期刊
TOURISM MANAGEMENT
卷 72, 期 -, 页码 417-426出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.tourman.2019.01.002
关键词
Online hotel reviews; Customer dissatisfaction; Structural topic model; Text mining; Tripadvisor
资金
- National Natural Science Foundation Program of China (NSFC) [71771182, 71772150]
- Research Fund for Academic Team of Young Scholars at Wuhan University [Whu2016013]
The ability to understand the causes of customers' complaints is critical for hotels to improve their service quality, customer satisfaction, and revenue. This study adopts a novel structural topic model text analysis method to analyze 27,864 hotel reviews in New York City, and show that it leads to improved inference on consumer dissatisfaction. Our results reveal 10 topics, whose appearances in the negative reviews are substantially higher than those in the positive reviews. In addition, we investigate how customer complaints vary across different hotel grades. Results indicate that customer complaints for high-end hotels are mainly related to service issues, whereas customers of low-end hotels are frequently annoyed by facility-related problems. This research contributes to the hospitality literature by enhancing our understanding of the aspects of hotel customers' dissatisfaction through rigorous statistical analysis, their correlations, and importance for different hotel grades.
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