An Economic Model and Simulation Results of App Adoption Decisions on Networks with Interdependent Privacy Consequences

The popularity of third-party apps on social network sites and mobile networks emphasizes the problem of the interdependency of privacy. It is caused by users installing apps that often collect and potentially misuse the personal information of users’ friends who are typically not involved in the decision-making process. In this paper, we provide an economic model and simulation results addressing this problem space. We study the adoption of social apps in a network where privacy consequences are interdependent. Motivated by research in behavioral economics, we extend the model to account for users’ other-regarding preferences; that is, users care about privacy harms they inflict on their peers. We present results from two simulations utilizing an underlying scale-free network topology to investigate users’ app adoption behaviors in both the initial adoption period and the late adoption phase. The first simulation predictably shows that in the early adoption period, app adoption rates will increase when (1) the interdependent privacy harm caused by an app is lower, (2) installation cost decreases, or (3) network size increases. Surprisingly, we find from the second simulation that app rankings frequently will not accurately reflect the level of interdependent privacy harm when simultaneously considering the adoption results of multiple apps. Given that in the late adoption phase, users make their installation decisions mainly based on app rankings, the simulation results demonstrate that even rational actors who consider their peers’ wellbeing might adopt apps with significant interdependent privacy harms. Our findings complement the usable privacy and security studies which show that users install privacy-invasive apps because they are unable to identify and understand apps’ privacy consequences; however, we show that fully-informed and rational users will likely fall for privacy-invasive apps as well.