Identification of patterns of travel preferences enables personalised services in the hospitality and tourism sectors. Previous research has indicated links between patterns of travel preferences and personality traits but has mostly focused on isolated segments of a traveller’s journey, such as hotel or destination selection. The current study, based on the Big Five personality traits, extends this line of research using a large-scale empirical dataset (N = 979) in China that spans multiple aspects of travel behaviour. K-means clustering identifies four distinct groups, Experience Seekers, Convenience & Low-Cost Seekers, Quality & Status Seekers, and Easy-Goers, which differ in their patterns of preferences as well as their demographic and personality profiles. Logistic regression and random forest analyses reveal Extraversion and Openness to Experience as the most significant predictors of travel preferences. The results provide insights for the hospitality and tourism industry and suggest that incorporating personality traits can support more effective customer understanding and service design.
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Ji et al. (2026) studied this question.
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