Bias and Reciprocity in Online Reviews: Evidence From Field Experiments on Airbnb

Reviews and other evaluations are used by consumers to decide what goods to buy and by firms to choose whom to trade with, hire, or promote. However, because potential reviewers are not compensated for submitting reviews and may have reasons to omit relevant information in their reviews, reviews may be biased. We use the setting of Airbnb to study the determinants of reviewing behavior, the extent to which reviews are biased, and whether changes in the design of reputation systems can reduce that bias. We find that reviews on Airbnb are generally informative and 97% of guests privately report having positive experiences. Using two field experiments intended to reduce bias, we show that non-reviewers tend to have worse experiences than reviewers and that strategic reviewing behavior occurred on the site, although the aggregate effect of the strategic behavior was relatively small. We use a quantitative exercise to show that the mechanisms for bias that we document decrease the rate of reviews with negative text and a non-recommendation by just .86 percentage points. Lastly, we discuss how online marketplaces can design more informative review systems.

[1]  Amanda Pallais Ineffiient Hiring in Entry-Level Labor Markets , 2012 .

[2]  J. Tirole,et al.  Incentives and Prosocial Behavior , 2005 .

[3]  David F. Sally Conversation and Cooperation in Social Dilemmas , 1995 .

[4]  Lingfang Li,et al.  Money Talks: Rebate Mechanisms in Reputation System Design , 2010, Manag. Sci..

[5]  Roberto A. Weber,et al.  Sorting in Experiments with Application to Social Preferences , 2019 .

[6]  Gary E. Bolton,et al.  Engineering Trust - Reciprocity in the Production of Reputation Information , 2009, Manag. Sci..

[7]  Michael Luca Reviews, Reputation, and Revenue: The Case of Yelp.Com , 2016 .

[8]  Chrysanthos Dellarocas,et al.  The Sound of Silence in Online Feedback: Estimating Trading Risks in the Presence of Reporting Bias , 2006, Manag. Sci..

[9]  F. Nagle,et al.  Online Word of Mouth and Product Quality Disagreement , 2014 .

[10]  Georgios Zervas,et al.  A first look at online reputation on Airbnb, where every stay is above average , 2015, Marketing Letters.

[11]  Neel Sundaresan,et al.  From Lemon Markets to Managed Markets: The Evolution of eBay’s Reputation System∗ , 2014 .

[12]  V. Smith,et al.  Social distance and other-regarding behavior in dictator games , 2000 .

[13]  Steven Tadelis,et al.  The Limits of Reputation in Platform Markets: An Empirical Analysis and Field Experiment , 2015 .

[14]  Luís M. B. Cabral,et al.  The Dynamics of Seller Reputation: Evidence from Ebay , 2006 .

[15]  Iris Bohnet,et al.  The sound of silence in prisoner's dilemma and dictator games , 1999 .

[16]  V. Smith,et al.  Preferences, Property Rights, and Anonymity in Bargaining Games , 1994 .

[17]  Neel Sundaresan,et al.  The Value of Feedback: An Analysis of Reputation System , 2014 .

[18]  P. Resnick,et al.  The Market for Evaluations , 1999 .

[19]  Andrey Fradkin,et al.  Search Frictions and the Design of Online Marketplaces , 2015, AMMA 2015.

[20]  Ulrike Malmendier,et al.  Rethinking Reciprocity , 2013 .

[21]  Michael Luca,et al.  Aggregation of Consumer Ratings: An Application to Yelp.com , 2012 .

[22]  David A. Schweidel,et al.  Online Product Opinions: Incidence, Evaluation, and Evolution , 2012, Mark. Sci..

[23]  Dina Mayzlin,et al.  Promotional Reviews: An Empirical Investigation of Online Review Manipulation , 2012 .

[24]  J. List,et al.  Testing for Altruism and Social Pressure in Charitable Giving , 2009, The quarterly journal of economics.

[25]  Lingfang Li,et al.  A Dollar for Your Thoughts: Feedback-Conditional Rebates on Ebay , 2014, Manag. Sci..

[26]  Justin M. Rao,et al.  The Power of Asking: How Communication Affects Selfishness, Empathy, and Altruism , 2010 .

[27]  Michael Luca,et al.  Aggregation of consumer ratings: an application to Yelp.com , 2012 .

[28]  Paul Resnick,et al.  Eliciting Informative Feedback: The Peer-Prediction Method , 2005, Manag. Sci..