A first look at online reputation on Airbnb, where every stay is above average
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A first look at online reputation on Airbnb, where every stay is above average Georgios Zervas 1 & Davide Proserpio 2
& John
W. Byers 3
Accepted: 29 September 2020/ # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Judging by the millions of reviews left by guests on the Airbnb platform, this trusted community marketplace for accommodations is fulfilling its mission of matching travelers with hosts having room to spare remarkably well. Based on our analysis of ratings, we collected for millions of properties listed on Airbnb worldwide, we find that nearly 95% of Airbnb properties boast an average star-rating of either 4.5 or 5 stars (the maximum); virtually none have less than a 3.5 star-rating. We contrast this with the ratings of roughly 700,000 hotels, B&Bs, and vacation rentals worldwide that we collected from TripAdvisor. We find that hotel and B&B average ratings are much lower—3.8 and 4.1 stars, respectively—with much more variance across reviews. TripAdvisor vacation rental ratings are more similar to Airbnb ratings, but only about 85% of properties have an average rating of 4.5 or 5 stars. We then consider properties cross-listed on both platforms. For these properties, we find that even though the average ratings on Airbnb and TripAdvisor are more similar than hotels and B&Bs, proportionally more properties receive the highest ratings (4.5 stars and above) on Airbnb than on TripAdvisor. Moreover, there is only a weak correlation in the ratings of individual cross-listed properties across the two platforms. Finally, we show that these differences are consistent when considering data from two different time periods: 2015 and 2018. Keywords Airbnb . Reputation . Reviews . Trust . Sharing economy
Electronic supplementary material The online version of this article (https://doi.org/10.1007/s11002-02009546-4) contains supplementary material, which is available to authorized users.
* Davide Proserpio [email protected] Georgios Zervas [email protected] John W. Byers [email protected] Extended author information available on the last page of the article
Marketing Letters
1 Introduction Online reviews are a significant driver of consumer behavior, providing a convenient mechanism for consumers to discover, evaluate, and compare products and services on the Web. Yet, users of existing review platforms generate distributions of star-ratings that are unlikely to reflect true product quality. Most empirical papers that have analyzed the distributions of ratings arising on major review platforms have arrived at a similar conclusion: ratings tend to be overwhelmingly positive, mixed with a small but noticeable number of highly negative reviews, giving rise to what has been characterized as a J-shaped distribution (Hu et al. 2009). Considerable effort has been dedicated to understanding how these distributions arise. The abundance of positive reviews on online platforms has been linked to at least four different underlying phenomena in the literature: herding behavior, underreporting of negative rev
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