Paper Number
ICIS2025-1489
Paper Type
Complete
Abstract
Data-sharing ecosystems (DSEs) emerge as key organizational arrangements for digital innovation, yet their economic and governance foundations remain poorly understood. Drawing on qualitative evidence from major European DSEs, this study identifies six conditions that shape viability, ranging from investment needs and innovation logic to integration complexity, security management, competitive dynamics, and interest alignment. The findings show that these conditions evolve across the development of DSEs, and that sustainability depends both on the ability to establish tailored use cases and on how orchestrators adapt governance to the ecosystem structure. The study contributes to ecosystem and platform theory by reframing DSEs as generative, innovation-driven structures, conceptualizing economic viability as phase-contingent, and integrating strategic and technical governance roles into a unified, context-dependent model. These insights advance theoretical understanding of ecosystem economics and provide guidance for the design of data ecosystems capable of achieving long-term sustainability.
Recommended Citation
Eustache, Lucas; Brousseau, Eric; and Toledano, Joëlle, "The Economics of Data-Sharing: An Empirical Investigation of Data Sharing Ecosystems" (2025). ICIS 2025 Proceedings. 6.
https://aisel.aisnet.org/icis2025/sharing_econ/sharing_econ/6
The Economics of Data-Sharing: An Empirical Investigation of Data Sharing Ecosystems
Data-sharing ecosystems (DSEs) emerge as key organizational arrangements for digital innovation, yet their economic and governance foundations remain poorly understood. Drawing on qualitative evidence from major European DSEs, this study identifies six conditions that shape viability, ranging from investment needs and innovation logic to integration complexity, security management, competitive dynamics, and interest alignment. The findings show that these conditions evolve across the development of DSEs, and that sustainability depends both on the ability to establish tailored use cases and on how orchestrators adapt governance to the ecosystem structure. The study contributes to ecosystem and platform theory by reframing DSEs as generative, innovation-driven structures, conceptualizing economic viability as phase-contingent, and integrating strategic and technical governance roles into a unified, context-dependent model. These insights advance theoretical understanding of ecosystem economics and provide guidance for the design of data ecosystems capable of achieving long-term sustainability.
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