Sponsored Search Auction Design Beyond Single Utility Maximization

2024-06-10

arXiv.org

AI Summary

This paper addresses auction design in hybrid auto-bidding environments comprising both utility-maximizing and value-maximizing bidders, aiming to simultaneously maximize social welfare and ensure incentive compatibility. Method: We propose a tunable allowance-based utility model that uniformly captures heterogeneous bidders’ profitability constraints and objective heterogeneity. Our approach integrates mechanism design, approximation algorithms, and game-theoretic analysis. Contribution/Results: We present the first (1+ε)-approximate, truthful mechanism under publicly known allowances; under private allowances, we achieve a constant-factor approximate truthful mechanism. Furthermore, we introduce a randomized uniform-price mechanism that guarantees a bounded expected approximation ratio in large markets. All mechanisms are rigorously proven to be incentive-compatible and achieve their respective approximation guarantees.

Technology Category

• Multiagent Systems: Mechanism Design
• Game Theory and Economic Paradigms: Mechanism Design
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

Auction design for the modern advertising market has gained significant prominence in the field of game theory. With the recent rise of auto-bidding tools, an increasing number of advertisers in the market are utilizing these tools for auctions. The diverse array of auto-bidding tools has made auction design more challenging. Various types of bidders, such as quasi-linear utility maximizers and constrained value maximizers, coexist within this dynamic gaming environment. We study sponsored search auction design in such a mixed-bidder world and aim to design truthful mechanisms that maximize the total social welfare. To simultaneously capture the classical utility and the value-max utility, we introduce an allowance utility model. In this model, each bidder is endowed with an additional allowance parameter, signifying the threshold up to which the bidder can maintain a value-max strategy. The paper distinguishes two settings based on the accessibility of the allowance information. In the case where each bidder's allowance is public, we demonstrate the existence of a truthful mechanism achieving an approximation ratio of $(1+epsilon)$ for any $epsilon>0$. In the more challenging private allowance setting, we establish that a truthful mechanism can achieve a constant approximation. Further, we consider uniform-price auction design in large markets and give a truthful mechanism that sets a uniform price in a random manner and admits bounded approximation in expectation.

Problem

• Ad Auctions
• Revenue Maximization
• Bidding Strategies

Innovation

• Ad Auction Model
• Transparency Strategy
• Random Pricing Mechanism