Paper Number
ICIS2025-2335
Paper Type
Short
Abstract
Data ecosystems are increasingly adopted in industrial sectors to enable cross-organizational data sharing, yet their governance remains poorly understood. Existing models of platform governance fall short of explaining the federated and competitive dynamics that arise when powerful incumbents jointly govern data ecosystems. To address this gap, we conceptualize data ecosystems as information commons and draw on polycentric governance theory to explain how heterogeneous stakeholders coordinate without a single authority and collectively define, adapt, and enforce rules. Based on a multiple-case study of three automotive, mobility, and manufacturing data ecosystems, we show how polycentric practices such as boundary regulation, shared accountability, and provider recognition materialize in three governance modes: enabling, sustaining, and scaling. This conceptualization advances platform governance theory by explaining how federated ecosystems can evolve in the absence of a central orchestrator, and it highlights polycentric governance as a viable approach for fostering sustainable value co-creation across development stages.
Recommended Citation
Kernstock, Philipp; Stahl, Tamara; Hein, Andreas; and Krcmar, Helmut, "Polycentric Governance of Data Ecosystems" (2025). ICIS 2025 Proceedings. 22.
https://aisel.aisnet.org/icis2025/sharing_econ/sharing_econ/22
Polycentric Governance of Data Ecosystems
Data ecosystems are increasingly adopted in industrial sectors to enable cross-organizational data sharing, yet their governance remains poorly understood. Existing models of platform governance fall short of explaining the federated and competitive dynamics that arise when powerful incumbents jointly govern data ecosystems. To address this gap, we conceptualize data ecosystems as information commons and draw on polycentric governance theory to explain how heterogeneous stakeholders coordinate without a single authority and collectively define, adapt, and enforce rules. Based on a multiple-case study of three automotive, mobility, and manufacturing data ecosystems, we show how polycentric practices such as boundary regulation, shared accountability, and provider recognition materialize in three governance modes: enabling, sustaining, and scaling. This conceptualization advances platform governance theory by explaining how federated ecosystems can evolve in the absence of a central orchestrator, and it highlights polycentric governance as a viable approach for fostering sustainable value co-creation across development stages.
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19-SharingEconomy