UC Berkeley

This dissertation combines two papers on industrial organizations and innovations. The first paper focuses on the market evolution in the mobile app platform and the second paper is an empirical study on firm's innovation disclosure and its impact on firm's intellectual property management.

Chapter 1 studies mobile app's platform choice decisions. Ever since Apple and Google launched their mobile application (app) stores in 2008, the market for mobile apps has experienced rapid growth and represents an enormous business opportunity. The success of an app platform largely relies on a great variety of apps, especially innovative and high-quality apps. 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 chapter studies the platform choice decisions of app developers and the implications for the app market evolution through using a unique and big daily-level panel data set that contains information on every app in the two leading app stores, Apple's App Store and Google Play, 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 tends to induce 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 are very useful measures to accelerate the platform expansion, but these policies simultaneously encourage many low-quality apps to enter. Regulations on low-quality apps and attenuating competition are more effective on attracting high-quality apps. Platforms can bundle these policies to achieve the optimal market design.

Chapter 2 focuses on an interesting phenomenon in firm's intellectual property management. Owners of knowledge sometimes choose to disclose their private innovation to the public domain, instead of filing patents or keeping them in secret. Such behaviors are called knowledge disclosure. Once disclosed, the private innovation becomes public knowledge free to use and is no longer patentable. Since it is long believed that private companies take various measures to securely protect their proprietary innovations, the question of how firms benefit from disclosing innovations is worth exploring. Employing a very unique data set of IBM innovation disclosures, I empirically investigate firm's strategic disclosures of private innovation. I further study how such disclosures affect other firm's patented innovation and the focal firm's selective exploitation of follow-up innovation. First, empirical results show that disclosures are not very defensive. They do not undermine citing patents, but lead to stronger citing patents. I also find that IBM discloses relatively low quality innovation on the periphery of its expertise without patenting these. Meanwhile, IBM often discriminatorily cites other firm's patents that are built on its disclosures and are distant from IBM patents assents. This selective utilization results in broader IBM patents and therefore extends its innovation domain.