How the Digital Innovation Ecosystem Drives Regional Green Innovation Cooperation—Based on Machine Learning Key Factor Mining and Dynamic QCA Causal Analysis

Against the backdrop of global digitalization and green development, digital innovation ecosystems have emerged as key drivers for advancing regional green innovation cooperation and achieving sustainable development goals. This study constructs a theoretical analytical framework encompassing “Actor-Resource-Environment.” Utilizing panel data from 30 Chinese provinces spanning 2012–2022, it employs machine learning and dynamic QCA methods to dissect the dynamic causal relationship between digital innovation ecosystems and regional green innovation cooperation. Key findings include: (1) Green innovation cooperation networks are evolving from a “core-periphery structure” toward new characteristics of multi-centered mutual coupling and coordination. (2) Different machine learning models yield varying effects on how digital innovation ecosystems influence regional green innovation cooperation, with the XGBoost model demonstrating the strongest performance. (3) No single element within the digital innovation ecosystem can serve as a necessary condition for driving regional green innovation cooperation. (4) Three configuration patterns emerge for achieving high-level regional green innovation cooperation, with digital innovation funding, digital talent resources, and digitally inclusive financial environments consistently serving as core prerequisites. These findings deepen our understanding of the complex causal mechanisms involving multi-factor matching and linkage that influence regional green innovation cooperation, offering valuable insights for advancing high-quality regional green innovation development. The research findings reveal the complex configuration pathways through which multidimensional elements of the digital innovation ecosystem collectively drive regional green innovation cooperation. This provides practical governance pathways for breaking down regional barriers and building highly resilient green innovation cooperation networks.