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Artificial intelligence as a boundary-crossing object for employee engagement and performance
Institution:1. School of Business, University of Southern Queensland, Springfield Central, Brisbane, Australia;2. Faculty of Business Administration, University of Macau, Avenida da Universidade, Taipa, Macau, China;3. School of Tourism Management, Sun Yat-Sen University, Key Laboratory of Sustainable Tourism Smart Assessment Technology, Ministry of Culture and Tourism of China, China
Abstract:The study proposes AI-powered tools and applications as boundary-crossing objects to examine how AI performance can affect employees' job engagement, service and job performance. Job security is modelled as a moderator in the boundary-crossing process. Several theories including boundary crossing, goal setting and self-regulation are drawn on to posit these relationships. The study was undertaken with Australia-based full-time employees who had experience with AI-powered tools at work. The results show that AI performance had a significant effect on job engagement, and employee service performance, which were significantly related to job performance appraisal. Job engagement and service performance exhibited significant mediation effects between AI and job performance. The moderation effect exerted by job security was significant in enhancing employees’ job engagement and service performance. The study contributes to service research and human resource management literature. The findings have implications for service marketers and human resource practitioners.
Keywords:Artificial intelligence  Service research  Employee engagement  Employee performance
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