Recommending suitable hotels to travelers in the post-COVID-19 pandemic using a novel FAHP-fuzzy TOPSIS approach

Abstract

Cities around the world have reopened from the lockdown caused by the COVID-19 pandemic, and more and more people are planning regional travel. Therefore, it is a practical problem to recommend suitable hotels to travelers amid the COVID-19 pandemic. However, it is also a challenging task since the criteria that affect hotel selection amid the COVID-19 pandemic may be different from those usually considered. From this perspective, a novel fuzzy analytic hierarchy process (FAHP)-fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS) approach is proposed in this study for hotel recommendation. The proposed methodology not only considers the criteria affecting hotel selection amid the COVID-19 pandemic, but also establishes a systematic mechanism to simultaneously improve the accuracy and efficiency of the recommendation process. The novel FAHP-fuzzy TOPSIS approach has been successfully applied to recommend suitable hotels to fifteen travelers for regional trips amid the COVID-19 pandemic.