• Media type: E-Book
  • Title: Optimal Mechanisms for a Value Maximizer : The Futility of Screening Targets
  • Contributor: Balseiro, Santiago [VerfasserIn]; Deng, Yuan [VerfasserIn]; Mao, Jieming [VerfasserIn]; Mirrokni, Vahab [VerfasserIn]; Zuo, Song [VerfasserIn]
  • imprint: [S.l.]: SSRN, 2023
  • Extent: 1 Online-Ressource (31 p)
  • Language: English
  • DOI: 10.2139/ssrn.4351927
  • Identifier:
  • Keywords: internet advertising ; autobidding ; mechanism design ; value maximization ; return-on-spend constraints ; two-part tariff
  • Origination:
  • Footnote: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 1, 2023 erstellt
  • Description: Motivated by the increased adoption of autobidding algorithms in internet advertising markets, we study the design of optimal mechanisms for selling items to a value-maximizing buyer with a return-on-spend constraint. The buyer's values and target ratio in the return-on-spend constraint are private. We restrict attention to deterministic sequential screening mechanisms that can be implemented as a menu of two-part tariffs. The main result of this paper is to provide a characterization of an optimal mechanism. Surprisingly, we show that the optimal mechanism does not require target screening, i.e., offering a single two-part tariff is optimal for the seller. The optimal mechanism is a subsidized two-part tariff that provides a lump-sum subsidy to the buyer to encourage participation and then charges a fixed unit price for each item sold. The seller's problem is a challenging non-linear mechanism design problem, and a key technical contribution of our work is to provide a novel approach to analyzing non-linear pricing contracts for constrained buyers. Our results have valuable implications for advertising platforms seeking to personalize pricing decisions based on advertisers' characteristics
  • Access State: Open Access