Perceptual mapping and key factors influencing hotel choices: A web mining approach to Booking.com reviews

IF 9.9 1区管理学 Q1 HOSPITALITY, LEISURE, SPORT & TOURISM

International Journal of Hospitality Management Pub Date : 2025-05-31 DOI:10.1016/j.ijhm.2025.104308

Amin Mojoodi , Tafazal Kumail , Seyed Mohammad Ahmadzadeh , Saeed Jalalian

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引用次数: 0

Abstract

Purpose

In the hospitality industry, hotel managers have widely considered online customer reviews because they play an essential role in influencing the decisions of potential travelers and improving hotel performance. The purpose of this research is to identify the variables that influence the decisions of hotel customers and to perceptual map brands using the web mining method.

Design/methodology/approach

The research analyzed user comments on the Booking.com website for data entry. Hotel user evaluations on the Booking.com site were gathered textually using Python programming and web scraping techniques. A Python script was developed to get hotel information and reviews from Booking.com. We analyzed the number of 17,446 customer comments on the Booking.com site that were posted between November 2020 and November 2023. Customer comments were carefully pre-processed to start the processing process by removing comments that were not in English or were less than five words long. Finally, 6111 comments entered the processing process.

Findings

According to the findings of this study, 40 variables were identified and categorized into six clusters using the K-Means technique and a dendrogram. The following clusters were sorted by weight and significance: facility stimuli (33.98 %), experimental stimuli (23.88 %), communication stimuli (23.85 %), locational stimuli (13.47 %), sensory stimuli (2.67 %), and hotel smartification stimuli (2.14 %). The silhouette index was used to assess the quality of the discovered clusters, and the resultant value was validated. Following cluster identification and rating, a perceptual map of hotel brands was developed for the two most prominent clusters (facility and experimental stimuli).

Practical implications

By evaluating user comments on competing hotels, managers may improve their strategies for attracting customers and elevating their products. By analyzing online comments and examining the critical elements revealed in this study, hotel managers may formulate and execute plans to improve customer satisfaction and loyalty. Also, The results of this research and the information gathered from analyzing customer feedback can be used to develop targeted marketing strategies. These strategies enable hotel administrators to develop and execute advertising campaigns that attract more clients.

Originality/value

This study used a different approach to evaluating customer opinions than previous research. Analyzing many online customer reviews on a website and identifying variables affecting their satisfaction or dissatisfaction is more reliable than other data collection methods, such as questionnaires. Also, since this study uses web mining, it has advantages over standard research methods. Due to cost and time constraints, we will study a large amount of data that would not be economically feasible in traditional research.

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感知映射和影响酒店选择的关键因素：Booking.com评论的网络挖掘方法

在酒店业，酒店管理者已经广泛考虑在线客户评论，因为它们在影响潜在旅行者的决策和提高酒店绩效方面发挥着至关重要的作用。本研究的目的是识别影响酒店客户决策的变量，并使用网络挖掘方法对品牌进行感知映射。设计/方法/方法本研究分析了Booking.com网站上的用户评论，以进行数据输入。Booking.com网站上的酒店用户评价是使用Python编程和网络抓取技术以文本形式收集的。开发了一个Python脚本来从Booking.com获取酒店信息和评论。我们分析了2020年11月至2023年11月期间Booking.com网站上发布的17,446条客户评论。对客户评论进行了仔细的预处理，以便通过删除非英文评论或长度少于五个单词的评论来开始处理过程。最后，6111条评论进入了处理过程。根据本研究的发现，使用K-Means技术和树形图确定了40个变量并将其分类为6个簇。按权重和显著性排序如下：设施刺激（33.98 %）、实验刺激（23.88 %）、交流刺激（23.85 %）、位置刺激（13.47 %）、感官刺激（2.67 %）和酒店智能化刺激（2.14 %）。使用剪影指数来评估发现的聚类的质量，并对结果值进行验证。在集群识别和评级之后，针对两个最突出的集群（设施和实验刺激）开发了酒店品牌的感知图。实际意义通过评价用户对竞争酒店的评价，管理者可以改进吸引顾客和提升产品的策略。通过分析在线评论和检查本研究揭示的关键因素，酒店管理者可以制定和执行计划，以提高顾客满意度和忠诚度。此外，这项研究的结果和从分析客户反馈收集的信息可以用来制定有针对性的营销策略。这些策略使酒店管理者能够开发和执行吸引更多客户的广告活动。原创性/价值本研究采用了与以往研究不同的方法来评估客户意见。分析网站上的许多在线客户评论，并确定影响他们满意度或不满意度的变量，比其他数据收集方法（如问卷调查）更可靠。此外，由于本研究使用了web挖掘，它比标准的研究方法有优势。由于成本和时间的限制，我们将研究大量在传统研究中不具有经济可行性的数据。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

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.