Travelers' Accommodation Intention Towards Smart Hotels: A Two-Stage Analysis Using SEM and fsQCA

Purpose – As IoT and AI advance, smart hotels are gaining popularity. This research explores why travelers prefer them, focusing on novelty, efficiency, compatibility, and value to understand accommodation intentions. Methodology/Design/Approach – Targeting participants familiar with RAISA technology in smart hotels, this study uses structural equation modeling (SEM) and fuzzy set qualitative comparative analysis (fsQCA) to validate and examine the research model, identifying factors influencing travelers’ acceptance of smart hotels. Findings – SEM analysis shows that travelers’ intention to choose smart hotels is influenced by perceived novelty, efficacy, and compatibility, both directly and through perceived value. fsQCA reveals three attribute configurations linked to a strong intention to stay at smart hotels, offering insights on how perceived attributes enhance travelers’ intentions and helping hotels develop effective attraction strategies. Originality of the research – This study examines smart hotel adoption determinants using innovation diffusion and information processing theories, expanding to include perceived novelty, efficacy, and compatibility. fsQCA insights highlight the importance of aligning these elements to increase adoption rates among travelers.