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Forging Self-Funded Marketplaces among Strategic Agents
Preprint

Forging Self-Funded Marketplaces among Strategic Agents

Yuan Deng, Vasilis Gkatzelis, Xizhi Tan, Grigoris Velegkas and Song Zuo
arXiv (Cornell University)
14 Aug 2026
url
https://arxiv.org/pdf/2608.14548View
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Abstract

Computer Science - Computer Science and Game Theory
We introduce the problem of designing mechanisms that incentivize strategic agents to form self-funded marketplaces. In our model, if agentiexerts effortxᵢ∈ [0,1] , they incur a cost ofxᵢ⋅ cᵢ(wherecᵢis unknown to the mechanism designer) and they generate revenuexᵢ⋅ rᵢ ; crucially,cᵢcan be greater or smaller thanrᵢ . Each effort profile𝐱yields valuev(𝐱)and the objective is to choose an effort vector that maximizes the value while ensuring that every agentireceives a paymentpᵢ≥ xᵢ⋅ cᵢand that𝐱is budget-balanced, i.e.,∑ᵢ pᵢ ≤ ∑ᵢ xᵢ⋅ rᵢ . This problem generalizes the well-studied budget-feasible mechanism design problem, where the requirement is that∑ᵢ pᵢ ≤ Bfor some predetermined budgetB . To evaluate the performance of such mechanisms, we first consider the first-best benchmark (the optimal value achievable in the absence of any private information) and show that no truthful auction can achieve a bounded approximation of this benchmark. Also, even in restricted settings, no auction can achieve better than a logarithmic approximation. We complement these results by proposing a class of sequential auctions whose subgame perfect equilibria guarantee a logarithmic approximation of this benchmark. We then introduce an alternative benchmark, the maximin share (MMS), that better captures the thickness of the market and we provide an auction whose subgame perfect equilibria achieve a constant approximation of this benchmark.

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