From data jungle to data governance in digital ecosystems: Empirical evidence from a multiple holistic case study

With increasing access to external data sources, firms are engaging in digital ecosystems to create data-driven products and services. However, governing data in these multi-actor environments is a critical challenge characterized by the need to reconcile conflicting institutional logics. Applying institutional complexity as theoretical lens, this study utilizes a multiple holistic case study of five digital ecosystems. Our findings reveal that data governance principles are not simply top-down mandates but are emergent institutional arrangements that resolve underlying tensions between actors. Based on this, we develop a framework for data governance comprised of four interdependent pillars. We theorize that these pillars operate as a dynamic control-loop, where continuous mutual adjustment enables ecosystems to adapt and maintain stability in response to internal and external pressures. This study contributes to governance theory by reframing data governance from a static design problem to a continuous process of adaptation.