利用多尺度时空特征预测酒店需求

IF 9.9 1区 管理学 Q1 HOSPITALITY, LEISURE, SPORT & TOURISM
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引用次数: 0

摘要

准确的需求预测对酒店收益管理和相关决策至关重要。考虑到不同时间尺度上空间效应的异质性和动态性,本研究引入了一种新型模型,可以深入提取这些特征,从而提高酒店需求预测性能。具体来说,该模型构建了具有不同周期性的输入变量,然后整合了 Transformer 神经网络和长短期记忆,以提取多尺度动态时空特征,从而生成准确的预测。该模型的有效性通过在中国厦门的实证案例得到了验证。结果表明,我们的模型在准确性和稳健性方面明显优于基准模型。研究结果拓展了时空模型在酒店需求预测中的应用。酒店管理者可以利用我们的预测来优化运营、提高收益和控制风险。提取的时空特征还可以帮助管理者研究与邻近酒店的合作和竞争关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Hotel demand forecasting with multi-scale spatiotemporal features

Accurate demand forecasting is critical to hotel revenue management and related decision-making. Considering the heterogeneity and dynamics of spatial effects across different time scales, this study introduces a novel model which can deeply extract these features to improve the forecasting performance of hotel demand. Specifically, the model constructs input variables with different periodicities and then integrates a Transformer neural network and long short-term memory to extract multi-scale and dynamic spatiotemporal features to generate accurate forecasts. The effectiveness of the model is verified through an empirical case in Xiamen, China. Results suggest our model significantly outperforms benchmarks in terms of accuracy and robustness. The findings extend the application of spatial-temporal modeling in hotel demand forecasting. Hotel managers can use our forecasts to optimize operations, improve revenues, and control risks. The extracted spatiotemporal features can also help managers examine cooperation and competition relationships with neighbor hotels.

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来源期刊
International Journal of Hospitality Management
International Journal of Hospitality Management HOSPITALITY, LEISURE, SPORT & TOURISM-
CiteScore
21.20
自引率
9.40%
发文量
218
审稿时长
85 days
期刊介绍: The International Journal of Hospitality Management serves as a platform for discussing significant trends and advancements in various disciplines related to the hospitality industry. The publication covers a wide range of topics, including human resources management, consumer behavior and marketing, business forecasting and applied economics, operational management, strategic management, financial management, planning and design, information technology and e-commerce, training and development, technological developments, and national and international legislation. In addition to covering these topics, the journal features research papers, state-of-the-art reviews, and analyses of business practices within the hospitality industry. It aims to provide readers with valuable insights and knowledge in order to advance research and improve practices in the field. The journal is also indexed and abstracted in various databases, including the Journal of Travel Research, PIRA, Academic Journal Guide, Documentation Touristique, Leisure, Recreation and Tourism Abstracts, Lodging and Restaurant Index, Scopus, CIRET, and the Social Sciences Citation Index. This ensures that the journal's content is widely accessible and discoverable by researchers and practitioners in the hospitality field.
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