From Welfare to Utility: Generalized Objectives in Budget-Feasible Procurement

2026-06-30

AI Summary

This work addresses budget-constrained procurement mechanism design by moving beyond the conventional focus on maximizing the buyer’s value alone, instead targeting the buyer’s utility, social welfare, and more general objectives under both prior-free and Bayesian settings. The key contribution is the first mechanism that achieves near-optimal buyer utility while satisfying ex-post budget feasibility, which is further extended to accommodate generalized objective functions. By integrating techniques from mechanism design, Bayesian optimization, worst-case analysis, and budget constraint transformation, the proposed approach yields a constant-factor approximation for social welfare and achieves near-optimal performance for utility objectives under both expected and ex-post budget constraints.

Abstract

We study mechanism design for the budget-feasible procurement problem, a natural problem that arises when a buyer wants to procure goods or services from multiple strategic sellers who each have a cost to provide that service, the buyer has a value for each service procured, but is constrained by a budget. In contrast to prior work, which has focused on buyer value maximization for this problem, we solve for optimal and approximately-optimal mechanisms for the objectives of buyer utility (value of procured services minus payments), welfare (value minus production costs), and generalizations of the two. For welfare, we design a simple mechanism that obtains a constant-factor approximation for the prior-free (worst-case) setting. As prior-free mechanisms fail to provide any guarantee for utility, even for a single seller, we consider Bayesian settings, where the buyer has distributional knowledge over sellers' costs. We first provide a utility-optimal mechanism that satisfies the buyer's budget constraint in expectation, then we show how to modify the mechanism to satisfy the budget constraint ex-post, for every realization of seller costs, while still obtaining near-optimal utility guarantees. Finally, we generalize our mechanisms to other objectives.

Problem

• budget-feasible procurement
• mechanism design
• buyer utility
• welfare
• Bayesian settings

Innovation

• budget-feasible procurement
• mechanism design
• buyer utility
• welfare maximization
• Bayesian mechanism