Optimizing customer searching experience of online hotel booking by sequencing hotel choices and selecting online reviews: A mathematical model approach

• A new methodology, a two-stage stochastic programming model, is proposed.
• The model determines the optimal sequence of hotel choices with a selection of online reviews.
• The multi-attributes of a hotel are considered in multi-dimensional sorting.
• A numerical result using an actual data set of hotels from an OTA is studied.
• The result shows that the optimal sequence outperforms typical sorting methods.

A two-stage stochastic programming model to determine an optimal sequencing of hotels, with the online review selection provided by online travel agencies (OTAs), is developed. The multi-attributes of hotels and online reviews containing various indicators (e.g., location and service) are all incorporated in a booking decision. To determine the optimal stopping search step for customers, a sequential search behavior is assumed. The objective of model is to minimize the expected number of search steps to reach a hotel of which all characteristics satisfy customer expectations under optimal search behavior. The effectiveness of the proposed model is confirmed in a case study using real data from an OTA. The contribution of this paper is to propose a new model that OTAs could practically adopt to generate an optimal sequence of hotels with a selection of online reviews to shorten search time for customers and yield a high number of booked rooms.