IDEAS home Printed from https://ideas.repec.org/a/spr/infotm/v24y2023i2d10.1007_s10799-022-00361-z.html
   My bibliography  Save this article

Beyond the review information: an investigation of individual- and group-based presentation forms of review information

Author

Listed:
  • Wanshu Niu

    (Zhejiang University)

  • Liqiang Huang

    (Zhejiang University)

  • Xixi Li

    (University of Science and Technology Beijing)

  • Jie Zhang

    (Zhejiang University City College)

  • Mingliang Chen

    (Zhejiang University)

Abstract

Since most of today’s consumers make purchase decisions based on online reviews, managers and researchers have been keen to determine how best to present review information in an online shopping context to maximize their persuasive power. Most online reviews are presented post-by-post, whereby individual reviewers express their respective opinions but lack group dynamism. As a result, it is worth asking what would happen if individual reviews are presented as a group? Drawing on social presence theory and information adoption literature, we propose a research framework to investigate the influences of two alternative presentation forms of review information (i.e., individual-based vs. group-based) on multiple-facet consumer evaluation of reviews, as well as their adoption of review information. By conducting two experiments (Study 1: N = 319; Study 2: N = 101), we find that, when given the same review information, consumers presented with the grouped review information rated higher review quality and credibility, but lower understandability, than consumers who were presented with individual review information. In addition, review quality, credibility, and understandability mediated the influence of review presentation forms on the consumer adoption of review information. Both theoretical and practical implications are discussed.

Suggested Citation

  • Wanshu Niu & Liqiang Huang & Xixi Li & Jie Zhang & Mingliang Chen, 2023. "Beyond the review information: an investigation of individual- and group-based presentation forms of review information," Information Technology and Management, Springer, vol. 24(2), pages 159-176, June.
    • Handle: RePEc:spr:infotm:v:24:y:2023:i:2:d:10.1007_s10799-022-00361-z
    DOI: 10.1007/s10799-022-00361-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10799-022-00361-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10799-022-00361-z?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Ha, Sejin & Stoel, Leslie, 2009. "Consumer e-shopping acceptance: Antecedents in a technology acceptance model," Journal of Business Research, Elsevier, vol. 62(5), pages 565-571, May.
    2. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    3. Swait, Joffre & Adamowicz, Wiktor, 2001. "The Influence of Task Complexity on Consumer Choice: A Latent Class Model of Decision Strategy Switching," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 28(1), pages 135-148, June.
    4. Stephanie Watts Sussman & Wendy Schneier Siegal, 2003. "Informational Influence in Organizations: An Integrated Approach to Knowledge Adoption," Information Systems Research, INFORMS, vol. 14(1), pages 47-65, March.
    5. Richard L. Daft & Robert H. Lengel, 1986. "Organizational Information Requirements, Media Richness and Structural Design," Management Science, INFORMS, vol. 32(5), pages 554-571, May.
    6. Yubo Chen & Jinhong Xie, 2008. "Online Consumer Review: Word-of-Mouth as a New Element of Marketing Communication Mix," Management Science, INFORMS, vol. 54(3), pages 477-491, March.
    7. 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.
    8. 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.
    9. Prashant Malaviya & Brian Sternthal, 2009. "Parity Product Features Can Enhance or Dilute Brand Evaluation: The Influence of Goal Orientation and Presentation Format," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 36(1), pages 112-121, June.
    10. Filieri, Raffaele, 2015. "What makes online reviews helpful? A diagnosticity-adoption framework to explain informational and normative influences in e-WOM," Journal of Business Research, Elsevier, vol. 68(6), pages 1261-1270.
    11. 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.
    12. 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.
    13. Vicki McKinney & Kanghyun Yoon & Fatemeh “Mariam” Zahedi, 2002. "The Measurement of Web-Customer Satisfaction: An Expectation and Disconfirmation Approach," Information Systems Research, INFORMS, vol. 13(3), pages 296-315, September.
    14. Joseph K. Goodman & Selin A. Malkoc, 2012. "Choosing Here and Now versus There and Later: The Moderating Role of Psychological Distance on Assortment Size Preferences," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 39(4), pages 751-768.
    15. Xitong Li, 2018. "Impact of Average Rating on Social Media Endorsement: The Moderating Role of Rating Dispersion and Discount Threshold," Information Systems Research, INFORMS, vol. 29(3), pages 739-754, September.
    16. 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.
    17. Wei Chen & Bin Gu & Qiang Ye & Kevin Xiaoguo Zhu, 2019. "Measuring and Managing the Externality of Managerial Responses to Online Customer Reviews," Service Science, INFORMS, vol. 30(1), pages 81-96, March.
    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. Irena Antošová & Jana Stávková, 2023. "Changes in the intensity and impact of factors influencing consumer behaviour in the food market over time," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 69(9), pages 358-365.

