Learning-by-doing in non-homogeneous tasks: An empirical study of content creator performance on a music streaming platform

Abstract

With the development of high-speed internet and better mobile connections, online streaming platforms with user-generated videos are becoming popular. The success of these platforms relies on content creators who can effectively enhance user engagement (e.g., subscribing to a content creator’s channel). As opposed to homogeneous production scenarios (e.g., assembling automobiles in a factory), creating user-generated videos is a more complex task in which learning might happen. In this study, we empirically test the effect of prior experience on content creators’ performance. Furthermore, we examine the role of specialization in learning. We use a dataset from NetEase Cloud Music, one of the most popular music streaming platforms in China, with 21,549 content creators and 252,762 user-generated videos. The findings indicate that: (1) prior experience has a positive effect on creators’ performance; (2) specialized experience across distinct video categories has a nonlinear effect on creators’ performance. These results have implications for improving user engagement for online user-generated video streaming platforms.