Collusion

A growing number of companies offer artificial intelligence-powered revenue management platforms, which leverage big data and sensitive business information from multiple firms to optimize pricing, output, and other operational decisions for their clients. Over the past 18 months, dozens of antitrust lawsuits have alleged that such platforms facilitate price-fixing among rivals. Barak Orbach explores the strength of the allegations and the antitrust implications of such revenue management platforms.

In new research, Taylor Begley, Peter Haslag, and Daniel Weagley find that when firms begin sharing a common director, there is a significant reduction in the number of employees that switch jobs between the two companies. The reduction is largest when the firms compete in the same labor market and for those employees who are most costly for firms to replace. The results show the link between overlapping board members and anticompetitive labor practices is a surprisingly widespread phenomenon.

In new research, Giovanna Massarotto explains how collusion manifests differently in the digital economy. She argues that antitrust regulators, scholars, and courts need to incorporate lessons from computer science to update how they monitor markets and identify algorithmic collusion.

Axel Gautier, Ashwin Ittoo, and Pieter van Cleynenbreugel write that the practice of pricing algorithms tacitly colluding remains theoretical for now, and technological obstacles render it very unlikely in the short term. However, regulators must still prepare for a future in which artificial intelligence achieves the necessary sophistication to collude.

What are airline executives really saying to each other with their extensive discussion of “capacity discipline”? New research from the University of Virginia finds...