Mobile App Platform Choice

Abstract

Since Apple and Google launched their mobile app stores in 2008, the market for mobile apps has experienced rapid growth. Given the existence of multiple app platforms, fundamental questions in the app industry are how app developers choose which app platform to enter and which market designs benefit the platform expansion. This paper studies these questions using a unique daily-level panel data set that contains information on every app in the two leading app stores, Apple and Google, over a 2-year period. Combining machine learning techniques for big data problems and computationally efficient econometric approaches, I construct and estimate a structural model for heterogeneous app developers' platform choice decisions within an incomplete-information game framework. I find that in general low-quality apps make the platform less favorable for high-quality entrants. In Google app store, the presence of low-quality apps induces more low-quality apps to enter, while Apple app store exhibits strong competitive effects among high-quality apps. Increasing smartphone user base and improving user engagement could accelerate the platform expansion, but also encourage many low-quality apps to enter. Regulations on low-quality apps and attenuating competition are more effective attracting high-quality apps. Platforms can bundle these policies to achieve better marketing evolution.