earticle

영어

Mobile applications (apps) are heavily relying on user data for their initial development, future updates, and successful revenue generation. In general, the use of private data helps developers better design key features, sharpen monetization strategies, and improve big data management capacities. Collecting and utilizing private user data, however, have become more difficult due to new policies and increasing users’ awareness about data privacy. Based on the key tenets of big data management and privacy economy, this research aims to understand the distinct impacts of private data acquisition and utilization approaches on mobile app success under the prevalence of data privacy-related policies and user concerns. We conduct empirical analyses on Apple App Store data containing 2,037 apps’ privacy-related attributes (i.e., privacy nutrition labels). The research empirically substantiates a salient relationship between private data acquisition and utilization approaches for app success. Our results show that apps implementing personalized data-driven strategies stayed in the top charts longer, while sharing data with third parties significantly reduced apps’ presences in the top charts. Surprisingly, improving the efficiency of utilization by diversifying the use of data does not significantly influence app performance. The findings of this research contribute to the literature in privacy valuation from mobile app developers’ perspectives and suggests managerial insights to app creators and policymakers.