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Platform or Wholesale? Different Implications for Retailers of Online Product

  • Young Kwark

    ()

    (Warrington College of Business Administration, University of Florida)

  • Jianqing Chen

    ()

    (Jindal School of Management, The University of Texas at Dallas)

  • Srinivasan Raghunathan

    ()

    (Jindal School of Management, The University of Texas at Dallas)

Registered author(s):

    Online retailing is dominated by a channel structure in which a retailer either buys products from competing manufacturers and resells to consumers (wholesale scheme) or lets manufacturers directly sell to consumers on its platform for a commission (platform scheme), and is characterized by easy access to product reviews to facilitate consumers' purchase decisions. We study how different types of information revealed by reviews affect the retailer under the wholesale scheme and platform scheme. We find that information provided by reviews on quality dimension homogenizes consumers' perceived utility differences between products and increases upstream competition, which benefits the retailer under the wholesale scheme but hurts the retailer under the platform scheme. Information provided by reviews on fit dimension heterogenizes consumers' estimated fits to products and softens upstream competition, which hurts the retailer under the wholesale scheme and benefits the retailer under the platform scheme. Together, we demonstrate that the quality information and fit information play very different roles in changing upstream competition, and whether the retailer benefits from reviews critically depends on its pricing scheme choice.

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    File URL: http://www.netinst.org/Kwark_Chen_13-14.pdf
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    Paper provided by NET Institute in its series Working Papers with number 13-14.

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    Length: 38 pages
    Date of creation: Sep 2013
    Date of revision:
    Handle: RePEc:net:wpaper:1314
    Contact details of provider: Web page: http://www.NETinst.org/

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    1. Dina Mayzlin, 2006. "Promotional Chat on the Internet," Marketing Science, INFORMS, vol. 25(2), pages 155-163, 03-04.
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    6. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    7. Baojun Jiang & Kinshuk Jerath & Kannan Srinivasan, 2011. "Firm Strategies in the "Mid Tail" of Platform-Based Retailing," Marketing Science, INFORMS, vol. 30(5), pages 757-775, September.
    8. Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
    9. 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.
    10. Lewis, Tracy R & Sappington, David E M, 1994. "Supplying Information to Facilitate Price Discrimination," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 35(2), pages 309-27, May.
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