Latent moderated mediation analyses further revealed that these indirect effects were stronger among employees with more positive attitudes toward Artificial Intelligence. Overall, the findings highlighted the importance of employee-centered strategies for enhancing meaningfulness and fostering positive outcomes during technological change. This study contributed to Human Resource Management (HRM) and meaningful work research by extending classic theoretical frameworks to Artificial Intelligence-enabled workplaces. Furthermore, from a practical perspective, our findings provided valuable guidance for organizations by highlighting the importance of transparent communication, employee involvement, and targeted training in reducing uncertainty and helping employees perceive their roles as relevant during the implementation of Artificial Intelligence.