Ranking hotels through multi-dimensional hotel information: a method considering travelers’ preferences and expectations

Although travelers tend to consider multi-dimensional hotel information when choosing their accommodation, few online travel agency (OTA) websites allow them to express their preferences and expectations for the selection criteria to obtain customized hotel ranking results. The lack of this function makes travelers have to spend extra time and effort in comparing different hotels to make the final decision. To solve this problem, a hotel ranking method considering travelers’ preferences and expectations is proposed based on multi-dimensional hotel information. In the method, considering the travelers’ actual process of hotel reservation through the OTA website, four types of hotel information (i.e., price, rating, location and text comment) are used. To make full use of these information, text mining, prospect theory and multi-attribute decision-making method are integrated into the proposed method. A case study is given to verify the reliability of the proposed method. The proposed method can be embedded into OTA websites to provide decision support for travelers’ hotel reservation, which will reduce the time spent by travelers in hotel search and comparison, thus effectively promote hotel reservation and improve traveler satisfaction.