Time changes of customer behavior on accommodation reservation: a case study of Japan

IF 0.7 4区 数学 Q3 MATHEMATICS, APPLIED Japan Journal of Industrial and Applied Mathematics Pub Date : 2023-11-28 DOI:10.1007/s13160-023-00623-5
Koichi Ito, Shunsuke Kanemitsu, Ryusuke Kimura, Ryosuke Omori
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Abstract

The 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.

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住宿预订中顾客行为的时间变化——以日本为例
对需求或取消的预测对于酒店行业有效的收益管理非常重要。以前的研究主要集中在预测特定住宿或连锁酒店的预订数量或取消率的准确性;因此,如果不对预测模型进行重新估计,则很难将预测应用于不同的住宿条件或客户对自然或人为事件的行为变化。为了建立一个通用的预测模型,需要了解顾客在住宿预订方面的行为趋势信息。在本研究中,我们利用日本某在线旅行社提供的预订记录大数据,关注客户行为的一个大趋势,即预订时间和取消概率的时间变化。我们证明了预订时间和取消概率可以被5个和6个指数函数分解为距离入住天数和距离预订天数。我们还发现,影响时间变化模式的显著因素是每间客房的预订和取消客人人数、客人的数量和性别构成以及预订的住宿时间。这些发现表明,顾客在预订或取消住宿时的行为可以分为多个动机因素。我们的研究结果有助于建立一个关于住宿预订的通用预测模型。
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来源期刊
CiteScore
1.50
自引率
11.10%
发文量
56
审稿时长
>12 weeks
期刊介绍: Japan Journal of Industrial and Applied Mathematics (JJIAM) is intended to provide an international forum for the expression of new ideas, as well as a site for the presentation of original research in various fields of the mathematical sciences. Consequently the most welcome types of articles are those which provide new insights into and methods for mathematical structures of various phenomena in the natural, social and industrial sciences, those which link real-world phenomena and mathematics through modeling and analysis, and those which impact the development of the mathematical sciences. The scope of the journal covers applied mathematical analysis, computational techniques and industrial mathematics.
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