Digital Content Creation: An Analysis of the Impact of Recommendation Systems

The success of digital content platforms such as YouTube depends on the creativity of independent content creators and the efficiency of content distribution. These platforms share advertising revenue with content creators to induce creative effort. Most platforms also use recommendation systems to provide personalized content recommendations for each consumer. Since the creators' revenues depend on their demand, the criteria of demand allocation embedded in the recommendation system may influence creators' content creation behavior. In this paper, we study how a platform's recommendation system can affect content creation, profits, and welfare. Our results show that a platform may benefit by deliberately biasing its recommendations to intensify competition among creators. Interestingly, we find that biased recommendations can lead to a win-win in which the platform, consumers, and content creators can benefit. We also show that consumers may be worse off when they are more knowledgeable and less dependent on the recommendation system. In addition, we find that the platform, consumers, and creators can benefit when the platform has better information on consumer preferences.