Structural Relationships between Perceived Hotel AI Service Failure Quality and Brand Avoidance Intention: The Mediating Effect of Technostress

The adoption of AI-enabled customer touchpoints, such as self-service kiosks, mobile checkin systems, chatbots, and service robots, has increased rapidly in the hotel industry.Although prior research has largely emphasized the benefits of AI-based services, t has paid relatively little attention to the negative consequences that may arise when these services fail.Against this background, this study examines the structural relationships among perceived hotel AI service failure quality, technostress, and brand avoidance intention.It also investigates whether technostress mediates the relationship between perceived hotel AI service failure quality and brand avoidance intention.Data were collected through a survey of guests who had used AI-based services at three hotels in Seoul.The survey was conducted from May 1 to May 25, 2026, and the final analysis included 317 valid responses.The data were analyzed using SPSS 23.0 and AMOS 23.0.The analytical procedures included frequency analysis, factor analysis, correlation analysis, mediation testing, and structural equation modeling for hypothesis testing.The findings indicate that all three dimensions of perceived hotel AI service failure quality significantly increase technostress.Technostress, in turn, has a significant positive effect on brand avoidance intention.These findings highlight the importance of managing failures in AI-enabled hotel services and designing customer experiences that reduce technology-related stress.The study concludes by offering practical and interdisciplinary implications for effectively managing AI-based services in the hotel industry.