A model integrating the 2‑tuple linguistic model and the CRITIC‑AHP method for hotel classification

Abstract

Hotel classification is essential for hotel managers and customers. It can assist hotel managers in better understanding the needs of their customers and in improving various aspects of the hotel through relevant strategies. It also aids customers in choosing appropriate accommodations according to their preferences regarding hotel location, services, and other aspects. This paper aims to improve our previous model by incorporating expert opinions into the weight calculation, thereby increasing its practical applicability. The extended model combines the analytical hierarchy process (AHP) and the CRiteria Importance Through Intercriteria Correlation (CRITIC) methods, introducing a novel approach for calculating the weights of each aspect. The 2-tuple linguistic model is retained in the extended model to resolve the problem of information loss in linguistic information fusion. Finally, various hotel segments are obtained with the weighted K-means clustering. A dataset with over fifty million hotel reviews from TripAdvisor has been applied to evaluate the extended model. The results show that the extended model achieves denser and better separated hotel clusters than our previous model, while maintaining the same advantages. This model is more likely to help hotel managers create better strategies to tackle hotel weaknesses or gain competitive advantages, as it combines two types of weights that improve clustering results: the quantity of information in each hotel aspect and the expert judgment of each aspect's importance in hotel development.