Streaming Platform and Strategic Recommendation Bias - Marc Bourreau; Germain Gaudin (Center for Economic Studies and ifo Institute (CESifo), 2018)
We consider a streaming platform which carries content from various upstream content providers. Participating customers face personalized recommendations from the platform and consume a mix of content originating from each provider. We analyze when the platform uses its personalized recommendation system to steer consumers from one content provider to another. We establish the conditions under which the recommendation system allows the platform to credibly threaten upstream providers to steer consumers away from their content in order to reduce their market power. We find that the streaming platform can increase its profit by reducing the royalty rate it pays to content providers through the use of a recommendation system which is strategically biased in favor of the cheaper content.
Keywords: D40; L10; L50; 330; streaming platform; recommendation system; personalization; bias