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Impacts of consumer cognitive process to ascertain online fake review: A cognitive dissonance theory approach

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  • Chatterjee, Sheshadri
  • Chaudhuri, Ranjan
  • Kumar, Ajay
  • Lu Wang, Cheng
  • Gupta, Shivam

Abstract

Online reviews of the products by consumers are very important to organizations as well as to prospective consumers. Ideally, online reviews by consumers should be an accurate and true representation of consumers’ feelings and experiences towards a particular product. But the online review process is also vulnerable to unethical representations of consumers’ experiences feeling towards particular product. Although if a deceptive review has been posted or not, it is essential to understand the perception of the consumers regarding deception because it is the perception of a consumer that leads them to the subsequent opinion and the follow-up action in the form of biased and fake online review. Very little study has been conducted on the impacts of consumer cognitive process to detect the intention of the reviewer to give fake reviews. In this background, the aim of this study is to examine the impact of consumer cognitive process towards detection of fake review. The study also investigates the moderating impacts of product knowledge towards online fake review. With the help of cognitive dissonance theory approach and existing literature, a theoretical model has been developed conceptually which subsequently validated using partial least square structural equation modelling considering responses from 342 respondents. The study found that there is a significant impact of consumer cognitive process on reviewer attitude towards detecting fake review. The study also revealed that there is a significant moderating impact of consumer product knowledge which influences the relationship between consumer attitude towards online review and perceived intention to give online fake review by the reviewers.

Suggested Citation

  • Chatterjee, Sheshadri & Chaudhuri, Ranjan & Kumar, Ajay & Lu Wang, Cheng & Gupta, Shivam, 2023. "Impacts of consumer cognitive process to ascertain online fake review: A cognitive dissonance theory approach," Journal of Business Research, Elsevier, vol. 154(C).
    • Handle: RePEc:eee:jbrese:v:154:y:2023:i:c:s0148296322008359
    DOI: 10.1016/j.jbusres.2022.113370
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    References listed on IDEAS

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    1. David F. Larcker & Anastasia A. Zakolyukina, 2012. "Detecting Deceptive Discussions in Conference Calls," Journal of Accounting Research, Wiley Blackwell, vol. 50(2), pages 495-540, May.
    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. 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. Alba, Joseph W & Hutchinson, J Wesley, 2000. "Knowledge Calibration: What Consumers Know and What They Think They Know," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 27(2), pages 123-156, September.
    5. Mishra, Anubhav & Maheswarappa, Satish S. & Maity, Moutusy & Samu, Sridhar, 2018. "Adolescent's eWOM intentions: An investigation into the roles of peers, the Internet and gender," Journal of Business Research, Elsevier, vol. 86(C), pages 394-405.
    6. Zhuang, Mengzhou & Cui, Geng & Peng, Ling, 2018. "Manufactured opinions: The effect of manipulating online product reviews," Journal of Business Research, Elsevier, vol. 87(C), pages 24-35.
    7. Domenico, Giandomenico Di & Sit, Jason & Ishizaka, Alessio & Nunan, Daniel, 2021. "Fake news, social media and marketing: A systematic review," Journal of Business Research, Elsevier, vol. 124(C), pages 329-341.
    8. Riquelme, Isabel P. & Román, Sergio & Iacobucci, Dawn, 2016. "Consumers' Perceptions of Online and Offline Retailer Deception: A Moderated Mediation Analysis," Journal of Interactive Marketing, Elsevier, vol. 35(C), pages 16-26.
    9. Brucks, Merrie, 1985. "The Effects of Product Class Knowledge on Information Search Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(1), pages 1-16, June.
    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. Daria Plotkina & Andreas Munzel & Jessie Pallud, 2020. "Illusions of truth—Experimental insights into human and algorithmic detections of fake online reviews," Post-Print hal-02423585, HAL.
    12. Isabel Riquelme & Sergio Román, 2014. "The Influence of Consumers’ Cognitive and Psychographic Traits on Perceived Deception: A Comparison Between Online and Offline Retailing Contexts," Journal of Business Ethics, Springer, vol. 119(3), pages 405-422, February.
    13. Clay M. Voorhees & Michael K. Brady & Roger Calantone & Edward Ramirez, 2016. "Discriminant validity testing in marketing: an analysis, causes for concern, and proposed remedies," Journal of the Academy of Marketing Science, Springer, vol. 44(1), pages 119-134, January.
    14. 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)

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