适度
分析
心理学
调解
调解
弹性(材料科学)
知识管理
人力资源管理
心理弹性
工作表现
独创性
工作满意度
应用心理学
计算机科学
社会心理学
数据科学
政治学
物理
创造力
法学
热力学
作者
Qijie Xiao,Jiaqi Yan,Greg J. Bamber
出处
期刊:Personnel Review
[Emerald (MCB UP)]
日期:2023-10-21
被引量:14
标识
DOI:10.1108/pr-03-2023-0198
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI