IDEAS home Printed from https://ideas.repec.org/a/eee/joinma/v39y2017icp1-14.html

The Presentation Format of Review Score Information Influences Consumer Preferences Through the Attribution of Outlier Reviews

Author

Listed:
  • Camilleri, Adrian R.

Abstract

Review score information can be presented in different formats. In three online experiments, we examined consumers' behavior in the context of review scores presented in a disaggregated format (individual review scores observed sequentially and individually), an aggregated format (review scores summarized into a frequency distribution chart), or both together. Participants tended to attribute outlier review scores to reviewer rather than product reasons. This tendency was more prevalent when reviews were presented in disaggregated format. Moreover, reviews attributed to reviewer reasons tended to be perceived with low credibility. When presented with a choice between two products with equal average review scores but different variances, participants chose as if outlier review scores were discounted when scores were presented in the disaggregated format. This tendency emerged even when disaggregated and aggregated formats were presented together. The number of review scores moderated the effect of format on choice. We argue that disaggregated information allows consumers to better track the number of outliers and, when the number of outliers is small, prompts them to attribute these outliers to reviewer reasons, and subsequently discount them.

Suggested Citation

  • Camilleri, Adrian R., 2017. "The Presentation Format of Review Score Information Influences Consumer Preferences Through the Attribution of Outlier Reviews," Journal of Interactive Marketing, Elsevier, vol. 39(C), pages 1-14.
  • Handle: RePEc:eee:joinma:v:39:y:2017:i:c:p:1-14
    DOI: 10.1016/j.intmar.2017.02.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1094996817300166
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.intmar.2017.02.002?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
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Bart de Langhe & Philip M. Fernbach & Donald R. Lichtenstein, 2016. "Navigating by the Stars: Investigating the Actual and Perceived Validity of Online User Ratings," Journal of Consumer Research, Oxford University Press, vol. 42(6), pages 817-833.
    2. David P. Mackinnon & James H. Dwyer, 1993. "Estimating Mediated Effects in Prevention Studies," Evaluation Review, , vol. 17(2), pages 144-158, April.
    3. Alba, Joseph W & Marmorstein, Howard, 1987. "The Effects of Frequency Knowledge on Consumer Decision Making," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 14(1), pages 14-25, June.
    4. Gerd Gigerenzer & Reinhard Selten (ed.), 2002. "Bounded Rationality: The Adaptive Toolbox," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262571641, December.
    5. Purnawirawan, Nathalia & De Pelsmacker, Patrick & Dens, Nathalie, 2012. "Balance and Sequence in Online Reviews: How Perceived Usefulness Affects Attitudes and Intentions," Journal of Interactive Marketing, Elsevier, vol. 26(4), pages 244-255.
    6. C. Nadine Wathen & Jacquelyn Burkell, 2002. "Believe it or not: Factors influencing credibility on the Web," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 53(2), pages 134-144.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. K. Pooja & Pallavi Upadhyaya, 2024. "What makes an online review credible? A systematic review of the literature and future research directions," Management Review Quarterly, Springer, vol. 74(2), pages 627-659, June.
    2. Ahani, Ali & Nilashi, Mehrbakhsh & Yadegaridehkordi, Elaheh & Sanzogni, Louis & Tarik, A. Rashid & Knox, Kathy & Samad, Sarminah & Ibrahim, Othman, 2019. "Revealing customers’ satisfaction and preferences through online review analysis: The case of Canary Islands hotels," Journal of Retailing and Consumer Services, Elsevier, vol. 51(C), pages 331-343.
    3. Wallbach, Sören, 2020. "Assimilation and Diffusion of Multi-Sided Platforms in Dynamic B2B Networks: Inhibiting Factors and Their Consequences," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 123277, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Dirk van Straaten & Vitalik Melnikov & Eyke Hüllermeier & Behnud Mir Djawadi & René Fahr, 2021. "Accounting for Heuristics in Reputation Systems: An Interdisciplinary Approach on Aggregation Processes," Working Papers Dissertations 72, Paderborn University, Faculty of Business Administration and Economics.
    5. Janina Seutter & Kristin Kutzner & Maren Stadtländer & Dennis Kundisch & Ralf Knackstedt, 2023. "“Sorry, too much information”—Designing online review systems that support information search and processing," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-19, December.
    6. Moon-Yong Kim & Sangkil Moon & Mason Jenkins, 2026. "Consumer-Perceived Differences between Best- and Second-Best-Rated Product Reviews," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 13(1), pages 1-29, December.
    7. Dominik Gutt & Jürgen Neumann & Steffen Zimmermann & Dennis Kundisch & Jianqing Chen, 2018. "Design of Review Systems - A Strategic Instrument to shape Online Review Behavior and Economic Outcomes," Working Papers Dissertations 42, Paderborn University, Faculty of Business Administration and Economics.
    8. Liu, Fu & Wei, Haiying & Wang, Xingyuan & Zhu, Zhenzhong & Chen, Haipeng Allan, 2023. "The influence of online review dispersion on consumers’ purchase intention: The moderating role of dialectical thinking," Journal of Business Research, Elsevier, vol. 165(C).
    9. Camilleri, Adrian R. & Newell, Ben R., 2019. "Better calibration when predicting from experience (rather than description)," Organizational Behavior and Human Decision Processes, Elsevier, vol. 150(C), pages 62-82.

