Affiliation:
1. Area of Production and Operations Management, Indian Institute of Management, Bangalore 560076, India
Abstract
Digital platforms share their customers’ data with social planners, who may utilize it to improve socioeconomic infrastructure. This may benefit customers because of the experience of improved infrastructure. On the contrary, it may lead to privacy concerns among them (as these data sets may include sensitive information). In this paper, we analyze the game-theoretic model to characterize the granularity of data sharing between firms and the social planner and the investments by the social planner to improve public infrastructure. In order to analyze the impact of regulation on data sharing strategy, we consider the cases when data sharing is regulated (decided by the social planner) and unregulated (strategically decided by firms). Our analysis reveals that the firms as well as the social planner decrease the granularity of data with an increase in privacy concerns among customers. To analyze the impact of regulation, we compare the granularity of data shared under unregulated and regulated scenarios. We find that when the firm is monopolist, it shares data with a higher level of granularity in the unregulated scenario. Interestingly, we find that under market competition, the data granularity may be higher or lower compared with the regulated scenario. Specifically, we find that if firms jointly determine the granularity of data to be shared, they share data with higher granularity under the unregulated scenario; however, if they do not collaborate and individually decide on data sharing, we find that regulation leads to higher granularity of data to be shared. Finally, we find that firms’ payoffs and customer surplus are higher under the unregulated data-sharing setup if they jointly determine the granularity of data; however, if they do not collaborate on data sharing, their payoffs, as well as customer surplus, are higher under regulation. Supplemental Material: The online appendix is available at https://doi.org/10.1287/serv.2022.0052 .
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)