Segmenting tourists' motivations via online reviews: An exploration of the service strategies for enhancing tourist satisfaction.

ABSTRACT

Tourism motivation and satisfaction are classic themes in tourism research. This study combines latent Dirichlet allocation (LDA) and the Censydiam motivation model to analyze online reviews of tourism in Qinghai, China. The aim of this research is to explore tourist motivation through online reviews and provide innovative service suggestions to improve tourist satisfaction. The LDA model initially extracts six main topics from online comments. Then, using the fuzzy analytic hierarchy process (FAHP), it maps the relationship between topics and tourism motivations to propose strategies for enhancing tourists' enjoyment, conviviality, and other motivating factors. Furthermore, we employ the Kano model to evaluate tourists' satisfaction levels regarding these strategies, demonstrating their positive evaluations. Hence, this study provides tourism industry professionals and service designers with an innovative method for understanding tourists' motivations through online reviews, enabling them to design specific services that enhance tourism experiences.