Achieving voluntary data sharing in cross sector partnerships: Three partnership models
Open accessAbstract
The complex societal problems that we face today require unprecedented collaboration and evidence-based decisions. These collaboration processes are further propelled by the datafication of virtually all spheres of public life. To benefit from this, the data needs to be made available to allow for data analytics. Thus, data sharing becomes a crucial aspect of cross-sector collaborations that aim to create and capture value from information. Compared to collaborations where data sharing is not the main goal, data sharing partnerships face a number of novel challenges, such as mitigating data risks, complying with data protection legislation, and ensuring responsible data use. Navigating these waters and achieving data sharing can be challenging for both governments and businesses, as well as other actors. How do organizations from different sectors manage to achieve data sharing for addressing societal challenges? To address this research question, we apply a framework of three models of cross sector social partnerships developed in the field of organization studies to structure the analysis of six cases. Our analysis suggests that to a certain extent the partnership model determines the types of drivers and challenges to sharing data in a partnership. Leveraging the drivers and anticipating these challenges can help organizations be more aware of key terms of the collaboration and the mechanisms that can be used to succeed in their partnership goals.
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Moving beyond one-way information disclosure to genuine co-creation and partnership models is essential for aligning AI systems with societal values and expectations.
“Moving beyond one-way information disclosure to genuine co-creation and partnership models, as advocated by international bodies, is essential for aligning AI systems with societal values and expectations [53,71].”
From Addressing Challenges for the Effective Adoption of Artificial Intelligence in the Energy Sector (2025) · cites this paper as [71]
Collaboration emphasizes the necessity of multi-stakeholder approaches involving industry, policymakers, academia, and civil society to co-create standards, share knowledge, and build consensus.
“Collaboration emphasizes the necessity of multi-stakeholder approaches involving industry, policymakers, academia, and civil society to co-create standards, share knowledge, and build consensus [53,71].”
From Addressing Challenges for the Effective Adoption of Artificial Intelligence in the Energy Sector (2025) · cites this paper as [71]
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The “missing link” in data-informed governance: An exploratory study of data-related capabilities
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Pattanaik, P. K., Gupta, S., & Jha, A. K. (2026) · Information Systems Frontiers · doi:10.1007/s10796-026-10831-2
- Authors
- Susha, I., Rukanova, B., Zuiderwijk, A., Gil-Garcia, J. R., & Gasco Hernandez, M.
- Affiliations
- Utrecht University (NL)
- Delft University of Technology (NL)
- Corresponding author
- Susha, Iryna
- Venue
- Information and Organization
- Publisher
- Elsevier BV
- Published
- 2023-03
- Volume
- 33
- Issue
- 1
- Pages
- 100448
- ISSN
- 1471-7727 (ISSN-L)
- OpenAlex
- W4321382152
- Cited by
- 55
- References
- 58
- Citations by year
- 2026: 18 · 2025: 20 · 2024: 11 · 2023: 6
- FWCI
- 24.07
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Information and Organization (publishedVersion, cc-by)
- Utrecht University Repository (Utrecht University) (submittedVersion, other-oa)
- Research Repository (Delft University of Technology) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Funders
- Vetenskapsradet
- Horizon 2020 (786746)
- National Science Foundation (1649820)
- Horizon 2020 Framework Programme
- European Commission Seventh Framework Programme for Research and Technological Development Information and Communication Technol (603993)
- Horizon 2020 Marie Skłodowska-Curie Actions (955569)
- Topics
- Social Sciences › Public Administration › Public Policy and Administration Research
- Social Sciences › Political Science and International Relations › E-Government and Public Services
- Physical Sciences › Engineering › Media Technology › Smart Cities and Technologies
- Keywords
- intersectoral collaboration, partnership model, datafication, data protection law, responsible data use, data risk, societal challenges, public-private collaboration, social partnership, data analytics
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