Platformization of data sharing: Multi-party computation (MPC) as control mechanism and its effect on firms' participation in data sharing via data marketplaces

Data sharing facilitated by data marketplaces enable companies to generate meaningful insights and discover new opportunities. However, enterprises are reluctant to share data over platforms due to lack of trust, fear of losing control over data and concerns regarding privacy violations. Multi-party computation (MPC) is a cryptographic technique that enables joint data analyses by multiple parties while retaining data secrecy. Despite the potential of MPC, its meaning in data marketplaces setting and how MPC change firms' behavior towards data sharing is not yet researched. This research aims to explain why and how MPC could enable platform control and affect firms' participation in data sharing via data marketplaces. To do so, we will employ a mixed-method research design by combining semi-structured interviews with actors in the mobility domain and quantitative experiments using a mockup of MPC-enabled data marketplaces. Our initial findings revealed various barriers and incentives for firms in sharing their data. We expect our research to become a foundation for future research in the emerging phenomenon of platformization of data sharing via data marketplaces and the key role of MPC in enabling the data economy.