Frontiers: Algorithmic Collusion: Supra-competitive Prices via Independent Algorithms

2021/01/01 by Karsten T. Hansen, Kanishka Misra, Mallesh M. Pai · 6 citations
Business, Management and Accounting · Decision Sciences · #Advanced Bandit Algorithms Research #Auction Theory and Applications #Consumer Market Behavior and Pricing

paper · doi:10.1287/mksc.2020.1276

openalex publication_date 2021/01/01 · openalex created_date 2021/01/18 · openalex updated_date 2026/07/31

Abstract

We show that the long-run prices from independent machine learning algorithms depend on the informational value of price experiments. If low, the long-run prices are consistent with the static Nash equilibrium; however, if high, the long-run prices are supra-competitive.

Citations

• Artificial Intelligence, Algorithmic Pricing, and Collusion

Cited by

• Breaking Algorithmic Collusion in Human-AI Ecosystems
• Naive analytics: The strategic advantage of algorithmic heuristics
• Collusion with Optimal Information Disclosure
• AI in business research
• Too Noisy to Collude? Algorithmic Collusion Under Laplacian Noise
• Algorithmic Collusion is Algorithm Orchestration

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