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Research Note—When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth

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  • Dezhi Yin

    (Trulaske College of Business, University of Missouri, Columbia, Missouri 65211)

  • Sabyasachi Mitra

    (Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia 30308)

  • Han Zhang

    (Scheller College of Business, Georgia Institute of Technology, Atlanta, Georgia 30308)

Abstract

In the online word-of-mouth literature, research has consistently shown that negative reviews have a greater impact on product sales than positive reviews. Although this negativity effect is well documented at the product level, there is less consensus on whether negative or positive reviews are perceived to be more helpful by consumers. A limited number of studies document a higher perceived helpfulness for negative reviews under certain conditions, but accumulating empirical evidence suggests the opposite. To reconcile these contradictory findings, we propose that consumers can form initial beliefs about a product on the basis of the product’s summary rating statistics (such as the average and dispersion of the product’s ratings) and that these initial beliefs play a vital role in their subsequent evaluation of individual reviews. Using a unique panel data set collected from Apple’s App Store, we empirically demonstrate confirmation bias—that consumers have a tendency to perceive reviews that confirm (versus disconfirm) their initial beliefs as more helpful, and that this tendency is moderated by their confidence in their initial beliefs. Furthermore, we show that confirmation bias can lead to greater perceived helpfulness for positive reviews (positivity effect) when the average product rating is high, and for negative reviews (negativity effect) when the average product rating is low. Thus, the mixed findings in the literature can be a consequence of confirmation bias. This paper is among the first to incorporate the important role of consumers’ initial beliefs and confidence in such beliefs (a fundamental dimension of metacognition) into their evaluation of online reviews, and our findings have significant implications for researchers, retailers, and review websites.

Suggested Citation

  • Dezhi Yin & Sabyasachi Mitra & Han Zhang, 2016. "Research Note—When Do Consumers Value Positive vs. Negative Reviews? An Empirical Investigation of Confirmation Bias in Online Word of Mouth," Information Systems Research, INFORMS, vol. 27(1), pages 131-144, March.
  • Handle: RePEc:inm:orisre:v:27:y:2016:i:1:p:131-144
    DOI: 10.1287/isre.2015.0617
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    References listed on IDEAS

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    1. Monic Sun, 2012. "How Does the Variance of Product Ratings Matter?," Management Science, INFORMS, vol. 58(4), pages 696-707, April.
    2. Iacus, Stefano & King, Gary & Porro, Giuseppe, 2009. "cem: Software for Coarsened Exact Matching," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 30(i09).
    3. Duan, Wenjing & Gu, Bin & Whinston, Andrew B., 2008. "The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry," Journal of Retailing, Elsevier, vol. 84(2), pages 233-242.
    4. Jeffrey M Wooldridge, 2010. "Econometric Analysis of Cross Section and Panel Data," MIT Press Books, The MIT Press, edition 2, volume 1, number 0262232588, December.
    5. Stephen X. He & Samuel D. Bond, 2015. "Why Is the Crowd Divided? Attribution for Dispersion in Online Word of Mouth," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 41(6), pages 1509-1527.
    6. 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.
    7. Matthew Blackwell & Stefano Iacus & Gary King & Giuseppe Porro, 2009. "cem: Coarsened exact matching in Stata," Stata Journal, StataCorp LP, vol. 9(4), pages 524-546, December.
    8. Pan, Yue & Zhang, Jason Q., 2011. "Born Unequal: A Study of the Helpfulness of User-Generated Product Reviews," Journal of Retailing, Elsevier, vol. 87(4), pages 598-612.
    9. Zhang, Jason Q. & Craciun, Georgiana & Shin, Dongwoo, 2010. "When does electronic word-of-mouth matter? A study of consumer product reviews," Journal of Business Research, Elsevier, vol. 63(12), pages 1336-1341, December.
    10. Alba, Joseph W, et al, 1994. "The Influence of Prior Beliefs, Frequency Cues, and Magnitude Cues on Consumers' Perceptions of Comparative Price Data," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 21(2), pages 219-235, September.
    11. Anindya Ghose & Sang Pil Han, 2014. "Estimating Demand for Mobile Applications in the New Economy," Management Science, INFORMS, vol. 60(6), pages 1470-1488, June.
    12. Michael Scholz & Verena Dorner, 2013. "The Recipe for the Perfect Review?," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 5(3), pages 141-151, June.
    13. Iacus, Stefano M. & King, Gary & Porro, Giuseppe, 2012. "Causal Inference without Balance Checking: Coarsened Exact Matching," Political Analysis, Cambridge University Press, vol. 20(1), pages 1-24, January.
    14. Leonardo Grilli & Carla Rampichini, 2007. "A multilevel multinomial logit model for the analysis of graduates’ skills," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 16(3), pages 381-393, November.
    15. JaeHong Park & Prabhudev Konana & Bin Gu & Alok Kumar & Rajagopal Raghunathan, 2013. "Information Valuation and Confirmation Bias in Virtual Communities: Evidence from Stock Message Boards," Information Systems Research, INFORMS, vol. 24(4), pages 1050-1067, December.
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