IDEAS home Printed from https://ideas.repec.org/a/inm/ormksc/v31y2012i3p372-386.html
   My bibliography  Save this article

Online Product Opinions: Incidence, Evaluation, and Evolution

Author

Listed:
  • Wendy W. Moe

    (Robert H. Smith School of Business, University of Maryland, College Park, Maryland 20472)

  • David A. Schweidel

    (Wisconsin School of Business, University of Wisconsin-Madison, Madison, Wisconsin 53706)

Abstract

Whereas recent research has demonstrated the impact of online product ratings and reviews on product sales, we still have a limited understanding of the individual's decision to contribute these opinions. In this research, we empirically model the individual's decision to provide a product rating and investigate factors that influence this decision. Specifically, we consider how previously posted ratings may affect an individual's posting behavior in terms of whether to contribute (incidence) and what to contribute (evaluation), and we identify selection effects that influence the incidence decision and adjustment effects that influence the evaluation decision. Across individuals, our results show that positive ratings environments increase posting incidence, whereas negative ratings environments discourage posting. Our results also indicate important differences across individuals in how they respond to previously posted ratings, with less frequent posters exhibiting bandwagon behavior and more active customers revealing differentiation behavior. These dynamics affect the evolution of online product opinions. Through simulations, we illustrate how the evolution of posted product opinions is shaped by the underlying customer base and show that customer bases with the same median opinion may evolve in substantially different ways because of the presence of a core group of "activists" posting increasingly negative opinions.

