Mechanism Design for Value Maximizers
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Abstract (arXiv)
In many settings, money is a tool of exchange with minimal inherent utility --- agents will spend it in a way that maximizes the value of goods received subject to reasonable constraints, giving only second-order consideration to the trade-off between value and price. While this perspective is commonly captured in consumer choice theory, market equilibrium theory, and other fields, it is markedly absent from the mechanism design literature --- agents strategizing in a mechanism with money are almost always assumed to incorporate money as an objective through quasilinear valuations. We study a simple model of value maximizers that captures online advertisers and other agents who may view money solely as a constraint, and study general questions of mechanism design for such agents. We show that the feasible and optimal points faced by a mechanism designer change dramatically from the quasilinear realm and lay a foundation for a broader study of value maximization in mechanism design. Along the way, we offer new insight into the generalized second price (GSP) auction commonly used in Internet advertising. Through the lens of value maximization, GSP metamorphosizes into a truthful auction, sound in its principles and elegant in its simplicity.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). First posted on arXiv 15 Jul 2016.
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Citing papers per year: 2022: 1; 2023: 1; 2024: 0; 2025: 0; 2026: 1.
3 papers.
- 2022ROI-Constrained Bidding via Curriculum-Guided Bayesian Reinforcement Learningcited by 12
- 2023Adversarial Constrained Bidding via Minimax Regret Optimization with Causality-Aware Reinforcement Learningcited by 7
- 2026Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?cited by 0
- 2026Model Monotonicity in Autobidding Auctions: When Do Better Predictions Lead to Better Outcomes?29 May 2026
- 2023Adversarial Constrained Bidding via Minimax Regret Optimization with Causality-Aware Reinforcement Learning12 Jun 2023
- 2022ROI-Constrained Bidding via Curriculum-Guided Bayesian Reinforcement Learning10 Jun 2022