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It is not (only) about privacy: How multi-party computation redefines control, trust, and risk in data sharing

Author

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  • Wirawan Agahari

    (Delft University of Technology)

  • Hosea Ofe

    (Delft University of Technology)

  • Mark Reuver

    (Delft University of Technology)

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.

Suggested Citation

  • Wirawan Agahari & Hosea Ofe & Mark Reuver, 2022. "It is not (only) about privacy: How multi-party computation redefines control, trust, and risk in data sharing," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1577-1602, September.
    • Handle: RePEc:spr:elmark:v:32:y:2022:i:3:d:10.1007_s12525-022-00572-w
    DOI: 10.1007/s12525-022-00572-w
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    References listed on IDEAS

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    Cited by:

    1. Michael Fruhwirth & Viktoria Pammer-Schindler & Stefan Thalmann, 2024. "Knowledge Leaks in Data-Driven Business Models? Exploring Different Types of Knowledge Risks and Protection Measures," Schmalenbach Journal of Business Research, Springer, vol. 76(3), pages 357-396, September.
    2. Andreas Engelmann & Gerhard Schwabe, 2024. "Certified data chats for future used car markets," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-22, December.
    3. Rainer Alt, 2022. "Electronic Markets on platform culture," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(3), pages 1019-1031, September.
    4. Mark Reuver & Hosea A. Ofe & Mila Gasco-Hernandez & Boriana Rukanova & J. Ramon Gil-Garcia, 2024. "Data economy in a globalized world, opportunities and challenges for public and private organizations," Electronic Markets, Springer;IIM University of St. Gallen, vol. 34(1), pages 1-5, December.

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    More about this item

    Keywords

    Privacy-enhancing technology; Multi-party computation; Data sharing; Control; Trust; Risk;
    All these keywords.

    JEL classification:

    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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