TY - JOUR
T1 - It is not (only) about privacy
T2 - How multi-party computation redefines control, trust, and risk in data sharing
AU - Agahari, W.
AU - Ofe, H.A.
AU - de Reuver, G.A.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - privacy-enhancing technology
KW - multi-party computation
KW - data sharing
KW - control
KW - risk
KW - trust
UR - http://www.scopus.com/inward/record.url?scp=85135281484&partnerID=8YFLogxK
U2 - 10.1007/s12525-022-00572-w
DO - 10.1007/s12525-022-00572-w
M3 - Article
SN - 1019-6781
VL - 32
SP - 1577
EP - 1602
JO - Electronic Markets
JF - Electronic Markets
IS - 3
ER -