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Engaging Hotel Employees in the Era of Artificial Intelligence: The Interplay of Artificial Intelligence Awareness, Job Insecurity, and Technical Self-Efficacy

Year: 2024

Type: article

Abstract: This study investigates the impact of artificial intelligence awareness (AIA) on employees' job engagement (EJE) in the hotel industry, focusing on the mediating role of job insecurity (JI) and the moderating role of technical self-efficacy (TSE). Drawing on the Expectancy theory and Affective Events theory, the study proposes a mediated moderation model and tests it using PLS-SEM on a sample of 390 full-time employees from five-star hotels in Egypt. The results confirm that AIA negatively influences EJE and positively influences JI, while JI negatively influences EJE and mediates the AIA→EJE relationship. Furthermore, TSE negatively moderates the AIA→JI relationship, mitigating the negative impact of AIA on JI. The findings highlight the importance of addressing employees' AIrelated concerns and leveraging their technical self-efficacy to maintain job engagement and security in the face of technological disruptions. The study contributes to the literature by extending the application of the Expectancy theory and Affective Events theory to the context of AI adoption in the hotel industry and offers practical implications for hotel managers and HR professionals.

Source: Journal of Logistics Informatics and Service Science

DOI: 10.33168/jliss.2024.0530

Authors: Ibrahim Hassan, Amany Hamid, Baquero, Asier, Salama, Wagih M. E., Ahmed Khairy, Hazem

Institutions: Universidad Internacional de La Rioja, King Faisal University, Fayoum University

Language: English

Topic: Job Satisfaction and Organizational Behavior

Subfield: Organizational Behavior and Human Resource Management

Field: Business, Management and Accounting

Domain: Social Sciences

SDG: Decent work and economic growth

Open Access status: diamond

Funder: King Faisal University