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Fake Google restaurant reviews and the implications for consumers and restaurants

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  • Shawn Berry

Abstract

The use of online reviews to aid with purchase decisions is popular among consumers as it is a simple heuristic tool based on the reported experiences of other consumers. However, not all online reviews are written by real consumers or reflect actual experiences, and present implications for consumers and businesses. This study examines the effects of fake online reviews written by artificial intelligence (AI) on consumer decision making. Respondents were surveyed about their attitudes and habits concerning online reviews using an online questionnaire (n=351), and participated in a restaurant choice experiment using varying proportions of fake and real reviews. While the findings confirm prior studies, new insights are gained about the confusion for consumers and consequences for businesses when reviews written by AI are believed rather than real reviews. The study presents a fake review detection model using logistic regression modeling to score and flag reviews as a solution.

Suggested Citation

  • Shawn Berry, 2024. "Fake Google restaurant reviews and the implications for consumers and restaurants," Papers 2401.11345, arXiv.org, revised Apr 2024.
    • Handle: RePEc:arx:papers:2401.11345
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    References listed on IDEAS

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    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. 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.
    3. Kapoor, Payal S. & M S, Balaji & Maity, Moutusy & Jain, Nikunj Kumar, 2021. "Why consumers exaggerate in online reviews? Moral disengagement and dark personality traits," Journal of Retailing and Consumer Services, Elsevier, vol. 60(C).
    4. Purnawirawan, Nathalia & Eisend, Martin & De Pelsmacker, Patrick & Dens, Nathalie, 2015. "A Meta-analytic Investigation of the Role of Valence in Online Reviews," Journal of Interactive Marketing, Elsevier, vol. 31(C), pages 17-27.
    5. Xiangbin Yan & Jing Wang & Michael Chau, 2015. "Customer revisit intention to restaurants: Evidence from online reviews," Information Systems Frontiers, Springer, vol. 17(3), pages 645-657, June.
    6. Septianto, Felix & Kemper, Joya A. & Choi, Jinyoung (Jane), 2020. "The power of beauty? The interactive effects of awe and online reviews on purchase intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 54(C).
    7. Moon, Sangkil & Kim, Moon-Yong & Iacobucci, Dawn, 2021. "Content analysis of fake consumer reviews by survey-based text categorization," International Journal of Research in Marketing, Elsevier, vol. 38(2), pages 343-364.
    8. Michael Hair & Timucin Ozcan, 2018. "How reviewers’ use of profanity affects perceived usefulness of online reviews," Marketing Letters, Springer, vol. 29(2), pages 151-163, June.
    9. Park, Sangwon & Nicolau, Juan L., 2015. "Asymmetric effects of online consumer reviews," Annals of Tourism Research, Elsevier, vol. 50(C), pages 67-83.
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    Cited by:

    1. Shawn Berry, 2024. "Consumer lying in online reviews: recent evidence," Papers 2405.12743, arXiv.org.

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