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What makes and breaks Data Cooperatives? A multi-case study of barriers and enablers

Davor Petreski*, Olivera Marjanovic, Marc Cheong

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

Abstract

Data cooperatives are member-owned enterprises where members collectively manage and benefit from their pooled data. While data cooperatives offer a promising alternative to power asymmetries and data practices in the dominant corporate platform paradigm, many data cooperatives encounter challenges and often struggle to sustain themselves. Existing research in this area remains conceptual and research investigating data cooperatives’ evolution and sustainability over time is needed. This paper presents a multi-case study of six data cooperatives, examining factors influencing their longevity or dissolution. The case study unveils four potential factors: (1) funding and financial constraints, (2) the wider environment and context where the DC is situated, (3) value proposition and incentives structure, and (4) autonomy/dependency on large corporate platforms and technology. By moving beyond conceptualization of the rapidly emerging phenomenon of data cooperatives, this study contributes to both interdisciplinary and IS research. The findings also offer practical insights into the development and sustainability of current and future data cooperatives.

Original languageEnglish
Title of host publicationPACIS 2025 Proceedings
Place of PublicationKuala Lumpur
PublisherAIS Electronic Library (AISeL)
Pages1-17
Number of pages17
Publication statusPublished - 2025
EventPacific-Asia Conference on Information Systems (29th : 2025) - Kuala Lumpur, Malaysia
Duration: 5 Jul 20259 Jul 2025

Publication series

NamePACIS proceedings
ISSN (Print)2689-6354

Conference

ConferencePacific-Asia Conference on Information Systems (29th : 2025)
Country/TerritoryMalaysia
CityKuala Lumpur
Period5/07/259/07/25

Keywords

  • data cooperatives
  • data governance
  • data ethics

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