Streaming Platform and Strategic Recommendation Bias

Abstract

We consider a platform that carries content from two upstream content providers and presents personalized recommendations to participating customers. We focus on streaming platforms in media markets, where users pay a subscription fee to join the platform but no usage fee, and consume a mix of content originating from each provider. We characterize the bias in the user-specific recommendations offered by the platform when one content provider charges lower royalties than the other. We establish that if consumers are sufficiently insensitive to bias, the recommendation system allows the platform to credibly threaten upstream providers to steer consumers away from their content, which reduces their market power. We also investigate the effects of vertical integration by the platform and show the robustness of our results to non-linear (personalized) streaming services.

Keywords: Streaming Platform, Recommendation System, Personalization, Bias

JEL Classification: D4, L1, L5