Robust Regression Discontinuity Estimates Of The Causal Effect Of The Tripadvisor’s Bubble Rating On Hotel Popularity

Elena Pokryshevskaya () and Evgeny Antipov
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Elena Pokryshevskaya: National Research University Higher School of Economics

HSE Working papers from National Research University Higher School of Economics

Abstract: In this paper we use detailed data on 4,599 hotels located in Rome collected from TripAdvisor, the world's largest travel platform, to examine the causal effects of bubble ratings (detailed to half-bubbles) on hotel popularity measured with the number of people viewing the hotel’s page. By using a regression discontinuity design, we find that bubble presentation of ratings does not create any significant jumps at cutoffs. This result is different from those obtained in previous studies of similarly designed rating systems from other industries. Another finding is that web users tend to shortlist hotels with the bubble rating of at least 3. Despite that, there is no strong evidence of review manipulation around the 2.75 cutoff to make a transition from the 2.5-bubble rating to the 3-bubble rating. Potential uses of the number of views as a proxy of demand in hospitality and tourism research are outlined.

Keywords: regression discontinuity; ratings; sales; booking; hotel reviews; TripAdvisor (search for similar items in EconPapers)
JEL-codes: L83 M31 (search for similar items in EconPapers)
Pages: 13 pages
Date: 2020
New Economics Papers: this item is included in nep-pay and nep-tur
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Published in WP BRP Series: Management / MAN, December 2020, pages 1-13

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