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Using Hotel Web Ratings Data: Understanding Customers' Overall Satisfaction Ratings

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Abstract:

This article presents techniques that hotel managers can use to analyze online rating data and effectively allocate scarce resources to improve a hotel's overall customer ratings. We apply the Classification and Regression Tree (CART) technique to analyze online hotel customer component ratings and their relationship to overall hotel satisfaction ratings. We demonstrate that the CART technique shows how strongly component ratings associate with the overall hotel satisfaction rating. Although customer satisfaction ratings are important to customer decisions about which hotel to engage, we have found that little research has been done on this topic. We provide recommendations to hotel managers about how they can collect and analyze online ratings data to help improve the overall satisfaction of their customers.

Keywords: CLASSIFICATION AND REGRESSION TREE; CUSTOMER SATISFACTION; DATA MINING; HOTEL MANAGEMENT; ONLINE CUSTOMER RATINGS; ONLINE FEEDBACK

Document Type: Research Article

DOI: https://doi.org/10.3727/154427209789130620

Publication date: 2009-03-01

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  • Tourism Review International is a peer-reviewed journal that advances excellence in all fields of tourism research, promotes high-level tourism knowledge, and nourishes cultural awareness in all sectors of the tourism industry by integrating industry and academic perspectives. Its international and interdisciplinary nature ensures that the needs of those interested in tourism are served by documenting industry practices, discussing tourism management and planning issues, providing a forum for primary research and critical examinations of previous research, and by chronicling changing tourism patterns and trends at the local, regional and global scale.
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