Suggested Citation

  • Wendy W. Moe & David A. Schweidel, 2012. "Online Product Opinions: Incidence, Evaluation, and Evolution," Marketing Science, INFORMS, vol. 31(3), pages 372-386, May.
    • Handle: RePEc:inm:ormksc:v:31:y:2012:i:3:p:372-386
    DOI: 10.1287/mksc.1110.0662
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mksc.1110.0662
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mksc.1110.0662?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Ann E. Schlosser, 2005. "Posting versus Lurking: Communicating in a Multiple Audience Context," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 32(2), pages 260-265, September.
    2. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    3. Manfred Gartner, 1976. "Endogenous bandwagon and underdog effects in a rational choice model," Public Choice, Springer, vol. 25(1), pages 83-89, March.
    4. Eugene W. Anderson & Mary W. Sullivan, 1993. "The Antecedents and Consequences of Customer Satisfaction for Firms," Marketing Science, INFORMS, vol. 12(2), pages 125-143.
    5. Dmitri Kuksov & Ying Xie, 2010. "Pricing, Frills, and Customer Ratings," Marketing Science, INFORMS, vol. 29(5), pages 925-943, 09-10.
    6. Xinxin Li & Lorin M. Hitt, 2008. "Self-Selection and Information Role of Online Product Reviews," Information Systems Research, INFORMS, vol. 19(4), pages 456-474, December.
    7. David Godes & José C. Silva, 2012. "Sequential and Temporal Dynamics of Online Opinion," Marketing Science, INFORMS, vol. 31(3), pages 448-473, May.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Young-Jin Lee & Kartik Hosanagar & Yong Tan, 2015. "Do I Follow My Friends or the Crowd? Information Cascades in Online Movie Ratings," Management Science, INFORMS, vol. 61(9), pages 2241-2258, September.
    2. Qian Wang & Michael Chau & Chih-Hung Peng & Eric W. T. Ngai, 2022. "Using the Anchoring Effect and the Cultural Dimensions Theory to Study Customers’ Online Rating Behaviors," Information Systems Frontiers, Springer, vol. 24(5), pages 1451-1463, October.
    3. Yuchi Zhang & David Godes, 2018. "Learning from Online Social Ties," Marketing Science, INFORMS, vol. 37(3), pages 425-444, May.
    4. Liye Ma & Baohong Sun & Sunder Kekre, 2015. "The Squeaky Wheel Gets the Grease—An Empirical Analysis of Customer Voice and Firm Intervention on Twitter," Marketing Science, INFORMS, vol. 34(5), pages 627-645, September.
    5. Yi-Chun (Chad) Ho & Junjie Wu & Yong Tan, 2017. "Disconfirmation Effect on Online Rating Behavior: A Structural Model," Information Systems Research, INFORMS, vol. 28(3), pages 626-642, September.
    6. Christoph Schneider & Markus Weinmann & Peter N.C. Mohr & Jan vom Brocke, 2021. "When the Stars Shine Too Bright: The Influence of Multidimensional Ratings on Online Consumer Ratings," Management Science, INFORMS, vol. 67(6), pages 3871-3898, June.
    7. S. Cicognani & P. Figini & M. Magnani, 2016. "Social Influence Bias in Online Ratings: A Field Experiment," Working Papers wp1060, Dipartimento Scienze Economiche, Universita' di Bologna.
    8. Zhang, Ziqiong & Zhang, Zili & Yang, Yang, 2016. "The power of expert identity: How website-recognized expert reviews influence travelers' online rating behavior," Tourism Management, Elsevier, vol. 55(C), pages 15-24.
    9. Tao Lu & May Yuan & Chong (Alex) Wang & Xiaoquan (Michael) Zhang, 2022. "Histogram Distortion Bias in Consumer Choices," Management Science, INFORMS, vol. 68(12), pages 8963-8978, December.
    10. Nachiketa Sahoo & Chrysanthos Dellarocas & Shuba Srinivasan, 2018. "The Impact of Online Product Reviews on Product Returns," Information Systems Research, INFORMS, vol. 29(3), pages 723-738, September.
    11. Zhijie Lin & Ying Zhang & Yong Tan, 2019. "An Empirical Study of Free Product Sampling and Rating Bias," Service Science, INFORMS, vol. 30(1), pages 260-275, March.
    12. Heeseung Andrew Lee & Angela Aerry Choi & Tianshu Sun & Wonseok Oh, 2021. "Reviewing Before Reading? An Empirical Investigation of Book-Consumption Patterns and Their Effects on Reviews and Sales," Information Systems Research, INFORMS, vol. 32(4), pages 1368-1389, December.
    13. Chong (Alex) Wang & Xiaoquan (Michael) Zhang & Il-Horn Hann, 2018. "Socially Nudged: A Quasi-Experimental Study of Friends’ Social Influence in Online Product Ratings," Information Systems Research, INFORMS, vol. 29(3), pages 641-655, September.
    14. Hui, Xiang & Klein, Tobias & Stahl, Konrad, 2022. "Learning from Online Ratings," CEPR Discussion Papers 17006, C.E.P.R. Discussion Papers.
    15. Kunpeng Zhang & Wendy Moe, 2021. "Measuring Brand Favorability Using Large-Scale Social Media Data," Information Systems Research, INFORMS, vol. 32(4), pages 1128-1139, December.
    16. Minnema, Alec & Bijmolt, Tammo H.A. & Gensler, Sonja & Wiesel, Thorsten, 2016. "To Keep or Not to Keep: Effects of Online Customer Reviews on Product Returns," Journal of Retailing, Elsevier, vol. 92(3), pages 253-267.
    17. Michael Luca & Georgios Zervas, 2013. "Fake It Till You Make It: Reputation, Competition, and Yelp Review Fraud," Harvard Business School Working Papers 14-006, Harvard Business School, revised May 2015.
    18. G. Tomas M. Hult & Forrest V. Morgeson III & Udit Sharma & Claes Fornell, 2022. "Customer satisfaction and international business: A multidisciplinary review and avenues for research," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 53(8), pages 1695-1733, October.
    19. Hülya Karaman, 2021. "Online Review Solicitations Reduce Extremity Bias in Online Review Distributions and Increase Their Representativeness," Management Science, INFORMS, vol. 67(7), pages 4420-4445, July.
    20. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Marketing Science, INFORMS, vol. 40(3), pages 481-507, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormksc:v:31:y:2012:i:3:p:372-386. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.