IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v41y2022i5p896-921.html
   My bibliography  Save this article

The Market for Fake Reviews

Author

Listed:
  • Sherry He

    (Anderson School of Management, University of California, Los Angeles, Los Angeles, California 90095)

  • Brett Hollenbeck

    (Anderson School of Management, University of California, Los Angeles, Los Angeles, California 90095)

  • Davide Proserpio

    (Marshall School of Business, University of Southern California, Los Angeles, California 90089)

Abstract

We study the market for fake product reviews on Amazon.com. Reviews are purchased in large private groups on Facebook and other sites. We hand-collect data on these markets and then collect a panel of data on these products’ ratings and reviews on Amazon, as well as their sales rank, advertising, and pricing policies. We find that a wide array of products purchase fake reviews, including products with many reviews and high average ratings. Buying fake reviews on Facebook is associated with a significant but short-term increase in average rating and number of reviews. We exploit a sharp but temporary policy shift by Amazon to show that rating manipulation has a large causal effect on sales. Finally, we examine whether rating manipulation harms consumers or whether it is mainly used by high-quality products in a manner like advertising or by new products trying to solve the cold-start problem. We find that after firms stop buying fake reviews, their average ratings fall and the share of one-star reviews increases significantly, particularly for young products, indicating rating manipulation is mostly used by low-quality products.

