[1G3-OS-13a] OS-13

2:40 PM - 2:55 PM JST(5:40 AM - 5:55 AM UTC)

[1G3-OS-13a-05] Boosting Hotel Profits: The Power of Enhanced Cancellation Predictions

〇Ryusuke Kimura¹, Kimitoshi Sato² (1. Recruit Co., Ltd., 2. Kanagawa University)

Keywords:

Revenue Management,Dynamic Pricing,Pricing,Demand Prediction,Cancellation Prediction

The hotel industry faces the uncertainty of reservations and cancellations. Although dynamic pricing provides appropriate discounts for last-minute cancellations, it is not always possible to fill vacancies unless there is sufficient demand. Therefore, it is important to examine how the accuracy of cancellation forecasts affects the performance of dynamic pricing in practice. In this study, we analyze the relationship between forecast accuracy and expected returns using actual data on room reservations and cancellations from a region in Japan. The results show that an improvement in forecast accuracy leads to an increase in revenue. We also show that this improvement simultaneously increases consumer surplus by lowering the average sales price and improves the load factor. Furthermore, the improvement is more pronounced during the peak season when the number of potential customers is higher.