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Paper Number
3072
Paper Type
LitReview
Abstract
This research examines the concept of data cooperatives, an emerging data governance model where members pool their data and manage it democratically for their benefit. We conduct a conceptual review using a systematic conceptual analysis method. The analysis identified five defining characteristics of data cooperatives: 1) cooperativism and high-reciprocity; 2) data subject-centeredness; 3) subversiveness; 4) collective action and benefit; 5) fiduciary responsibility. We developed a concept system, positioning data cooperatives as a subtype of platform cooperatives and data stewardship institutions; distinguishing them from coordinate concepts such as data commons, trusts, and collaboratives. Finally, from our analysis, we present a set of five differentiating determinants for data cooperatives, highlighting important decisions relevant to development of different data cooperatives. Expanding on current IS research, we contribute to conceptual clarity of the term, presenting valuable theoretical insights. Further, our findings can inform the future establishment of data cooperatives in practice.
Recommended Citation
Petreski, Davor and Cheong, Marc, "Data Cooperatives: A Conceptual Review" (2024). ICIS 2024 Proceedings. 15.
https://aisel.aisnet.org/icis2024/lit_review/lit_review/15
Data Cooperatives: A Conceptual Review
This research examines the concept of data cooperatives, an emerging data governance model where members pool their data and manage it democratically for their benefit. We conduct a conceptual review using a systematic conceptual analysis method. The analysis identified five defining characteristics of data cooperatives: 1) cooperativism and high-reciprocity; 2) data subject-centeredness; 3) subversiveness; 4) collective action and benefit; 5) fiduciary responsibility. We developed a concept system, positioning data cooperatives as a subtype of platform cooperatives and data stewardship institutions; distinguishing them from coordinate concepts such as data commons, trusts, and collaboratives. Finally, from our analysis, we present a set of five differentiating determinants for data cooperatives, highlighting important decisions relevant to development of different data cooperatives. Expanding on current IS research, we contribute to conceptual clarity of the term, presenting valuable theoretical insights. Further, our findings can inform the future establishment of data cooperatives in practice.
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