Greedy or desperate? Performance feedback and app data misconduct

In the digital economy, personal data has materialized as new assets that not only engender value for organizations but also render them susceptible to security risks. Instances of unauthorized user information exploitation by mobile applications for economic benefits have become conventional, and outperforming apps are no exception. What is the motivation for app data misconduct? Based on the behavioral theory, we discuss the performance motivation of app data misconduct and find that performance feedback intensity, regardless of whether it is positive or negative, can motivate apps to take such deviant risks. Furthermore, we scrutinize the roles of app user scale, category competition, and regional legal development in shaping data misconduct decisions. Using a sample of apps operating in China's domestic market, we empirically substantiate these arguments and contribute insights that bear both theoretical significance and pragmatic pertinence in the spheres of behavioral theory, organizational misconduct and corporate data responsibility.