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Taking Fake Online Consumer Reviews Seriously

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  • Justin Malbon

Abstract

Evidence discussed in this article indicates that consumers rely heavily upon consumer reviews when making decisions about which products and services to purchase online. Sellers and their marketeers are aware of this, and as a result, some of them succumb to the temptation to generate fake consumer reviews. This article argues that policymakers and regulators need to take fake reviews seriously. This is because they undermine a (potentially) effective and efficient mechanism for overcoming information asymmetry between online sellers and buyers. Consumer reviews also offer a powerful mechanism for regulating the marketplace. Sellers who sell sub-standard products or engage in sub-standard selling practices risk reputational damage. Genuine consumer reviews can therefore moderate bad seller behaviour and assist in improving the quality and efficiency of the marketplace. Although there are laws in many jurisdictions that prohibit misleading and deceptive conduct, detecting fake reviews is complex and difficult. This article proposes that one way of increasing the effectiveness of regulatory oversight is for regulators to add an “alliance approach” to their existing arsenal of regulatory systems and mechanisms. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • Justin Malbon, 2013. "Taking Fake Online Consumer Reviews Seriously," Journal of Consumer Policy, Springer, vol. 36(2), pages 139-157, June.
    • Handle: RePEc:kap:jcopol:v:36:y:2013:i:2:p:139-157
    DOI: 10.1007/s10603-012-9216-7
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    References listed on IDEAS

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    Cited by:

    1. Junran Wu & Ke Xu & Jichang Zhao, 2019. "Online reviews can predict long-term returns of individual stocks," Papers 1905.03189, arXiv.org.
    2. Blazquez, Desamparados & Domenech, Josep, 2018. "Big Data sources and methods for social and economic analyses," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 99-113.
    3. Travis Dyer & Eunjee Kim, 2021. "Anonymous Equity Research," Journal of Accounting Research, Wiley Blackwell, vol. 59(2), pages 575-611, May.
    4. Munzel, Andreas, 2016. "Assisting consumers in detecting fake reviews: The role of identity information disclosure and consensus," Journal of Retailing and Consumer Services, Elsevier, vol. 32(C), pages 96-108.
    5. King, Robert Allen & Racherla, Pradeep & Bush, Victoria D., 2014. "What We Know and Don't Know About Online Word-of-Mouth: A Review and Synthesis of the Literature," Journal of Interactive Marketing, Elsevier, vol. 28(3), pages 167-183.
    6. Petrescu, Maria & Ajjan, Haya & Harrison, Dana L., 2023. "Man vs machine – Detecting deception in online reviews," Journal of Business Research, Elsevier, vol. 154(C).
    7. Wu, Ruhai & Qiu, Chun, 2023. "When Karma strikes back: A model of seller manipulation of consumer reviews in an online marketplace," Journal of Business Research, Elsevier, vol. 155(PB).
    8. Janßen, Rebecca & Klock, David, 2023. "Fünf Sterne für ein Halleluja: Welche ökonomisch positiven Funktionen haben Kundenbewertungen noch und können neue Gesetzesänderungen den Verbraucherschutz stärken?," ZEW Expert Briefs 23-01, ZEW - Leibniz Centre for European Economic Research.
    9. Mustak, Mekhail & Salminen, Joni & Mäntymäki, Matti & Rahman, Arafat & Dwivedi, Yogesh K., 2023. "Deepfakes: Deceptions, mitigations, and opportunities," Journal of Business Research, Elsevier, vol. 154(C).
    10. Plotkina, Daria & Munzel, Andreas & Pallud, Jessie, 2020. "Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews," Journal of Business Research, Elsevier, vol. 109(C), pages 511-523.
    11. Poddar, Amit & Banerjee, Syagnik & Sridhar, Karthik, 2019. "False advertising or slander? Using location based tweets to assess online rating-reliability," Journal of Business Research, Elsevier, vol. 99(C), pages 390-397.
    12. Engler, Tobias H. & Winter, Patrick & Schulz, Michael, 2015. "Understanding online product ratings: A customer satisfaction model," Journal of Retailing and Consumer Services, Elsevier, vol. 27(C), pages 113-120.
    13. Hutzinger, Clemens & Weitzl, Wolfgang J., 2021. "Co-creation of online service recoveries and its effects on complaint bystanders," Journal of Business Research, Elsevier, vol. 130(C), pages 525-538.
    14. Harman Preet Singh & Ibrahim Abdullah Alhamad, 2022. "A Novel Categorization of Key Predictive Factors Impacting Hotels’ Online Ratings: A Case of Makkah," Sustainability, MDPI, vol. 14(24), pages 1-25, December.

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