Abstract
Computational antitrust promises not only to help antitrust agencies preside over increasingly complex and dynamic markets but also to provide companies with the tools to assess and enforce their compliance with antitrust laws. If research in the space has been primarily dedicated to supporting antitrust agencies, this article fills the gap by offering an innovative solution for companies. Specifically, this article serves as a proof of concept whose aim is to guide antitrust agencies in creating a decision-trees based antitrust compliance API intended for market players. It includes an open-access prototype of the API, which automates compliance with Article 102 TFEU by providing companies with access to the legality tests behind the most common practices. Finally, the article discusses the API limitations and lessons learned.
Original language | English |
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Journal | Stanford Computational Antitrust |
Early online date | 18 Oct 2022 |
Publication status | Published - 28 Feb 2023 |