Abstract
AbstractThe forecasting of demand or cancellations is highly important for efficient revenue management in the hotel industry. Previous studies have mainly focused on the accuracy of the prediction of reservation number or cancellation rate on a specific accommodation or hotel chain; therefore, the application of the prediction to different accommodations or under the behavioral change of customers in response to natural or human events is difficult without the re-estimation of the prediction model. Information of the customer behavioral trend on the accommodation reservations is necessary for the construction of a general forecasting model. In this study, we focus on one of the general trends of customer behavior, that is, the reservation timing and the time changes of the cancellation probability using the big data of the reservation records provided by an online trip agency in Japan. We showed that the reservation timing and cancellation probability can be decomposed by five and six exponential functions of the days until the stay and the days from the reservations. We also showed that the significant factors influencing the time changing patterns are the guest numbers per room for both reservation and cancellation, composition of guests in terms of the number and gender of guests, and the stay length for reservation. These findings imply that the customer behavior during accommodation reservation could be categorized into multiple motivational factors toward reservations or cancellations. Our results contribute to the construction of a general forecasting model on the accommodation reservations.
Funder
Core Research for Evolutional Science and Technology
Japan Society for the Promotion of Science
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,General Engineering
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