Big data for big insights: Investigating language-specific drivers of hotel satisfaction with 412, 784 user-generated reviews. (April 2017)

• Record Type: Journal Article
• Authors: Liu, Yong; Teichert, Thorsten; Rossi, Matti; Li, Hongxiu; Hu, Feng
• Is Part Of: Tourism management. Volume 59(2017)
• Page Start: 554
• Page End: 563
• Publication Date: 2017-04
• Subjects: Big data -- Satisfaction -- Hotel -- Online reviews -- User-generated review -- TripAdvisor; Tourism -- Periodicals; 338.4791
• DOI: 10.1016/j.tourman.2016.08.012
• Languages: English
• ISSNs: 0261-5177

Abstract

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". Graphical abstract: Highlights: Domestic vs. international tourists' preference on hotel are studied using big data. Hotel attributes preference of tourists from nine countries are examined. Travel types, e.g. business vs. leisure have significant mediating effects. Methodological contributions of the study are highlighted.