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1 – 2 of 2Qijie Xiao, Jiaqi Yan and Greg J. Bamber
Based on the JD-R model and process-focused HRM perspective, this research paper aims to investigate the processes underlying the relationship between AI-enabled HR analytics and…
Abstract
Purpose
Based on the JD-R model and process-focused HRM perspective, this research paper aims to investigate the processes underlying the relationship between AI-enabled HR analytics and employee well-being outcomes (resilience) that received less attention in the AI-driven HRM literature. Specifically, this study aims to examine the indirect effect between AI-enabled HR analytics and employee resilience via job crafting, moderated by HRM system strength to highlight the contextual stimulus of AI-enabled HR analytics.
Design/methodology/approach
The authors adopted a time-lagged research design (one-month interval) to test the proposed hypotheses. The authors used two-wave surveys to collect data from 175 full-time hotel employees in China.
Findings
The findings indicated that employees' perceptions of AI-enabled HR analytics enhance their resilience. This study also found the mediation role of job crafting in the mentioned relationship. Moreover, the positive effects of AI-enabled HR analytics on employee resilience amplify in the presence of a strong HRM system.
Practical implications
Organizations that aim to utilize AI-enabled HR analytics to achieve organizational missions should also dedicate attention to its associated employee well-being outcomes.
Originality/value
This study enriched the literature with regard to AI-driven HRM in that it identifies the mediating role of job crafting and the moderating role of HRM system strength in the relationship between AI-enabled HR analytics and employee resilience.
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Chia-Huei Wu, Matthew Davis, Hannah Collis, Helen Hughes and Linhao Fang
This study aims to examine the role of location autonomy (i.e. autonomy over where to work) in shaping employee mental distress during their working days.
Abstract
Purpose
This study aims to examine the role of location autonomy (i.e. autonomy over where to work) in shaping employee mental distress during their working days.
Design/methodology/approach
A total of 316 employees from 6 organizations in the UK provided data for 4,082 half-day sessions, over 10 working days. Random intercept modeling is used to analyze half-day data nested within individuals.
Findings
Results show that location autonomy, beyond decision-making autonomy and work-method autonomy, is positively associated with the perception of task-environment (TE) fit which, in turn, contributes to lower mental distress during each half-day session. Results of supplementary analysis also show that location autonomy can contribute to higher absorption, task proficiency and job satisfaction via TE fit during each half-day session.
Originality/value
This study reveals the importance and uniqueness of location autonomy in shaping employees' outcomes, offering implications for how organizations can use this in the work–life flexibility policies to support employee mental health.
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