    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. 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.
    2. 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.
    3. Lutz, Bernhard & Pröllochs, Nicolas & Neumann, Dirk, 2022. "Are longer reviews always more helpful? Disentangling the interplay between review length and line of argumentation," Journal of Business Research, Elsevier, vol. 144(C), pages 888-901.
    4. 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).
    5. Yani Wang & Jun Wang & Tang Yao, 2019. "What makes a helpful online review? A meta-analysis of review characteristics," Electronic Commerce Research, Springer, vol. 19(2), pages 257-284, June.
    6. Guha Majumder, Madhumita & Dutta Gupta, Sangita & Paul, Justin, 2022. "Perceived usefulness of online customer reviews: A review mining approach using machine learning & exploratory data analysis," Journal of Business Research, Elsevier, vol. 150(C), pages 147-164.
    7. Bin Guo & Shasha Zhou, 2017. "What makes population perception of review helpfulness: an information processing perspective," Electronic Commerce Research, Springer, vol. 17(4), pages 585-608, December.
    8. Yi Feng & Yunqiang Yin & Dujuan Wang & Lalitha Dhamotharan & Joshua Ignatius & Ajay Kumar, 2023. "Diabetic patient review helpfulness: unpacking online drug treatment reviews by text analytics and design science approach," Annals of Operations Research, Springer, vol. 328(1), pages 387-418, September.
    9. Srivastava, Vartika & Kalro, Arti D., 2019. "Enhancing the Helpfulness of Online Consumer Reviews: The Role of Latent (Content) Factors," Journal of Interactive Marketing, Elsevier, vol. 48(C), pages 33-50.
    10. Young Kwark & Gene Moo Lee & Paul A. Pavlou & Liangfei Qiu, 2021. "On the Spillover Effects of Online Product Reviews on Purchases: Evidence from Clickstream Data," Information Systems Research, INFORMS, vol. 32(3), pages 895-913, September.
    11. Liu, Yong & Gan, Wen-xue & Zhang, Qi, 2021. "Decision-making mechanism of online retailer based on additional online comments of consumers," Journal of Retailing and Consumer Services, Elsevier, vol. 59(C).
    12. Juan Feng & Xin Li & Xiaoquan (Michael) Zhang, 2019. "Online Product Reviews-Triggered Dynamic Pricing: Theory and Evidence," Information Systems Research, INFORMS, vol. 30(4), pages 1107-1123, December.
    13. Muhammad Rifki Shihab & Audry Pragita Putri, 2019. "Negative online reviews of popular products: understanding the effects of review proportion and quality on consumers’ attitude and intention to buy," Electronic Commerce Research, Springer, vol. 19(1), pages 159-187, March.
    14. 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.
    15. Dongpu Fu & Yili Hong & Kanliang Wang & Weiguo Fan, 2018. "Effects of membership tier on user content generation behaviors: evidence from online reviews," Electronic Commerce Research, Springer, vol. 18(3), pages 457-483, September.
    16. Kick, Markus, 2015. "Social Media Research: A Narrative Review," EconStor Preprints 182506, ZBW - Leibniz Information Centre for Economics.
    17. Zhen Li & Fangzhou Li & Jing Xiao & Zhi Yang, 2020. "Topic Features in Negative Customer Reviews: Evidence Based on Text Data Mining," The Review of Socionetwork Strategies, Springer, vol. 14(1), pages 19-40, April.
    18. Akbari, Morteza & Foroudi, Pantea & Zaman Fashami, Rahime & Mahavarpour, Nasrin & Khodayari, Maryam, 2022. "Let us talk about something: The evolution of e-WOM from the past to the future," Journal of Business Research, Elsevier, vol. 149(C), pages 663-689.
    19. 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.
    20. Yucheng Zhang & Zhiling Wang & Lin Xiao & Lijun Wang & Pei Huang, 2023. "Discovering the evolution of online reviews: A bibliometric review," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-22, December.

    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:spr:infotm:v:24:y:2023:i:2:d:10.1007_s10799-022-00361-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.