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Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews

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  • Liu, Yong
  • Teichert, Thorsten
  • Rossi, Matti
  • Li, Hongxiu
  • Hu, Feng

Abstract

This study leveraged the advantages of user-generated reviews with the aim of offering new insights into the determinants of hotel customer satisfaction by discriminating among customers by language group. From a collection of 412,784 user-generated reviews on TripAdvisor for 10,149 hotels from five Chinese cities, we found that foreign tourists, who speak diverse languages (English, German, French, Italian, Portuguese, Spanish, Japanese, and Russian), differ substantially in terms of their emphasis on the roles of various hotel attributes (“Rooms,” “Location,” “Cleanliness,” “Service,” and “Value”) in forming their overall satisfaction rating for hotels. Chinese tourists domestically exhibit distinct preferences for room-related hotel attributes when compared to foreign tourists. Major interaction effects are revealed between the attributes “Rooms” and “Service” and between “Value” and “Service”.

Suggested Citation

  • Liu, Yong & Teichert, Thorsten & Rossi, Matti & Li, Hongxiu & Hu, Feng, 2017. "Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412,784 user-generated reviews," Tourism Management, Elsevier, vol. 59(C), pages 554-563.
    • Handle: RePEc:eee:touman:v:59:y:2017:i:c:p:554-563
    DOI: 10.1016/j.tourman.2016.08.012
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