Measuring Fair Competition on Digital Platforms

Digital platforms use recommendations to facilitate the exchange between platform actors, such as trade between buyers and sellers. Platform actors expect, and legislators increasingly require that competition, including recommendations, are fair—especially for a market-dominating platform on which self-preferencing could occur. However, testing for fairness on platforms is challenging because offers from competing platform actors usually differ in their attributes, and many distinct fairness definitions exist. This article considers these challenges, develops a five-step approach to measure fair competition through recommendations on digital platforms, and illustrates this approach by conducting two empirical studies. These studies examine Amazon’s search engine recommendations on the Amazon marketplace for more than a million daily observations from three countries. They find no consistent evidence for unfair competition through search engine recommendations. The article also discusses applying the five-step approach in other settings to ensure compliance with new regulations governing fair competition on digital platforms, such as the Digital Markets Act in the European Union or the proposed American Innovation and Choice Online Act in the United States