Abstract
We are amidst a significant shift in how companies price their products and services. A rapidly increasing number of firms use pricing algorithms to recommend or determine prices. Like many technological transitions, the widespread adoption of pricing algorithms can raise important questions and implicate significant tradeoffs.
There are three core competitive scenarios around algorithmic pricing: (1) human agreements to fix prices with algorithmic implementation, (2) sharing competitively sensitive data through a shared algorithm to recommend or set prices or production, and (3) feeding public data into an algorithm to recommend or set prices. Each scenario reflects unique legal and factual considerations. Accordingly, each requires a tailored solution to address specific competitive concerns.
Part I of this article explains the legal framework for evaluating claims of collusion under Section 1 of the Sherman Antitrust Act. Part II analyzes three different scenarios involving algorithmic pricing. Part III discusses legislative proposals to address algorithmic pricing. Part IV offers my conclusion that each of the scenarios discussed in Part II requires a solution that is narrowly tailored.
Link to Full Article:
Fixing Algorithmic Pricing? Competition Concerns and Solutions