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Aggregation of Consumer Ratings: An Application to Yelp.com

Author

Listed:
  • Weijia Dai
  • Ginger Z. Jin
  • Jungmin Lee
  • Michael Luca

Abstract

Because consumer reviews leverage the wisdom of the crowd, the way in which they are aggregated is a central decision faced by platforms. We explore this "rating aggregation problem" and offer a structural approach to solving it, allowing for (1) reviewers to vary in stringency and accuracy, (2) reviewers to be influenced by existing reviews, and (3) product quality to change over time. Applying this to restaurant reviews from Yelp.com, we construct an adjusted average rating and show that even a simple algorithm can lead to large information efficiency gains relative to the arithmetic average.

Suggested Citation

  • Weijia Dai & Ginger Z. Jin & Jungmin Lee & Michael Luca, 2012. "Aggregation of Consumer Ratings: An Application to Yelp.com," NBER Working Papers 18567, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:18567
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Verena Dorner & Marcus Giamattei & Matthias Greiff, 0. "The Market for Reviews: Strategic Behavior of Online Product Reviewers with Monetary Incentives," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 0, pages 1-39.
    2. Michael Luca, 2016. "Designing Online Marketplaces: Trust and Reputation Mechanisms," NBER Chapters, in: Innovation Policy and the Economy, Volume 17, pages 77-93, National Bureau of Economic Research, Inc.
    3. Marios Kokkodis & Theodoros Lappas, 2020. "Your Hometown Matters: Popularity-Difference Bias in Online Reputation Platforms," Information Systems Research, INFORMS, vol. 31(2), pages 412-430, June.
    4. Michael Luca & Oren Reshef, 2020. "The Impact of Prices on Firm Reputation," NBER Working Papers 27405, National Bureau of Economic Research, Inc.
    5. Liad Wagman & Vincent Conitzer, 2014. "False-name-proof voting with costs over two alternatives," International Journal of Game Theory, Springer;Game Theory Society, vol. 43(3), pages 599-618, August.
    6. Michael Luca, 2016. "Designing Online Marketplaces: Trust and Reputation Mechanisms," NBER Working Papers 22616, National Bureau of Economic Research, Inc.
    7. Verena Dorner & Marcus Giamattei & Matthias Greiff, 2020. "The Market for Reviews: Strategic Behavior of Online Product Reviewers with Monetary Incentives," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 72(3), pages 397-435, July.
    8. Simon Martin & Sandro Shelegia, 2019. "Underpromise and Overdeliver? - Online Product Reviews and Firm Pricing," Working Papers 1123, Barcelona Graduate School of Economics.
    9. Feng Zhu & Qihong Liu, 2018. "Competing with complementors: An empirical look at Amazon.com," Strategic Management Journal, Wiley Blackwell, vol. 39(10), pages 2618-2642, October.
    10. Amedeo Piolatto, 2015. "Online booking and information: competition and welfare consequences of review aggregators," Working Papers 2015/11, Institut d'Economia de Barcelona (IEB).
    11. Michael Luca & Georgios Zervas, 2013. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Harvard Business School Working Papers 14-006, Harvard Business School, revised May 2015.
    12. Michael Luca, 2017. "Designing Online Marketplaces: Trust and Reputation Mechanisms," Innovation Policy and the Economy, University of Chicago Press, vol. 17(1), pages 77-93.
    13. Marcello Basili & Maria Alessandra Rossi, 2018. "Platform-mediated reputation systems in the sharing economy and incentives to provide service quality: the case of ridesharing services," Department of Economics University of Siena 787, Department of Economics, University of Siena.
    14. Michael Luca, 2016. "Designing Online Marketplaces: Trust and Reputation Mechanisms," Harvard Business School Working Papers 17-017, Harvard Business School.
    15. Benjamin Edelman & Micahel Luca, 2014. "Digital Discrimination: The Case of Airbnb.com," Harvard Business School Working Papers 14-054, Harvard Business School.

    More about this item

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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