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Platform or Wholesale? Different Implications for Retailers of Online Product

Author

Listed:
  • 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)

Abstract

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.

Suggested Citation

  • Young Kwark & Jianqing Chen & Srinivasan Raghunathan, 2013. "Platform or Wholesale? Different Implications for Retailers of Online Product," Working Papers 13-14, NET Institute.
    • Handle: RePEc:net:wpaper:1314
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    References listed on IDEAS

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    1. Monic Sun, 2011. "Disclosing Multiple Product Attributes," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 20(1), pages 195-224, March.
    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. Duan, Wenjing & Gu, Bin & Whinston, Andrew B., 2008. "The dynamics of online word-of-mouth and product sales—An empirical investigation of the movie industry," Journal of Retailing, Elsevier, vol. 84(2), pages 233-242.
    4. Nikolay Archak & Anindya Ghose & Panagiotis G. Ipeirotis, 2007. "Deriving the Pricing Power of Product Features by Mining Consumer Reviews," Working Papers 07-36, NET Institute.
    5. S. Chan Choi, 1991. "Price Competition in a Channel Structure with a Common Retailer," Marketing Science, INFORMS, vol. 10(4), pages 271-296.
    6. 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 309-327, May.
    7. 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.
    8. 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.
    9. 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.
    10. Justin P. Johnson & David P. Myatt, 2006. "On the Simple Economics of Advertising, Marketing, and Product Design," American Economic Review, American Economic Association, vol. 96(3), pages 756-784, June.
    11. Dina Mayzlin, 2006. "Promotional Chat on the Internet," Marketing Science, INFORMS, vol. 25(2), pages 155-163, 03-04.
    12. 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.
    13. 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.
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    More about this item

    Keywords

    Online Product Reviews; Pricing Scheme; Competition;
    All these keywords.

    JEL classification:

    • L11 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Production, Pricing, and Market Structure; Size Distribution of Firms
    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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