What makes a better hotel selection? A hybrid approach considering tourists’ preference and review helpfulness

Hotel selection is crucial in planning trips. Several studies constructed the decision methods, which assumed that people are completely rational and neglected decision-maker’s (DM’s) behavioural aspects, based on text reviews or numerical ratings with the subjective or objective weights of criteria. Therefore, this study proposes a picture fuzzy gained and lost dominance score (PF-GLDS) method based on prospect theory, which integrates user-generated text reviews and multi-criteria ratings to facilitate hotel selection while considering tourists’ preference and review helpfulness. First, review helpfulness is analyzed to enhance data quality. Second, a decision matrix is constructed by simultaneously considering sentiment in helpful text reviews as well as multi-criteria ratings. Third, the criteria are derived by the maximising deviation and best worst methods (BWM), respectively, for tourists’ preferred objective and subjective weights. Finally, to address hotel selection problems, an extended GLDS method with picture fuzzy information, considering bounded rationality behaviour, is developed. Empirical evaluation on five hotels from the TripAdvisor website demonstrates the reasonableness and advantages of our proposed hybrid approach in achieving more objective and reliable decision making. Concurrently, this study can serve as a reference for tourists seeking well-suited hotels and tourism website optimisation.