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The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry

Author

Listed:
  • Theodoros Lappas

    (Stevens Institute of Technology, Hoboken, New Jersey 07030)

  • Gaurav Sabnis

    (Stevens Institute of Technology, Hoboken, New Jersey 07030)

  • Georgios Valkanas

    (Stevens Institute of Technology, Hoboken, New Jersey 07030)

Abstract

Extant research has focused on the detection of fake reviews on online review platforms, motivated by the well-documented impact of customer reviews on the users’ purchase decisions. The problem is typically approached from the perspective of protecting the credibility of review platforms, as well as the reputation and revenue of the reviewed firms. However, there is little examination of the vulnerability of individual businesses to fake review attacks. This study focuses on formalizing the visibility of a business to the customer base and on evaluating its vulnerability to fake review attacks. We operationalize visibility as a function of the features that a business can cover and its position in the platform’s review-based ranking. Using data from over 2.3 million reviews of 4,709 hotels from 17 cities, we study how visibility can be impacted by different attack strategies. We find that even limited injections of fake reviews can have a significant effect and explore the factors that contribute to this vulnerable state. Specifically, we find that, in certain markets, 50 fake reviews are sufficient for an attacker to surpass any of its competitors in terms of visibility. We also compare the strategy of self-injecting positive reviews with that of injecting competitors with negative reviews and find that each approach can be as much as 40% more effective than the other across different settings. We empirically explore response strategies for an attacked hotel, ranging from the enhancement of its own features to detecting and disputing fake reviews. In general, our measure of visibility and our modeling approach regarding attack and response strategies shed light on how businesses that are targeted by fake reviews can detect and tackle such attacks.

Suggested Citation

  • Theodoros Lappas & Gaurav Sabnis & Georgios Valkanas, 2016. "The Impact of Fake Reviews on Online Visibility: A Vulnerability Assessment of the Hotel Industry," Information Systems Research, INFORMS, vol. 27(4), pages 940-961, December.
    • Handle: RePEc:inm:orisre:v:27:y:2016:i:4:p:940-961
    DOI: 10.1287/isre.2016.0674
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    References listed on IDEAS

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    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. Young Kwark & Jianqing Chen & Srinivasan Raghunathan, 2014. "Online Product Reviews: Implications for Retailers and Competing Manufacturers," Information Systems Research, INFORMS, vol. 25(1), pages 93-110, March.
    3. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    4. Chakravarthi Narasimhan & Özge Turut, 2013. "Differentiate or Imitate? The Role of Context-Dependent Preferences," Marketing Science, INFORMS, vol. 32(3), pages 393-410, May.
    5. Pan, Bing, 2015. "The power of search engine ranking for tourist destinations," Tourism Management, Elsevier, vol. 47(C), pages 79-87.
    6. Decker, Reinhold & Trusov, Michael, 2010. "Estimating aggregate consumer preferences from online product reviews," International Journal of Research in Marketing, Elsevier, vol. 27(4), pages 293-307.
    7. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2014. "Examining the Impact of Ranking on Consumer Behavior and Search Engine Revenue," Management Science, INFORMS, vol. 60(7), pages 1632-1654, July.
    8. Xianghua Lu & Sulin Ba & Lihua Huang & Yue Feng, 2013. "Promotional Marketing or Word-of-Mouth? Evidence from Online Restaurant Reviews," Information Systems Research, INFORMS, vol. 24(3), pages 596-612, September.
    9. Silvia Ferrari & Francisco Cribari-Neto, 2004. "Beta Regression for Modelling Rates and Proportions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(7), pages 799-815.
    10. Chris Forman & Anindya Ghose & Batia Wiesenfeld, 2008. "Examining the Relationship Between Reviews and Sales: The Role of Reviewer Identity Disclosure in Electronic Markets," Information Systems Research, INFORMS, vol. 19(3), pages 291-313, September.
    11. Anindya Ghose & Panagiotis G. Ipeirotis & Beibei Li, 2012. "Designing Ranking Systems for Hotels on Travel Search Engines by Mining User-Generated and Crowdsourced Content," Marketing Science, INFORMS, vol. 31(3), pages 493-520, May.
    12. 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 & Policy, De Gruyter, vol. 10(1), pages 1-35, May.
    13. Lori Lorigo & Maya Haridasan & Hrönn Brynjarsdóttir & Ling Xia & Thorsten Joachims & Geri Gay & Laura Granka & Fabio Pellacini & Bing Pan, 2008. "Eye tracking and online search: Lessons learned and challenges ahead," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(7), pages 1041-1052, May.
    14. Catherine Tucker & Juanjuan Zhang, 2011. "How Does Popularity Information Affect Choices? A Field Experiment," Management Science, INFORMS, vol. 57(5), pages 828-842, May.
    15. Sparks, Beverley A. & Browning, Victoria, 2011. "The impact of online reviews on hotel booking intentions and perception of trust," Tourism Management, Elsevier, vol. 32(6), pages 1310-1323.
    16. Octavian Carare, 2012. "The Impact Of Bestseller Rank On Demand: Evidence From The App Market," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 53(3), pages 717-742, August.
    17. 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.
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