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Clash of reputation and status in online reviews

Author

Listed:
  • Hyejin Mun

    (Korea Advanced Institute of Science and Technology)

  • Chul Ho Lee

    (Korea Advanced Institute of Science and Technology)

  • Hyunju Jung

    (Korea Advanced Institute of Science and Technology)

  • Ceran Yasin

    (Korea Advanced Institute of Science and Technology
    San Jose State University)

Abstract

This study extends the heterogeneous effectiveness of market signals by examining when textual sentiments have the most influence on purchasing decisions. Specifically, we argue that reputation and status, two distinct theoretical constructs, which are difficult to disentangle in practice, may influence the effectiveness of textual sentiments on customers’ decision making process in opposite directions. Reputation refers to the quality trajectory for a product whereas status sets a societal expectation from a product based on the social standing of that product among its peers. In this study, we examine reputation and status as contingencies that affect how electronic word of mouth (e-WoM) is perceived by customers in the context of review platform. To demonstrate the impact of textual sentiments and the moderation effects of reputation and status, we used an online platform to crawl review and reservation data at the same time of everyday over a period of 100 days on 310 hotels located in New York City. We found that customers are more sensitive to the sentiment of textual reviews on hotels of high status but less receptive when reviews are on hotels of high reputation. Our robustness tests and two identification strategies are all consistent with these findings. This research offers a strategic guideline to businesses and platforms in terms of how much they should rely on e-WoM, contingent upon their reputation and status.

Suggested Citation

  • Hyejin Mun & Chul Ho Lee & Hyunju Jung & Ceran Yasin, 2023. "Clash of reputation and status in online reviews," Information Technology and Management, Springer, vol. 24(1), pages 55-77, March.
  • Handle: RePEc:spr:infotm:v:24:y:2023:i:1:d:10.1007_s10799-022-00374-8
    DOI: 10.1007/s10799-022-00374-8
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    References listed on IDEAS

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    1. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    2. David Godes & Dina Mayzlin, 2009. "Firm-Created Word-of-Mouth Communication: Evidence from a Field Test," Marketing Science, INFORMS, vol. 28(4), pages 721-739, 07-08.
    3. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2011. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Management Science, INFORMS, vol. 57(8), pages 1485-1509, August.
    4. Jonah Berger & Raghuram Iyengar, 2013. "Communication Channels and Word of Mouth: How the Medium Shapes the Message," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 40(3), pages 567-579.
    5. 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.
    6. Hollenbeck, Brett, 2018. "Online Reputation Mechanisms and the Decreasing Value of Chain Affliation," MPRA Paper 91573, University Library of Munich, Germany.
    7. Karen D. W. Patterson & David Eduardo Cavazos & Marvin Washington, 2014. "It Does Matter How You Get to the Top: Differentiating Status from Reputation," Administrative Sciences, MDPI, vol. 4(2), pages 1-14, April.
    8. Matanda, Tandadzo & Ewing, Michael T., 2012. "The process of global brand strategy development and regional implementation," International Journal of Research in Marketing, Elsevier, vol. 29(1), pages 5-12.
    9. Paul A. Pavlou & Angelika Dimoka, 2006. "The Nature and Role of Feedback Text Comments in Online Marketplaces: Implications for Trust Building, Price Premiums, and Seller Differentiation," Information Systems Research, INFORMS, vol. 17(4), pages 392-414, December.
    10. Yasin Ceran & Harpreet Singh & Vijay Mookerjee, 2016. "Knowing What Your Customer Wants: Improving Inventory Allocation Decisions in Online Movie Rental Systems," Production and Operations Management, Production and Operations Management Society, vol. 25(10), pages 1673-1688, October.
    11. Andrew E. Wilson & Michael D. Giebelhausen & Michael K. Brady, 2017. "Negative word of mouth can be a positive for consumers connected to the brand," Journal of the Academy of Marketing Science, Springer, vol. 45(4), pages 534-547, July.
    12. David Godes & Dina Mayzlin, 2004. "Using Online Conversations to Study Word-of-Mouth Communication," Marketing Science, INFORMS, vol. 23(4), pages 545-560, June.
    13. Highhouse, Scott & Thornbury, Erin E. & Little, Ian S., 2007. "Social-identity functions of attraction to organizations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 103(1), pages 134-146, May.
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