The success of an app platform largely relies on a great variety of innovative apps. Given the existence of multiple app platforms, fundamental questions in the app industry are how heterogeneous app developers choose which app platform to enter and which market designs benefit the platform expansion. Combining machine learning techniques and structural estimation, this paper studies these questions using a unique and big 2-year panel data set covering entire Apple and Google app stores. I find that Google and Apple app stores exhibit different competition structures across high-type and low-type apps. Counterfactual experiments investigate market policies regarding platform designs.
This research provides rich implications with regarding the market design, given the existence of multiple completing platforms.