Extension of the POS-TI relationship – in the context of contemporary hotels with AI applications

Abstract

Purpose – This study aims to extend the classic perceived organizational support (POS)–turnover intention (TI) relationship in the context of the application of artificial intelligence (AI) technology in contemporary hotels. Design/methodology/approach – This study adopted an explanatory sequential design. Stage 1 – Quantitative Methodology. A total of 554 valid questionnaires with the random sampling technique were collected with the help of the China Hotel Association. This study combined SPSS and SmartPLS software to verify hypotheses. Stage 2 – Qualitative Methodology. This section obtained a sample size of 24 interviewees with the objective sampling technique. The researchers transcribed all interview materials into text and used NVivo version 14 to explain the results of hypothesis testing. Findings – This study shows that POS significantly impacts employee TI in contemporary hotels with AI applications, and both the perceived value and threat of AI play partial mediating roles between the two. Research limitations/implications – The results are conducive to providing practical enlightenment for the contemporary hotel industry with AI applications. Practical implications – In contemporary hotels where AI technology is widely used, this study provides practical guidance for hotel managers, employees and AI technology developers from the dual perspectives of value and threat, aiming to minimize the TI among hotel employees caused by AI technology. Originality/value – To the best of the authors’ knowledge, this study is the initial attempt to design a dual mediation model with the perceived AI for the POS–TI relationship.