Master Thesis
Search, Quality, and Subscription Platforms
New Economic School Best Student Research Paper Award 2025
Abstract: I model a subscription platform that (i) charges a subscription fee, (ii) pays per-stream royalties that differ by quality, and (iii) controls the first item consumers see. Consumers conduct pseudo-ordered search with a reservation utility; creators, facing heterogeneous effort costs, decide whether to supply high quality. The platform’s royalty is a cost, so ranking decisions are a steering tool that trades royalty savings against user satisfaction and, in turn, reshapes creators’ effort incentives. Solutions pin down the reservation cut-off, the creator cost threshold, and the platform’s joint choice of royalty gap and bias. The framework I have built allows us to answer different questions regarding the subscription platforms pricing, content management, and quality provision, and it can be used further to answer different specific questions for a platforms regulation. I also provide comparative statics linking search frictions, royalty heterogeneity, and catalog quality, and offers a benchmark for current debates on Spotify’s “Discovery Mode” and algorithmic self-preferencing.