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The Use and Value of Social Information in Selective Selling of Exclusive Products

Author

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  • Ruslan Momot

    (HEC Paris, 78351 Jouy-en-Josas, France)

  • Elena Belavina

    (Cornell University, Ithaca, New York 14853)

  • Karan Girotra

    (Cornell University, Ithaca, New York 14853)

Abstract

We consider the use and value of social-network information in selectively selling goods and services whose value derives from exclusive ownership among network connections or friends. Our model accommodates customers who are heterogeneous in their number of friends (degree) and their proclivity for social comparisons (conspicuity). Firms with information on either (or both) of these characteristics can use it to make the product selectively available and to personalize prices. We find that firms’ preferred customers are low degree and high conspicuity , with the conspicuity threshold nondecreasing in degree. Interestingly, although both degree and conspicuity levels are relevant to curating the desired customer base, we find that firms do not need conspicuity information to do so; its absence can be substituted by incentivizing customers to self-select. There is no such recourse for the absence of degree information. As a result, degree information is typically more valuable than conspicuity information. Our analysis suggests that there are two canonical categories of social information—less valuable “consonant” information on characteristics where firm and customer preferences are aligned and more valuable “competing” information where preferences are misaligned. Customers can be incentivized to act in a way that their actions are a perfect substitute for consonant information, making it less valuable.

Suggested Citation

  • Ruslan Momot & Elena Belavina & Karan Girotra, 2020. "The Use and Value of Social Information in Selective Selling of Exclusive Products," Management Science, INFORMS, vol. 66(6), pages 2610-2627, June.
  • Handle: RePEc:inm:ormnsc:v:66:y:2020:i:6:p:2610-2627
    DOI: 10.1287/mnsc.2019.3310
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    References listed on IDEAS

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    Cited by:

    1. Zhang, Mengyao & Gou, Qinglong & Yu, Lili & Zhang, Juzhi, 2022. "Pricing decisions for a social comparison product supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    2. Itay P. Fainmesser & Andrea Galeotti & Ruslan Momot, 2023. "Digital Privacy," Management Science, INFORMS, vol. 69(6), pages 3157-3173, June.
    3. Yunke Mai & Bin Hu, 2023. "Optimizing Free-to-Play Multiplayer Games with Premium Subscription," Management Science, INFORMS, vol. 69(6), pages 3437-3456, June.
    4. Li, Guo & Li, Xiaochuan & Zheng, Hong, 2023. "Discount preannouncement in the digital supply chain era," International Journal of Production Economics, Elsevier, vol. 258(C).
    5. Jiali Huang & Ankur Mani & Zizhuo Wang, 2022. "The Value of Price Discrimination in Large Social Networks," Management Science, INFORMS, vol. 68(6), pages 4454-4477, June.

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