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Employers today struggle with how to retain workers, yet research is not clear on how specific strategies lessen voluntary turnover. The study’s objective is to clarify the relationship between paid time off and voluntary turnover. In particular, we consider the mediating effect of job satisfaction and the interaction effect of flexible scheduling.

Through a longitudinal quantitative design, we are able to isolate the association between paid time off and voluntary turnover with logit regression and fixed effects estimations, using the National Longitudinal Survey of Youth (NLSY97). We further assess the likelihood of intervening and interacting variables on the focal relationship.

Our data suggest paid time off is associated with fewer voluntary resignations, but not through the mediator of job satisfaction. Flexible scheduling is also associated with fewer resignations, though the variables of paid time off and flexible scheduling do not interact. Further, paid time off had a gender effect: men who were offered paid time off were associated with a 41% decrease in voluntary turnover, whereas women were associated with a 25% decrease. In summary, we find PTO influences voluntary turnover, but this relationship is not mediated by job satisfaction or moderated by flexible scheduling.

The role of employee benefits on voluntary turnover is understudied and not well understood, particularly as to whether voluntary turnover is impacted by paid time off through job satisfaction or as a measure of necessity. Furthermore, previous literature has not considered how contemporary benefits, such as flexible scheduling, work to complement or substitute, the effects of paid time off.

This study classifies and estimates safety costs in Arctic shipping.

Based on the literature review, the paper details shipping prevention costs into five categories (infrastructure and facilities, measures, technologies, personnel and management) and groups marine accidents into injury and death, property damage, environmental damage and others.

The proposed classification and estimation allow for a comparison of prevention costs and accident expenses. Estimating safety expenses in the Arctic presents challenges, such as data inadequacies. However, the method has been tested with data provided by an Arctic ship operator.

Thus, shipping companies can verify the effectiveness of their investments and reorientate whenever necessary, becoming a decision-support system to best allocate safety investments. Combined with company safety performance, the tool can help identify the safety areas requiring enhanced attention.

This paper presents the first classification and a tool to assess safety costs in relation to Arctic shipping, potentially supporting safety investment decisions.

This chapter focuses on the integration of virtual reality (VR) into human resource management (HRM), with a special emphasis on theoretical underpinnings that support its adoption and utilisation. The speed at which technology is improving has placed VR as potentially game-changing for the field of HRM. This chapter reviews a number of theoretical models, including the Technology Acceptance Model, Unified Theory of Acceptance and Use of Technology, Diffusion of Innovations Theory and Social Cognitive Theory, in an attempt to make the framework as exhaustive as possible in the quest to unravel the ingredients that influence the acceptance of VR in HRM. This chapter discusses the practical implications of VR on the enhancement of organisational efficiency and employee well-being, based on a literature review of empirical studies that shed light on the challenges for VR applications due to technical limitations, ethical concerns and people's resistance to change. It concludes by indicating the literature gaps and proposing some future lines of research for the use of VR in HRM.

Current studies show that the Lean Six Sigma (LSS) methodology is used all over the world, by different types of companies in different countries. However, this is not yet the case for certain developing countries such as Morocco, where this methodology is still being discovered and applied and where also the relationship between the adoption of this methodology and sustainable performance is not yet clear. Thus, the aim of this study is to investigate the impact of LSS tools, used by industrial companies in Morocco, on the three dimensions of performance: economic, social and environmental.

This study used partial least squares-based structural equation modeling (PLS-SEM) to conduct an empirical examination of the impact of LSS tools used by Moroccan manufacturing industries on their sustainable performance. Data were collected using a semistructured questionnaire, with a total of 121 valid responses collected for this study.

The results showed that the adoption of LSS tools has a positive effect on the sustainable performance of these industries. The analysis of the collected data also revealed that this effect is most significant when it comes to social performance, followed by environmental and finally economic performance. It was also found that Lean Management tools have a greater impact than Six Sigma tools.

