Exploring Enablers of Data-Driven Sustainable Business Model Innovation: A Systemic View of Innovation Ecosystems

Incumbent firms are increasingly leveraging data-driven technologies to enhance sustainability. However, the mechanisms that enable data-driven sustainable business model innovation (DDSBMI) within innovation ecosystems remain underexplored. This study investigates how DDSBMI enablers interact within such ecosystems by employing a methodological approach that combines automated semantic text analysis and cross-impact analysis. Drawing on a corpus of 90 peer-reviewed publications, we identify 23 interconnected variables that shape DDSBMI across five building blocks: actors, relations, structures, strategies, and governance. Our findings reveal that manufacturers, users, customers, consumers, and product-service systems emerge as critical variables, characterized by high influence and high dependency within the ecosystem. Suppliers, stakeholders, and sustainable business models function as influential variables, shaping ecosystem dynamics while remaining relatively independent. In contrast, digital platforms, circular business models, and co-creation strategies appear as neuter variables, indicating conceptual relevance but limited empirical traction in current academic discourse. This study provides a systematic categorization of DDSBMI enablers and their interrelationships, contributing to innovation ecosystem theory and offering practitioners guidance for navigating the dynamics of DDSBMI ecosystem orchestration.