Truthfulness and Approximation with Value-Maximizing Bidders

Fadaei, Salman; Bichler, Martin

doi:10.1007/978-3-662-53354-3_19

Cited by 11 publications

(7 citation statements)

References 46 publications

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“…In contrast, this paper studies Vickrey's problem of efficient auction design in dominant strategies. My results are also related to recent literature on value maximizing bidders (see Fadaei and Bichler 2016). Value maximization is a limiting case of my model where a bidder gets arbitrarily small disutility from spending money up to their budget.…”

Section: Introductionsupporting

confidence: 73%

Efficient multiunit auctions for normal goods

Baisa

2020

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I study multiunit auction design when bidders have private values, multiunit demands, and non‐quasilinear preferences. Without quasilinearity, the Vickrey auction loses its desired incentive and efficiency properties. I give conditions under which we can design a mechanism that retains the Vickrey auction's desirable incentive and efficiency properties: (1) individual rationality, (2) dominant strategy incentive compatibility, and (3) Pareto efficiency. I show that there is a mechanism that retains the desired properties of the Vickrey auction if there are two bidders who have single‐dimensional types. I also present an impossibility theorem that shows that there is no mechanism that satisfies Vickrey's desired properties and weak budget balance when bidders have multidimensional types.

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Section: Introductionsupporting

confidence: 73%

Efficient multiunit auctions for normal goods

Baisa

2020

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“…In particular, the negative payment term in the utility function is replaced by a general cost, which is often a convex function of the payment. Independent of the above, the term of value-maximizer has been used in some other works but with quite di erent mathematical models Fadaei and Bichler [2016], Wilkens et al [2016Wilkens et al [ , 2017. The main distinction is that in these models, the target ROS constraints are imposed on a single auction rather than across a set of auctions, hence the bidders become insensitive to the marginal tradeo between values and payments, leading to di erent behavior patterns.…”

Section: Related Workmentioning

confidence: 99%

Robust Auction Design in the Auto-bidding World

Balseiro¹,

Deng²,

Mao³

et al. 2021

Preprint

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In classic auction theory, reserve prices are known to be e ective for improving revenue for the auctioneer against quasi-linear utility maximizing bidders. The introduction of reserve prices, however, usually do not help improve total welfare of the auctioneer and the bidders. In this paper, we focus on value maximizing bidders with return on spend constraints-a paradigm that has drawn considerable attention recently as more advertisers adopt auto-bidding algorithms in advertising platforms-and show that the introduction of reserve prices has a novel impact on the market. Namely, by choosing reserve prices appropriately the auctioneer can improve not only the total revenue but also the total welfare. Our results also demonstrate that reserve prices are robust to bidder types, i.e., reserve prices work well for di erent bidder types, such as value maximizers and utility maximizers, without using bidder type information. We generalize these results for a variety of auction mechanisms such as VCG, GSP, and rst-price auctions. Moreover, we show how to combine these results with additive boosts to improve the welfare of the outcomes of the auction further. Finally, we complement our theoretical observations with an empirical study con rming the e ectiveness of these ideas using data from online advertising auctions.

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“…because the money comes from a corporate budget) will buy as much as possible. This types of bidders are called value maximizers, and have recently drawn the attention of researchers in mechanism design [10,11].…”

Section: Modelmentioning

confidence: 99%

Generalized assignment problem: Truthful mechanism design without money

Fadaei

Bichler

2017

Operations Research Letters

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In this paper, we study a mechanism design problem for a strategic variant of the generalized assignment problem (GAP) in a both payment-free and priorfree environment. In GAP, a set of items has to be optimally assigned to a set of bins without exceeding the capacity of any singular bin. In the strategic variant of the problem we study, bins are held by strategic agents, and each agent may hide its compatibility with some items in order to obtain items of higher values. The compatibility between an agent and an item encodes the willingness of the agent to receive the item. Our goal is to maximize total value (sum of agents' values, or social welfare) while certifying no agent can benefit from hiding its compatibility with items. The model has applications in auctions with budgeted bidders.

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Truthfulness and Approximation with Value-Maximizing Bidders

Cited by 11 publications

References 46 publications

Efficient multiunit auctions for normal goods

Efficient multiunit auctions for normal goods

Robust Auction Design in the Auto-bidding World

Generalized assignment problem: Truthful mechanism design without money

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