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Optimal Commissions and Subscriptions in Networked Markets

Author

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  • Birge, John R.

    (Booth School of Business, University of Chicago)

  • Candogan, Ozan

    (Booth School of Business, University of Chicago)

  • Chen, Hongfan

    (Booth School of Business, University of Chicago)

  • Saban, Daniela

    (Graduate School of Business, Stanford University)

Abstract

Two salient features of most online platforms are that they do not dictate the transaction prices, and use commissions/subscriptions for extracting revenues. We consider a platform that charges commission rates and subscription fees to sellers and buyers for facilitating transactions, but does not directly control the transaction prices, which are determined by the traders. Buyers and sellers are divided into types, and we represent the compatibility between different types using a bipartite network. Traders are heterogeneous in terms of their valuations, and different types have possibly different value distributions. The platform chooses commissions-subscriptions to maximize its revenues. We provide a convex optimization formulation to calculate the revenue-maximizing commissions/subscriptions, and establish that, typically, different types should be charged different commissions/subscriptions depending on their network positions. We establish lower and upper bounds on the platform’s revenues in terms of the supply-demand imbalance across the network. Motivated by simpler schemes used in practice, we show that the revenue loss can be unbounded when all traders on the same side are charged the same commissions/subscriptions, and bound the revenue loss in terms of the supply-demand imbalance across the network. Charging only buyers or only sellers leads to a (bounded) revenue loss, even when different types on the same side can be charged differently. Under mild assumptions, we establish that a revenue-maximizing platform achieves at least 2/3 of the maximum achievable social welfare. Our results highlight the suboptimality of commonly used payment schemes, and showcase the importance of accounting for the compatibility between different user types.

Suggested Citation

  • Birge, John R. & Candogan, Ozan & Chen, Hongfan & Saban, Daniela, 2018. "Optimal Commissions and Subscriptions in Networked Markets," Research Papers 3742, Stanford University, Graduate School of Business.
  • Handle: RePEc:ecl:stabus:3742
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    Cited by:

    1. Saeed Alaei & Ali Makhdoumi & Azarakhsh Malekian & Saša Pekeč, 2022. "Revenue-Sharing Allocation Strategies for Two-Sided Media Platforms: Pro-Rata vs. User-Centric," Management Science, INFORMS, vol. 68(12), pages 8699-8721, December.
    2. Zhu, Haoruo & Ni, Yaodong & Yang, Meng & Song, Qinyu, 2023. "Blessing or curse? Impact of incomplete information in a networked cournot competition," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    3. Xu, Xiaoping & Chen, Xinyang & Choi, Tsan-Ming & Cheng, T.C.E., 2024. "Platform financing versus bank financing: “When to choose which” for green production systems," European Journal of Operational Research, Elsevier, vol. 317(2), pages 515-532.
    4. Tiffany Ding & Dominique Perrault-Joncas & Orit Ronen & Michael I. Jordan & Dirk Bergemann & Dean Foster & Omer Gottesman, 2025. "Marketplace Operators Can Induce Competitive Pricing," Papers 2503.06582, arXiv.org, revised Oct 2025.
    5. Charlson, G., 2020. "Searching for Results: Optimal Platform Design in a Network Setting," Cambridge Working Papers in Economics 20118, Faculty of Economics, University of Cambridge.
    6. Zhou, Sijie & Shi, Ye & Yu, Yugang & Liu, Jie, 2025. "Design of platform-labeling standards and competition strategy for retail platforms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 196(C).

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