Suggested Citation

  • Sherry He & Brett Hollenbeck & Davide Proserpio, 2022. "The Market for Fake Reviews," Marketing Science, INFORMS, vol. 41(5), pages 896-921, September.
    • Handle: RePEc:inm:ormksc:v:41:y:2022:i:5:p:896-921
    DOI: 10.1287/mksc.2022.1353
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.2022.1353
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.2022.1353?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Dina Mayzlin & Yaniv Dover & Judith Chevalier, 2014. "Promotional Reviews: An Empirical Investigation of Online Review Manipulation," American Economic Review, American Economic Association, vol. 104(8), pages 2421-2455, August.
    2. Uttara M. Ananthakrishnan & Beibei Li & Michael D. Smith, 2020. "A Tangled Web: Should Online Review Portals Display Fraudulent Reviews?," Information Systems Research, INFORMS, vol. 31(3), pages 950-971, September.
    3. Yue Wu & Tansev Geylani, 2020. "Regulating Deceptive Advertising: False Claims and Skeptical Consumers," Marketing Science, INFORMS, vol. 39(4), pages 788-806, July.
    4. Yasui, Yuta, 2021. "Controlling Fake Reviews," MPRA Paper 108177, University Library of Munich, Germany.
    5. Liran Einav & Chiara Farronato & Jonathan Levin, 2016. "Peer-to-Peer Markets," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 615-635, October.
    6. Luís Cabral & Ali Hortaçsu, 2010. "The Dynamics Of Seller Reputation: Evidence From Ebay," Journal of Industrial Economics, Wiley Blackwell, vol. 58(1), pages 54-78, March.
    7. Brett Hollenbeck & Sridhar Moorthy & Davide Proserpio, 2019. "Advertising Strategy in the Presence of Reviews: An Empirical Analysis," Marketing Science, INFORMS, vol. 38(5), pages 793-811, September.
    8. Hollenbeck, Brett, 2018. "Online Reputation Mechanisms and the Decreasing Value of Chain Affliation," MPRA Paper 91573, University Library of Munich, Germany.
    9. Milgrom, Paul & Roberts, John, 1986. "Price and Advertising Signals of Product Quality," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 796-821, August.
    10. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    11. Nelson, Phillip, 1970. "Information and Consumer Behavior," Journal of Political Economy, University of Chicago Press, vol. 78(2), pages 311-329, March-Apr.
    12. Lesley Chiou & Catherine Tucker, 2018. "Fake News and Advertising on Social Media: A Study of the Anti-Vaccination Movement," NBER Working Papers 25223, National Bureau of Economic Research, Inc.
    13. Chris Nosko & Steven Tadelis, 2015. "The Limits of Reputation in Platform Markets: An Empirical Analysis and Field Experiment," NBER Working Papers 20830, National Bureau of Economic Research, Inc.
    14. Steven Tadelis, 2016. "Reputation and Feedback Systems in Online Platform Markets," Annual Review of Economics, Annual Reviews, vol. 8(1), pages 321-340, October.
    15. Michael Luca & Georgios Zervas, 2016. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Management Science, INFORMS, vol. 62(12), pages 3412-3427, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Salminen, Joni & Kandpal, Chandrashekhar & Kamel, Ahmed Mohamed & Jung, Soon-gyo & Jansen, Bernard J., 2022. "Creating and detecting fake reviews of online products," Journal of Retailing and Consumer Services, Elsevier, vol. 64(C).
    2. Hui, Xiang & Klein, Tobias & Stahl, Konrad, 2022. "Learning from Online Ratings," CEPR Discussion Papers 17006, C.E.P.R. Discussion Papers.
    3. Shukla, Aishwarya Deep & Goh, Jie Mein, 2024. "Fighting fake reviews: Authenticated anonymous reviews using identity verification," Business Horizons, Elsevier, vol. 67(1), pages 71-81.
    4. Ishita Chakraborty & Joyee Deb & Aniko Oery, 2020. "When Do Consumers Talk?," Cowles Foundation Discussion Papers 2254, Cowles Foundation for Research in Economics, Yale University.
    5. Krügel, Jan Philipp & Paetzel, Fabian, 2024. "The impact of fraud on reputation systems," Games and Economic Behavior, Elsevier, vol. 144(C), pages 329-354.
    6. Georgios Zervas & Davide Proserpio & John W. Byers, 2021. "A first look at online reputation on Airbnb, where every stay is above average," Marketing Letters, Springer, vol. 32(1), pages 1-16, March.
    7. Ko, Eunhee Emily & Bowman, Douglas, 2023. "Suspicious online product reviews: An empirical analysis of brand and product characteristics using Amazon data," International Journal of Research in Marketing, Elsevier, vol. 40(4), pages 898-911.
    8. Das, Ronnie & Ahmed, Wasim & Sharma, Kshitij & Hardey, Mariann & Dwivedi, Yogesh K. & Zhang, Ziqi & Apostolidis, Chrysostomos & Filieri, Raffaele, 2024. "Towards the development of an explainable e-commerce fake review index: An attribute analytics approach," European Journal of Operational Research, Elsevier, vol. 317(2), pages 382-400.
    9. Harrison-Walker, L. Jean & Jiang, Ying, 2023. "Suspicion of online product reviews as fake: Cues and consequences," Journal of Business Research, Elsevier, vol. 160(C).
    10. Fei Long & Yunchuan Liu, 2024. "Platform Manipulation in Online Retail Marketplace with Sponsored Advertising," Marketing Science, INFORMS, vol. 43(2), pages 317-345, March.
    11. Luis Aguiar, 2024. "Bad Apples on Rotten Tomatoes: Critics, Crowds, and Gender Bias in Product Ratings," CESifo Working Paper Series 11422, CESifo.
    12. Alexei Parahonyak & Nick Vikander, 2024. "Strategic Use of Product Delays to Shape Word-of-Mouth Communication," Economics Series Working Papers 1032, University of Oxford, Department of Economics.
    13. Young Joon Park & Jaewoo Joo & Charin Polpanumas & Yeujun Yoon, 2021. "“Worse Than What I Read?” The External Effect of Review Ratings on the Online Review Generation Process: An Empirical Analysis of Multiple Product Categories Using Amazon.com Review Data," Sustainability, MDPI, vol. 13(19), pages 1-22, September.
    14. Christoph Carnehl & Maximilian Schaefer & André Stenzel & Kevin Ducbao Tran, 2022. "Value for Money and Selection: How Pricing Affects Airbnb Ratings," Working Papers 684, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    15. Hajek, Petr & Hikkerova, Lubica & Sahut, Jean-Michel, 2023. "Fake review detection in e-Commerce platforms using aspect-based sentiment analysis," Journal of Business Research, Elsevier, vol. 167(C).
