Qualitative study reveals barriers and enablers for digital sustainable business models in energy ecosystems, highlighting collaborative governance and platforms for climate resilience.
Overlapping economic, social, sustainable, health, and military crises create new spaces for scientific research to be applied to practice. The paper focuses on constructing and configuring digital sustainable business models for energy ecosystems that can effectively respond to and mitigate the impacts of dynamic climate change. This topic is important as it contributes to the global transition toward resilient and resource‐efficient energy systems. The research builds on established concepts in strategic management, digital transformation, and sustainability‐oriented business modeling. It also draws on prior studies linking regional innovation ecosystems, public–private collaboration, and energy transition governance. By connecting these strands, the paper extends existing discussions surrounding digital and sustainable innovation in regional energy networks. A qualitative research design was employed to analyze the mechanisms that enable or hinder the creation and management of digital sustainable business models. The findings reveal central barriers and enablers for effectively and efficiently managing digital sustainable business models in energy ecosystems. Among others, coordination complexity, data integration, and regulatory fragmentation were identified as critical barriers, while collaborative governance structures and digital platforms act as strong enablers. The main contribution is the integration of digital transformation and sustainability logic within business model research applied to regional energy ecosystems. It delivers original insights into how digital sustainable business models can be structured to enhance climate resilience and offers a holistic understanding of ecosystem governance under crisis conditions. The thorough qualitative foundation supports both theoretical advancement and practical policy orientation.
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Schachtner et al. (2026) studied this question.
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