Designing data collaboratives’ governance dimensions for long-term stability: an empirical analysis

The momentum surrounding the use of data for the public good has grown over the past few years, resulting in several initiatives, and rising interest from public bodies, intergovernmental organizations, and private organizations. The potential benefits of data collaboratives (DCs) have been proved in several contexts, including health, migration, pandemics, and public transport. However, these cross-sectoral partnerships have frequently not progressed beyond the pilot level, a condition hindering their ability to generate long-term societal benefits and scale their impact. Governance models play an important role in ensuring DCs’ stability over time; however, existing models do not address this issue. Our research investigates DCs’ governance settings to determine governance dimensions’ design settings enhancing DCs’ long-term stability. The research identifies through the literature on collaborative governance and DCs seven key governance dimensions for the long-term stability of DCs. Then, through the analysis of 16 heterogeneous case studies, it outlines the optimal design configurations for each dimension. Findings make a significant contribution to academic discourse by shedding light on the governance aspects that bolster the long-term stability of DCs. Additionally, this research offers practical insights and evidence-based guidelines for practitioners, aiding in the creation and maintenance of enduring DCs.