Hospitality labor leakage and dynamic turnover behaviors in the age of artificial intelligence and robotics

Abstract

Purpose This study aims to examine the impact of artificial intelligence (AI) adoption on job insecurity and its subsequent effect on turnover intentions within the hotel industry. It investigated how AI-induced job insecurity affects the likelihood of employees considering leaving their current hotel jobs for other hotels or for opportunities outside the hotel sector, mediated by feelings of job stress and insecurity. Design/methodology/approach Quantitative data analysis used 259 responses from frontline hotel employees. Confirmatory factor analysis was used to explore the factor structure and assess model fit indices. Structural equation modeling was then applied to test the hypotheses. Findings Findings reveal that AI awareness has a positive impact on job stress and insecurity. Moreover, job insecurity is found to positively affect turnover intentions, with a notably stronger effect observed for turnover intentions toward non-hotel companies. Additionally, the influence of social capital as a moderator on the relationship between job insecurity and turnover intention varies depending on the specific dimensions of turnover intention. Research limitations/implications This study contributes to enhancing both theoretical frameworks and empirical insights into turnover dynamics within the hotel sector. However, future research should take into account employees’ positions, roles, organizations and career levels by examining these factors in relation to technology awareness, job stress, job insecurity and turnover intention. Originality/value This study initially focuses on the phenomenon of dynamic turnover issues within the hospitality sector, offering empirical and practical perspectives on effectively integrating new technologies and managing human resources amidst the automation and AI era.