Restaurant Rating
Reviews, Reputation, and Revenue: The Case of Yelp.com
Michael Luca
Working Paper
12-016 September 16, 2011
Copyright © 2011 by Michael Luca Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be reproduced without permission of the copyright holder. Copies of working papers are available from the author.
Reviews, Reputation, and Revenue: The Case of Yelp.com
Michael Luca† September 2011
Abstract
Do online consumer reviews affect restaurant demand? I investigate this question using a novel dataset combining reviews from the website Yelp.com and restaurant data from the Washington State Department of Revenue. Because Yelp prominently displays a restaurant 's rounded average rating, I can identify the causal impact of Yelp ratings on demand with a regression discontinuity framework that exploits Yelp‟s rounding thresholds. I present three findings about the impact of consumer reviews on the restaurant industry: (1) a one-star increase in Yelp rating leads to a 5-9 percent increase in revenue, (2) this effect is driven by independent restaurants; ratings do not affect restaurants with chain affiliation, and (3) chain restaurants have declined in market share as Yelp penetration has increased. This suggests that online consumer reviews substitute for more traditional forms of reputation. I then test whether consumers use these reviews in a way that is consistent with standard learning models. I present two additional findings: (4) consumers do not use all available information and are more responsive to quality changes that are more visible and (5) consumers respond more strongly when a rating contains more information. Consumer response to a restaurant‟s average rating is affected by the number of reviews and whether the reviewers are certified as “elite” by Yelp, but is unaffected by the size of the reviewers‟ Yelp friends network.
†
Harvard Business School, mluca@hbs.edu
Michael Luca
Working Paper
12-016 September 16, 2011
Copyright © 2011 by Michael Luca Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may not be reproduced without permission of the copyright holder. Copies of working papers are available from the author.
Reviews, Reputation, and Revenue: The Case of Yelp.com
Michael Luca† September 2011
Abstract
Do online consumer reviews affect restaurant demand? I investigate this question using a novel dataset combining reviews from the website Yelp.com and restaurant data from the Washington State Department of Revenue. Because Yelp prominently displays a restaurant 's rounded average rating, I can identify the causal impact of Yelp ratings on demand with a regression discontinuity framework that exploits Yelp‟s rounding thresholds. I present three findings about the impact of consumer reviews on the restaurant industry: (1) a one-star increase in Yelp rating leads to a 5-9 percent increase in revenue, (2) this effect is driven by independent restaurants; ratings do not affect restaurants with chain affiliation, and (3) chain restaurants have declined in market share as Yelp penetration has increased. This suggests that online consumer reviews substitute for more traditional forms of reputation. I then test whether consumers use these reviews in a way that is consistent with standard learning models. I present two additional findings: (4) consumers do not use all available information and are more responsive to quality changes that are more visible and (5) consumers respond more strongly when a rating contains more information. Consumer response to a restaurant‟s average rating is affected by the number of reviews and whether the reviewers are certified as “elite” by Yelp, but is unaffected by the size of the reviewers‟ Yelp friends network.
†
Harvard Business School, mluca@hbs.edu
References: 25 Luca, Michael and Jonathan Smith, 2010 Wang, Zhongmin, 2010. “Anonymity, Social Image, and the Competition for Volunteers: A Case Study of the Online Market for Reviews,” The B.E. Journal of Economic Analysis and Policy, Vol. 10, No. 1, Article 44.