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Maximizing revenue in the presence of intermediaries

Author

Listed:
  • Gagan Aggarwal
  • Kshipra Bhawalkar
  • Guru Guruganesh
  • Andres Perlroth

Abstract

We study the mechanism design problem of selling $k$ items to unit-demand buyers with private valuations for the items. A buyer either participates directly in the auction or is represented by an intermediary, who represents a subset of buyers. Our goal is to design robust mechanisms that are independent of the demand structure (i.e. how the buyers are partitioned across intermediaries), and perform well under a wide variety of possible contracts between intermediaries and buyers. We first study the case of $k$ identical items where each buyer draws its private valuation for an item i.i.d. from a known $\lambda$-regular distribution. We construct a robust mechanism that, independent of the demand structure and under certain conditions on the contracts between intermediaries and buyers, obtains a constant factor of the revenue that the mechanism designer could obtain had she known the buyers' valuations. In other words, our mechanism's expected revenue achieves a constant factor of the optimal welfare, regardless of the demand structure. Our mechanism is a simple posted-price mechanism that sets a take-it-or-leave-it per-item price that depends on $k$ and the total number of buyers, but does not depend on the demand structure or the downstream contracts. Next we generalize our result to the case when the items are not identical. We assume that the item valuations are separable. For this case, we design a mechanism that obtains at least a constant fraction of the optimal welfare, by using a menu of posted prices. This mechanism is also independent of the demand structure, but makes a relatively stronger assumption on the contracts between intermediaries and buyers, namely that each intermediary prefers outcomes with a higher sum of utilities of the subset of buyers represented by it.

Suggested Citation

  • Gagan Aggarwal & Kshipra Bhawalkar & Guru Guruganesh & Andres Perlroth, 2021. "Maximizing revenue in the presence of intermediaries," Papers 2111.10472, arXiv.org.
  • Handle: RePEc:arx:papers:2111.10472
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    References listed on IDEAS

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    1. Sergiu Hart & Noam Nisan, 2013. "The Menu-Size Complexity of Auctions," Discussion Paper Series dp637, The Federmann Center for the Study of Rationality, the Hebrew University, Jerusalem.
    2. Paul Milgrom & Ilya Segal, 2002. "Envelope Theorems for Arbitrary Choice Sets," Econometrica, Econometric Society, vol. 70(2), pages 583-601, March.
    3. Hart, Sergiu & Nisan, Noam, 2017. "Approximate revenue maximization with multiple items," Journal of Economic Theory, Elsevier, vol. 172(C), pages 313-347.
    4. Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2016. "Selling to Intermediaries: Optimal Auction Design in a Common Value Model," Cowles Foundation Discussion Papers 2064R, Cowles Foundation for Research in Economics, Yale University, revised Jul 2017.
    5. Dirk Bergemann & Benjamin Brooks & Stephen Morris, 2016. "Optimal Auction Design in a Common Value Model," Working Papers 085_2016, Princeton University, Department of Economics, Econometric Research Program..
    6. Che, Yeon-Koo & Condorelli, Daniele & Kim, Jinwoo, 2018. "Weak cartels and collusion-proof auctions," Journal of Economic Theory, Elsevier, vol. 178(C), pages 398-435.
    7. Che, Yeon-Koo & Kim, Jinwoo, 2009. "Optimal collusion-proof auctions," Journal of Economic Theory, Elsevier, vol. 144(2), pages 565-603, March.
    8. Yeon-Koo Che & Jinwoo Kim, 2006. "Robustly Collusion-Proof Implementation," Econometrica, Econometric Society, vol. 74(4), pages 1063-1107, July.
    9. Manelli, Alejandro M. & Vincent, Daniel R., 2006. "Bundling as an optimal selling mechanism for a multiple-good monopolist," Journal of Economic Theory, Elsevier, vol. 127(1), pages 1-35, March.
    10. R. Preston McAfee & John McMillan & Michael D. Whinston, 1989. "Multiproduct Monopoly, Commodity Bundling, and Correlation of Values," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 104(2), pages 371-383.
    11. Schweizer, Nikolaus & Szech, Nora, 2019. "Performance bounds for optimal sales mechanisms beyond the monotone hazard rate condition," Journal of Mathematical Economics, Elsevier, vol. 82(C), pages 202-213.
    12. Shengwu Li, 2017. "Obviously Strategy-Proof Mechanisms," American Economic Review, American Economic Association, vol. 107(11), pages 3257-3287, November.
    13. Gabriel Carroll, 2017. "Robustness and Separation in Multidimensional Screening," Econometrica, Econometric Society, vol. 85, pages 453-488, March.
    14. Shuchi Chawla & Jason Hartline & David Malec & Balasubramanian Sivan, 2010. "Sequential Posted Pricing and Multi-parameter Mechanism Design," Discussion Papers 1486, Northwestern University, Center for Mathematical Studies in Economics and Management Science.
    15. Patrick Hummel & R. Preston McAfee & Sergei Vassilvitskii, 2016. "Incentivizing advertiser networks to submit multiple bids," International Journal of Game Theory, Springer;Game Theory Society, vol. 45(4), pages 1031-1052, November.
    16. Roger B. Myerson, 1981. "Optimal Auction Design," Mathematics of Operations Research, INFORMS, vol. 6(1), pages 58-73, February.
    17. ,, 2008. "Auction design in the presence of collusion," Theoretical Economics, Econometric Society, vol. 3(3), September.
    18. Thanassoulis, John, 2004. "Haggling over substitutes," Journal of Economic Theory, Elsevier, vol. 117(2), pages 217-245, August.
    19. Santiago R. Balseiro & Ozan Candogan, 2017. "Optimal Contracts for Intermediaries in Online Advertising," Operations Research, INFORMS, vol. 65(4), pages 878-896, August.
    20. Hana Choi & Carl F. Mela & Santiago R. Balseiro & Adam Leary, 2020. "Online Display Advertising Markets: A Literature Review and Future Directions," Information Systems Research, INFORMS, vol. 31(2), pages 556-575, June.
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