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Abstract Firms are often reluctant to share data because of mistrust, concerns over control, and other risks. Multi-party computation (MPC) is a new technique to compute meaningful insights without having to transfer data. This paper investigates if MPC affects known antecedents for data sharing decisions: control, trust, and risks. Through 23 qualitative interviews in the automotive industry, we find that MPC (1) enables new ways of technology-based control, (2) reduces the need for inter-organizational trust, and (3) prevents losing competitive advantage due to data leakage. However, MPC also creates the need to trust technology and introduces new risks of data misuse. These impacts arise if firms perceive benefits from sharing data, have high organizational readiness, and perceive data as non-sensitive. Our findings show that known antecedents of data sharing should be specified differently with MPC in place. Furthermore, we suggest reframing MPC as a data collaboration technology beyond enhancing privacy.

Purpose This paper aims to propose a framework for how privacy-preserving technologies (PETs) create business value for organizations. The framework was developed by examining the literature on privacy and information technology’s impact (symbolic and function). The authors evaluate the framework’s applicability using multiparty computation (MPC) as an instance of PETs, with expert interviews in the telecommunication industry. Design/methodology/approach In an illustrative case of four telecommunication companies, the authors conducted semi-structured interviews with experts and used MPC as an instance of PET. Findings The evaluation of the framework indicates that PETs create business value for organizations: enhancing customer interactions, sales, personalized services, predicting market trends and collaboration among organizations. The findings show that business value of PETs is mainly driven by consumers and organizations willing to share data and collaborate. Research limitations/implications This study was limited to the telecom sector and focused on MPC as an instance of PET. Further studies should be conducted to explore the benefits of other PETs and MPC. Future research could find out if this framework is also helpful for implementing other PETs or even other types of technology. The authors’ framework provides factors that future studies can use to quantify the impact of PETs. The authors hope that this framework provides an overarching reference for organizations considering the adoption of PETs. Practical implications The authors’ findings inform managers in exploring the business value of PETs for organizations. This study also provides insights into which costs and risks to consider when implementing PETs. Originality/value This study is one of the few to propose a framework on how PETs create business value for organizations. Future research can use factors in the framework (e.g. customer interactions, sales, personalized services and market trend prediction) to conduct a quantitative study on PETs’ business value. Managers adopting PETs can use the framework to identify areas where PETs impact their organization.