Diego Aparicio (University of Navarra, IESE Business School) & Kanishka Misra (University of California, San Diego (UCSD)) have posted Artificial Intelligence and Pricing on SSRN. Here is the abstract: As businesses become more sophisticated and welcome new technologies, artificial intelligence-based.
Machine learning can be an effective tool to set competitive prices.
Artificial intelligence has its limits on how to set the most effective prices due to variables beyond the seller s control.
Over the long term, supracompetitive pricing can result.
CATONSVILLE, MD, January 12, 2021 - Machine learning and artificial intelligence (AI) are perfectly suited to help companies and marketers monitor and set prices based on real-time dynamic pricing. But new research has identified some possible unintended consequences of AI in this area.
Machine learning algorithms don t always account for factors outside of the seller s control, such as competitor prices. Researchers found that if AI algorithms are setting prices over the long term, a monopolistic price effect is possible, essentially creating a collusive pricing environment in the marketplace. This represents a challenge for policymakers as the researchers show that independent AI pricing algorithms can result in supracompetitive