Spatial spillovers and causal configurations of the digital economy driving green manufacturing transformation in China

The digital economy has emerged as a critical engine for high-quality economic development, yet its specific mechanisms and configurational pathways in empowering green manufacturing transformation remain under-explored. Based on panel data from 31 provinces in China (2012–2023), this study constructs a dual-methodological framework integrating the Spatial Durbin Model (SDM) and fuzzy-set Qualitative Comparative Analysis (fsQCA) to investigate the spatiotemporal evolution, transmission mechanisms, and causal recipes of this relationship. The empirical results reveal four key findings. First, green manufacturing transformation exhibits a steady upward trend but follows a distinct “East-High, West-Low” spatial gradient. Second, the digital economy exerts a significant positive impact on local green transformation and generates positive spatial spillovers to neighboring regions, though the spillover effect is weaker than the direct effect due to administrative barriers; technological innovation and environmental regulation are identified as two pivotal transmission channels. Third, a “Northeast Paradox” is observed: while the digital economy promotes green growth in most regions, it shows a significant negative interaction effect in the Northeast, attributed to the “lock-in effect” of rigid industrial structures. Fourth, fsQCA identifies four sufficient pathways leading to high green efficiency: “Digital-Talent Driven,” “Digital-Innovation Driven”, “Internal-Capability Driven”, and “Comprehensive Synergy”. Notably, a substitution effect exists between talent support and R&D intensity, offering flexible transformation strategies for resource-constrained regions. By moving beyond linear effect analysis, this study provides a multidimensional analytical roadmap to support the design of differentiated, context-sensitive green transformation policies.