From Network Effects to Data Network Effects: Enabling Ecosystemic Innovation for Sustainability

This paper distinguishes between traditional network effects and data network effects, showing how the latter become central levers of sustainability transitions by enhancing efficiency, equity, and resilience across ecosystems. We argue that data network effects provide a more dynamic and sustainable basis for value creation, not only by enhancing firm-level performance but, more importantly, also by enabling ecosystemic innovation. They allow distributed actors across industries to cocreate novel solutions and adapt jointly to complex challenges, especially in ecosystems undergoing digital transformation … Drawing on case studies in precision agriculture, digital healthcare, and decentralized energy, we show how these effects improve performance, foster ecosystem-wide learning, and support sustainability objectives such as resource efficiency, equity, and resilience. A comparative framework clarifies key differences in value drivers, saturation risks, and competitive dynamics. We further explore how orchestrators – such as distribution system operators, healthcare consortia, and agri-data platforms – can become stewards of shared intelligence by aligning innovation strategies with ethical, open, and interoperable data governance. This paper concludes by outlining future research priorities, including sustainability metrics for data ecosystems and policy frameworks that enable responsible and inclusive platform evolution.