Unpacking the Reasons Shaping Employee Acceptance and Attitudes towards AI Assistant Services in the Hotel Industry: A Behavioral Reasoning Perspective

Abstract

This study investigated organizational employees' opinions and acceptance of AI-based service assistants using the Behavioral Reasoning Theory (BRT). The behavioural reasoning theory-based study included 50 hotel industry executives, HR leaders, and employees. Themes were identified by thematic analysis of observations, focus groups, and participant interviews. This study used comparative thematic analysis and MAXQDA automated content analysis. It examines "reasons for" and "reasons against" adoption from a least developing nation's perspective. The reasons are personalisation, interactivity, perceived intelligence, anthropomorphism, language difficulties, technology phobia, service failure recovery, and inadequate infrastructure. "Reasons for" positively affect mindset and adoption intention, whereas "reasons against" negatively affect them. Financial risks, technological infrastructure issues, data security issues, and a lack of an organisational strategy are also seen in Bangladesh's AI deployment. The study provides practical insights for hotel industry practitioners, managers, and employees, as well as system designers and developers of AI-driven service solutions, on AI assistant adoption. Behavioural reasoning theory is used for the first time to examine hotel employees' attitudes and intentions to use AI-based service assistants. This study is a cross-sectional investigation that is carried out within certain, limited industrial sectors. Longitudinal studies can be conducted to generalize the outcome of this study. JEL classification numbers: M21, M30, 010. Keywords: AI service assistant, Employee adoption, Behavioral reasoning theory, Hotel industry.