    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. Fourkan, Md & Darani, Milad Mohammadi & Wiggins, Jennifer, 2026. "Beyond credibility: expressive authenticity judgments of online reviews," Journal of Business Research, Elsevier, vol. 206(C).
    2. Dezhi Yin & Triparna de Vreede & Logan M. Steele & Gert-Jan de Vreede, 2023. "Decide Now or Later: Making Sense of Incoherence Across Online Reviews," Information Systems Research, INFORMS, vol. 34(3), pages 1211-1227, September.
    3. Zheng, Lili, 2021. "The classification of online consumer reviews: A systematic literature review and integrative framework," Journal of Business Research, Elsevier, vol. 135(C), pages 226-251.
    4. Rosillo-Díaz, Elena & Muñoz-Rosas, Juan Francisco & Blanco-Encomienda, Francisco Javier, 2024. "Impact of heuristic–systematic cues on the purchase intention of the electronic commerce consumer through the perception of product quality," Journal of Retailing and Consumer Services, Elsevier, vol. 81(C).
    5. Halloran, Timothy J. & Lutz, Richard J., 2021. "Let's Give Them Something to Talk About: Which Social Media Engagements Predict Purchase Frequency?," Journal of Interactive Marketing, Elsevier, vol. 56(C), pages 83-95.
    6. Aspasia Tsaoussi & Eleni Zervogianni, 2010. "Judges as satisficers: a law and economics perspective on judicial liability," European Journal of Law and Economics, Springer, vol. 29(3), pages 333-357, June.
    7. Nicolas Marciales Parra, 2013. "A mathematical model for consumers based on aspiration adaptation theory and bounded rationality," Review of Applied Socio-Economic Research, Pro Global Science Association, vol. 5(1), pages 136-143, June.
    8. Pengkun Wu & Eric W. T. Ngai & Yuanyuan Wu, 2023. "Impact of praise cashback strategy: Implications for consumers and e‐businesses," Production and Operations Management, Production and Operations Management Society, vol. 32(9), pages 2825-2845, September.
    9. Binder, Carola C., 2017. "Measuring uncertainty based on rounding: New method and application to inflation expectations," Journal of Monetary Economics, Elsevier, vol. 90(C), pages 1-12.
    10. Kaushik, Kapil & Mishra, Rajhans & Rana, Nripendra P. & Dwivedi, Yogesh K., 2018. "Exploring reviews and review sequences on e-commerce platform: A study of helpful reviews on Amazon.in," Journal of Retailing and Consumer Services, Elsevier, vol. 45(C), pages 21-32.
    11. Mindy K. Shoss & Dustin K. Jundt & Allison Kobler & Clair Reynolds, 2016. "Doing Bad to Feel Better? An Investigation of Within- and Between-Person Perceptions of Counterproductive Work Behavior as a Coping Tactic," Journal of Business Ethics, Springer, vol. 137(3), pages 571-587, September.
    12. Sanaji & Tias Andarini Indarwati & Ika Diyah Candra, 2021. "The influence of perceived ease of use, perceive usefulness, and trust on customer's intention to use "Bebas Bayar" mobile payment application in Indonesia," Technium Social Sciences Journal, Technium Science, vol. 20(1), pages 726-738, June.
    13. Sungsik Park & Woochoel Shin & Jinhong Xie, 2021. "The Fateful First Consumer Review," Marketing Science, INFORMS, vol. 40(3), pages 481-507, May.
    14. Moradi, Masoud & Dass, Mayukh & Kumar, Piyush, 2023. "Differential effects of analytical versus emotional rhetorical style on review helpfulness," Journal of Business Research, Elsevier, vol. 154(C).
    15. Giovanni Dosi & Marcelo C. Pereira & Maria Enrica Virgillito, 2017. "The footprint of evolutionary processes of learning and selection upon the statistical properties of industrial dynamics," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(2), pages 187-210.
    16. Glückstad, Fumiko Kano & Schmidt, Mikkel N. & Mørup, Morten, 2020. "Testing a model of destination image formation: Application of Bayesian relational modelling and fsQCA," Journal of Business Research, Elsevier, vol. 120(C), pages 351-363.
    17. Carlos Lamela-Orcasitas & Jesús García-Madariaga, 2023. "How to really quantify the economic value of customer information in corporate databases," Humanities and Social Sciences Communications, Palgrave Macmillan, vol. 10(1), pages 1-13, December.
    18. Lakon, Cynthia M. & Ennett, Susan T. & Norton, Edward C., 2006. "Mechanisms through which drug, sex partner, and friendship network characteristics relate to risky needle use among high risk youth and young adults," Social Science & Medicine, Elsevier, vol. 63(9), pages 2489-2499, November.
    19. Dena Yadin & Inbal Yahav & Lior Zalmanson & Nira Munichor, 2024. "Resolving the Ethical Tension Between Creating a Civil Environment and Facilitating Free Expression Online: Comment Reordering as an Alternative to Comment Moderation," Journal of Business Ethics, Springer, vol. 192(2), pages 261-283, June.
    20. Chakravarty, Anindita & Liu, Yong & Mazumdar, Tridib, 2010. "The Differential Effects of Online Word-of-Mouth and Critics' Reviews on Pre-release Movie Evaluation," Journal of Interactive Marketing, Elsevier, vol. 24(3), pages 185-197.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:eee:joinma:v:39:y:2017:i:c:p:1-14. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/journal-of-interactive-marketing/ .

    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.