    16. Yassine Lefouili & Leonardo Madio, 2022. "The economics of platform liability," European Journal of Law and Economics, Springer, vol. 53(3), pages 319-351, June.
    17. Emily West, 2021. "Review Pollution: Pedagogy for a Post-Truth Society," Media and Communication, Cogitatio Press, vol. 9(3), pages 144-154.
    18. de Haan, Evert & Padigar, Manjunath & El Kihal, Siham & Kübler, Raoul & Wieringa, Jaap E., 2024. "Unstructured data research in business: Toward a structured approach," Journal of Business Research, Elsevier, vol. 177(C).
    19. Yingtong Chen & Fei Wu & Dayong Zhang & Qiang Ji, 2024. "Tourism in pandemic: the role of digital travel vouchers in China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-15, December.
    20. Daniel Ershov & Yanting, He & Stephan Seiler, 2023. "How Much Influencer Marketing Is Undisclosed? Evidence from Twitter," CESifo Working Paper Series 10743, CESifo.
    21. Wang, Qiang & Zhang, Wen & Li, Jian & Ma, Zhenzhong, 2023. "Complements or confounders? A study of effects of target and non-target features on online fraudulent reviewer detection," Journal of Business Research, Elsevier, vol. 167(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yasui, Yuta, 2021. "Controlling Fake Reviews," MPRA Paper 108177, University Library of Munich, Germany.
    2. Paul Belleflamme & Martin Peitz, 2018. "Inside the Engine Room of Digital Platforms: Reviews, Ratings, and Recommendations," Working Papers halshs-01714549, HAL.
    3. Brett Hollenbeck & Sridhar Moorthy & Davide Proserpio, 2019. "Advertising Strategy in the Presence of Reviews: An Empirical Analysis," Marketing Science, INFORMS, vol. 38(5), pages 793-811, September.
    4. Hui, Xiang & Klein, Tobias & Stahl, Konrad, 2022. "Learning from Online Ratings," CEPR Discussion Papers 17006, C.E.P.R. Discussion Papers.
    5. Zibo Liu & Zhijie Lin & Ying Zhang & Yong Tan, 2022. "The Signaling Effect of Sampling Size in Physical Goods Sampling Via Online Channels," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 529-546, February.
    6. Lingfang (Ivy) Li & Steven Tadelis & Xiaolan Zhou, 2020. "Buying reputation as a signal of quality: Evidence from an online marketplace," RAND Journal of Economics, RAND Corporation, vol. 51(4), pages 965-988, December.
    7. Gesche, Tobias, 2018. "Reference Price Shifts and Customer Antagonism: Evidence from Reviews for Online Auctions," VfS Annual Conference 2018 (Freiburg, Breisgau): Digital Economy 181650, Verein für Socialpolitik / German Economic Association.
    8. Erfan Rezvani & Christian Rojas, 2022. "Firm responsiveness to consumers' reviews: The effect on online reputation," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 31(4), pages 898-922, November.
    9. Apostolos Filippas & John J. Horton & Richard J. Zeckhauser, 2020. "Owning, Using, and Renting: Some Simple Economics of the “Sharing Economy”," Management Science, INFORMS, vol. 66(9), pages 4152-4172, September.
    10. Xiang Hui & Meng Liu, 2022. "Quality Certificates Alleviate Consumer Aversion to Sponsored Search Advertising," CESifo Working Paper Series 9886, CESifo.
    11. Andreas J. Steur & Mischa Seiter, 2021. "Properties of feedback mechanisms on digital platforms: an exploratory study," Journal of Business Economics, Springer, vol. 91(4), pages 479-526, May.
    12. Greiff, Matthias & Paetzel, Fabian, 2020. "Information about average evaluations spurs cooperation: An experiment on noisy reputation systems," Journal of Economic Behavior & Organization, Elsevier, vol. 180(C), pages 334-356.
    13. Hui Zhao & Xiaoyuan Wang & Debing Ni & Kevin W. Li, 2023. "The Quality-Signaling Role of Manipulated Consumer Reviews," Group Decision and Negotiation, Springer, vol. 32(3), pages 503-536, June.
    14. Fei Long & Yunchuan Liu, 2024. "Platform Manipulation in Online Retail Marketplace with Sponsored Advertising," Marketing Science, INFORMS, vol. 43(2), pages 317-345, March.
    15. Georgios Zervas & Davide Proserpio & John W. Byers, 2021. "A first look at online reputation on Airbnb, where every stay is above average," Marketing Letters, Springer, vol. 32(1), pages 1-16, March.
    16. Liting Li & Haichao Zheng & Dongyu Chen & Bin Zhu, 2024. "Whose reviews are most valuable for predicting the default risk of peer-to-peer lending platforms? Evidence from China," Electronic Commerce Research, Springer, vol. 24(3), pages 1619-1658, September.
    17. Pradeep K. Chintagunta & Junhong Chu, 2021. "Geography as branding: Descriptive evidence from Taobao," Quantitative Marketing and Economics (QME), Springer, vol. 19(1), pages 53-92, March.
    18. M. Narciso, 2022. "The Unreliability of Online Review Mechanisms," Journal of Consumer Policy, Springer, vol. 45(3), pages 349-368, September.
    19. Xiang Hui & Tobias J. Klein & Konrad Stahl, 2021. "When and Why Do Buyers Rate in Online Markets?," CRC TR 224 Discussion Paper Series crctr224_2021_267v1, University of Bonn and University of Mannheim, Germany.
    20. Peitz, Martin & Schwalbe, Ulrich, 2016. "Zwischen Sozialromantik und Neoliberalismus: Zur Ökonomie der Sharing-Economy," ZEW Discussion Papers 16-033, ZEW - Leibniz Centre for European Economic Research.

    More about this item

    Keywords

    word of mouth; electronic commerce; retailing;
    All these keywords.

    JEL classification:

    • K42 - Law and Economics - - Legal Procedure, the Legal System, and Illegal Behavior - - - Illegal Behavior and the Enforcement of Law
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • L51 - Industrial Organization - - Regulation and Industrial Policy - - - Economics of Regulation
    • L81 - Industrial Organization - - Industry Studies: Services - - - Retail and Wholesale Trade; e-Commerce
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:41:y:2022:i:5:p:896-921. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.