Dynamics of Openness in Mobile Platforms: Understanding the Impact of Third-Party Apps’ User Data Sharing

How does participation in platform-enabled user data sharing affect the performance of third-party apps (TPAs) in mobile ecosystems? While data sharing has become increasingly prevalent, its implications for TPA performance remain ambiguous. This study theorizes and empirically examines four competing pathways through which data sharing can influence TPA performance: (1) focal TPA feature diversification, (2) rival TPA feature diversification, (3) focal TPA feature differentiation, and (4) rival TPA feature differentiation. Drawing on the logic of sequential innovation, we argue that data sharing facilitates diversification into adjacent markets but may erode differentiation within focal markets due to shared access to user data. We test these pathways through a novel quasi-experimental design using the rollout of Apple’s HealthKit as an exogenous shock, analyzing panel data from 724 free iOS health and fitness apps. Our results reveal that data sharing reduces both focal and rival TPA feature differentiation and increases rival TPA diversification—each negatively impacting TPA performance. However, focal TPA feature diversification increases, which enhances TPA performance. Together, the findings reveal that while data sharing can broaden strategic scope, it simultaneously threatens competitive distinctiveness. This study advances our understanding of platform openness, intra-platform competition, and innovation in digital ecosystems.