Categorizing peer-to-peer review site features and examining their impacts on room sales

ABSTRACT

This study examines the impacts of online review features on hotel Online Room Sales for various types of hotel segments utilizing a dataset that includes 227,378 post-purchase customer review comments for 1,092 hotels. Data were analyzed by conducting three different analyses utilizing the log-log regression model. Findings suggest that overall recommendation scores and hotel attribute information are the two most critical features of online reviews used by consumers in their decision-making process to make their hotel booking decisions. Thus, changes in customer rating scores result in a profound impact on room sales. However, the impact sizes of these review features are not significantly different among different hotel segments, with one exception, the room rate. This study found that the impact size of the room rate is significantly larger for luxury hotels compared to other hotel segments. Managerial implications and contributions of the current study are discussed.

摘要

本研究利用包括1092家酒店227378个购买后客户评论的数据集，研究了在线评论功能对不同类型酒店客房销售的影响.通过使用对数回归模型进行三种不同的分析来分析数据.调查结果表明，总体推荐得分和酒店属性信息是消费者在决策过程中用来做出酒店预订决策的两个最重要的在线评论功能.因此，客户评分的变化会对客房销售产生深远的影响.但是，这些审查功能的影响大小在不同的酒店细分市场之间没有显著差异，除了一个例外，即房价.这项研究发现，与其他酒店相比，豪华酒店房价的影响幅度要大得多.讨论了本研究的管理意义和贡献.

KEYWORDS:

• Online customer reviews
• review comments
• features
• customer ratings
• hotel performance
• online room sales
• online information
• log-log regression

Additional information

Funding

The authors wish to thank the Fundamental Research Funds for the Central Universities, Southwestern University of Finance and Economics (No. JBK1803003).