Designing Strategy-Proof Auctions: A Game Theory, Mechanism Design, and Computational Perspective

Abstract

This paper examines the evolution of auction design from ancient traditions to modern digital markets, focusing on the development of strategy-proof mechanisms that incentivize truthful bidding. The research analyzes classical formats including first-price and English auctions, highlighting their strategic limitations, before exploring the Vickrey-Clarke-Groves (VCG) mechanism which achieves dominant-strategy incentive compatibility through externality pricing. The study then empirically contrasts Google's Generalized Second-Price (GSP) auction with Meta's VCG-inspired approach in digital advertising markets. Cost-per-click analysis reveals an average premium of $1.52 in GSP auctions, with industry-specific variations reaching $3.88. A computational complexity analysis demonstrates that GSP achieves O(n log n) time complexity compared to VCG's O(nk), providing algorithmic justification for GSP's prevalence in latency-sensitive real-time bidding environments. These findings suggest that real-world mechanism selection depends critically on the interplay between theoretical properties, market structure, and computational constraints. CCS CONCEPTS Theory of computation~Theory and algorithms for application domains~Algorithmic game theory and mechanism design~Computational pricing and auctions.