How Do Memorable Experiences Influence Wellness Tourist Satisfaction? Insights From User-Generated Content and Machine Learning

Abstract

This study examines how international wellness tourists' memorable experiences influence their satisfaction and behavior in wellness hotels. We use machine learning to analyze user-generated content from wellness hotels across nine Asia-Pacific countries. Using k-means clustering, we identified two tourist segments based on tourists' ratings. Regression results showed that for Segment 1, value, rooms, and service positively influenced satisfaction; sleep quality had a negative effect, while location and cleanliness were insignificant. For Segment 2, value, rooms, service, and location had positive effects, whereas cleanliness and sleep quality were insignificant. Topic modeling further revealed three wellness dimensions (environmental, physical, and mental wellness) shaping memorable experiences. Based on these findings, we propose a conceptual framework linking hotel performance, wellness dimensions, memorable experience, satisfaction, and recommendation intention. This study contributes to wellness tourism research by emphasizing the role of big data and machine learning in enhancing wellness services and understanding consumer behavior.