The results of this study may encourage Moroccan industries that are new to LSS to adopt it, as it proves to have positive results not only on the economic aspects of the firm but also on the improvement of employee well-being and the protection of our planet’s environment. In addition, this study gives them an idea of the tools that are most widely used in their Moroccan context, thus facilitating the choice of tools with which they can begin to embed a continuous improvement mindset.

Although several studies have already analyzed the relationship between the LSS approach and sustainable performance, these studies have generally focused on developed countries that are well advanced in the use of these tools. Hence, the originality of this study is its relevance to the Moroccan context, which still needs more studies in the fields of continuous improvement and sustainability.

In today's digitised world, human resource management (HRM) faces challenges due to emerging technologies. Among these, virtual reality (VR) has become particularly significant as it reshapes critical aspects of HRM by offering immersive experiences. Although VR holds strategic value for HRM, integrating it effectively is challenging and cannot be achieved overnight. This chapter is dedicated to studying organisations that seek to embrace VR as a novel approach to HRM. It covers several key areas: VR technology, its applications in HRM, strategic benefits, drawbacks and implementation challenges, while highlighting contentious issues that require attention. In conclusion, the study suggests that overcoming obstacles to manage change may help bridge the gap to the desired outcomes. Additionally, the way the technology is utilised will determine the benefits ultimately received.

While high-performance work systems (HPWS) are widely viewed as beneficial, some suggest they may have a dark side and be simultaneously detrimental. This is tested toward turnover intentions (reduced by HPWS) in the context of perceived employability because HPWS are expected to enhance employability, which positively influences turnover intentions.

Survey data using two New Zealand employee studies were conducted (n = 525, n = 306). Data were analyzed for mediation (Study 1) and moderated mediation (Study 2) using the PROCESS macro.

Both studies show HPWS are negatively related to turnover intentions and positively to perceived employability, which also positively influences turnover intentions. This provides support for dark side effects. Study two extends the model by including career planning and tests a moderated mediation model, showing the indirect effects of HPWS being positive toward turnover intentions in the context of perceived employability at all levels of career planning. This indirect effect weakens as career planning strengthens.

Highlights that HPWS appear to have a dark side by positively shaping employability and ultimately turnover intentions when career planning is included as a boundary condition.

With its continuous development and application in the hotel industry, artificial intelligence (AI) is gradually replacing many jobs traditionally performed by humans. This research aims to understand how this threat and opportunity of substitution affects hotel employees’ behavioral decision-making.

This study uses a structural equation model, ordinary least squares and bootstrapping method to analyze the data collected with a field study and a scenario experiment from star-hotels in Shanghai, Paris and Seoul.

The results discovered that employees’ AI awareness has a positive relationship with their work engagement and AI boycott through two paths. The promoting path involves recovery level, while the hindering path includes job insecurity. In addition, the estimates showed that AI awareness has a great indirect effect on work engagement or AI boycott when innovativeness as a job requirement is high.

The findings offer insights to help hotels optimize the relationship between AI and hotel human workers while providing valuable implications for addressing behavioral dilemmas faced by hotel employees in the era of AI.

By integrating the behavioral decision-making literature with the conservation of resources theory, the study focuses on the dual mechanisms – challenging and hindering – through which AI awareness influences hotel employees’ coping strategies.

This study aims to evaluate the effectiveness of tax incentives provided by the Ethiopian government in spurring private investment and job creation, using unique administrative and survey data.

The study employs a dataset covering large- and medium-scale manufacturing in Ethiopia from 2012 to 2018, combined with administrative data on actual tax payments and statutory obligations to gauge the impact of tax incentives. Regression analysis using the generalized method of moments (GMM) is used to examine the relationship between tax incentives and employment, taking into account variations in production, distribution and financial costs.

The study finds that tax incentives do not significantly affect employment at conventional significance levels. The incentive elasticity of employment appears to diminish as production, distribution and financial costs increase. Consequently, the incentives provided by the government have not had a substantial impact on employment generation within the manufacturing sector.

