Reduced demand uncertainty and the sustainability of collusion : How AI could affect competition
Year of publication: |
2021
|
---|---|
Authors: | O'Connor, Jason ; Wilson, Nathan E. |
Published in: |
Information economics and policy : IEP. - Amsterdam [u.a.] : Elsevier, ISSN 0167-6245, ZDB-ID 877702-0. - Vol. 54.2021, p. 1-22
|
Subject: | Artificial Intelligence | Uncertainty | Collusion | Price Discrimination | Antitrust | Wettbewerbsbeschränkung | Restraints of competition | Theorie | Theory | Preismanagement | Pricing strategy | Künstliche Intelligenz | Artificial intelligence | Preisdifferenzierung | Price discrimination | Wettbewerbspolitik | Competition policy | Kartell | Cartel | Wettbewerb | Competition | Kartellrecht | Antitrust law |
-
Reduced demand uncertainty and the sustainability of collusion : how AI could affect competition
O'Connor, Jason, (2019)
-
Autonomous algorithmic collusion : economic research and policy implications
Assad, Stephanie, (2021)
-
Autonomous algorithmic collusion: economic research and policy implications
Assad, Stephanie, (2021)
- More ...
-
Reduced Demand Uncertainty and the Sustainability of Collusion : How AI Could Affect Competition
O'Connor, Jason, (2019)
-
Reduced demand uncertainty and the sustainability of collusion : how AI could affect competition
O'Connor, Jason, (2019)
-
Economics at the FTC : non-price merger effects and deceptive automobile Ads
Jones, Matthew, (2018)
- More ...