This study is unique for its comprehensive analysis of tax incentives in the Ethiopian manufacturing sector using both administrative and survey data. It highlights that increasing production and financial costs can offset the employment benefits of these incentives, emphasizing the need for a more favorable business environment for private investors.

This paper analyzes employees’ perceptions of data collection processes for human resource analytics (HRA). More specifically, we study the effect that information sharing practices have on employees’ attributions (i.e. benevolent vs malevolent) through the perceived legitimacy of data collection and monitoring processes. Moreover, we investigate whether employees’ emotional reaction (i.e. fear of datafication) depends on their perceived legitimacy and attributions.

The research is based on a sample of 259 employees operating for an Italian consulting firm that developed and implemented HRA processes in the last 3 years. The hypothesized model has been tested using structural equation modeling (SEM) on Stata 14.

This paper demonstrates the mediating role of perceived legitimacy in the relationship between information sharing practices and employees’ benevolent and malevolent attributions about data collection and monitoring processes for HRA practices. Results also reveal that perceived legitimacy predicts employees’ fear of datafication, with benevolent attributions that partially mediate this relationship.

This research indicates that employees perceive, try to make sense of and emotionally react to HRA processes. Moreover, we reveal the crucial role of information sharing practices and perceived legitimacy in determining employees’ attributions and emotional reactions to data collection and monitoring processes.

Combining human resource (HR) attributions, HR system strength, information processing and signaling theories, this work explores employees’ perception, attributive processes and emotional reactions to data collection processes for HRA practices.

This study aims to examine key factors influencing hospitality employee turnover in a post-pandemic context, challenging conventional assumptions about the role of demographics and work-related factors in retention decisions.

The research adopted a comprehensive framework using the capability approach and geospatial data analysis, integrating social vulnerability indexes with survey responses from 797 hospitality employees. This study analyzed turnover intentions across demographics, job roles and regions, focusing on Florida’s I-4 corridor.

Individual conversion factors like age and marital status were the strongest predictors of turnover, with older and married employees less likely to leave their jobs. In contrast, traditional variables like income, education and job type did not significantly influence turnover intentions. The pandemic blurred distinctions between job roles, highlighting personal circumstances, health risks and economic pressures as critical factors. Contrary to expectations, financial assistance did not significantly reduce turnover intentions. In addition, employees’ life circumstances, such as social vulnerability, influence labor relations and turnover more than work-related conditions.

This study enriches turnover literature by confirming that personal life circumstances, like age and marital status, are pivotal in understanding employee retention. It challenges conventional demographic and work-related predictors and urges future research to explore the interaction between personal and professional factors in the hospitality industry. The study’s agent-based framework deepens the understanding of how various factors shape employee decisions to stay or leave.

The findings suggest that hospitality employers must develop more localized, employee-centric retention strategies, especially for younger employees. Tailored approaches considering regional and demographic differences, such as providing career development opportunities and flexible work conditions, could foster long-term loyalty. In rural areas, retention efforts should focus on improving job satisfaction and community support, while in urban areas, strategies prioritize career progression and flexibility.

The study’s findings have significant social implications, particularly in reshaping how employee retention strategies are developed in the hospitality industry. By emphasizing life circumstances over traditional work-related factors, the research highlights the importance of supporting employees’ resilience, especially for those facing social vulnerability. Employers may need to create more flexible and inclusive policies that account for personal, economic and health-related challenges. In addition, the findings suggest that financial aid alone is insufficient in reducing turnover, calling for a more holistic approach that integrates emotional and social support to foster a more stable and loyal workforce.

This study challenges traditional turnover models by shifting focus from work-related factors to life circumstances, particularly the resilience of older and married employees. It integrates three dimensions – personal (sociodemographics), social (support) and environmental (job type, pandemic challenges) – to examine their influence on employee agency. This triadic framework offers insights into how individual, social and contextual factors shape turnover decisions.