Green Technological Innovation, Spatial Spillovers, and the Green Transformation of High-Tech Manufacturing in China

Green technological innovation is widely regarded as a key driver of sustainable industrial transformation, yet most existing research focuses on local effects and neglects spatial interdependence. Using panel data for 30 Chinese provinces from 2010 to 2024, this study measures green transformation performance (GTP) in high-tech manufacturing by integrating a network slacks-based measure (SBM) model with the Global Malmquist–Luenberger (GML) productivity index and estimates spatial Durbin models under multiple spatial weight matrices. The results show that green technological innovation significantly improves local GTP: the baseline coefficients of lagged green patents are positive and statistically significant across all specifications, ranging from 0.0216 to 0.0247, and the decomposed direct effects are consistently positive at approximately 0.025. The spatially lagged green innovation terms are also positive and significant under the three baseline matrices, and the decomposed indirect effects range from 0.051 to 0.129, while total effects range from 0.076 to 0.154, indicating positive but matrix-sensitive spatial spillovers. Heterogeneity analyses reveal pronounced differences between inland and coastal provinces and between regions with different manufacturing foundations: significant total effects are concentrated in coastal provinces and in regions with a high manufacturing foundation, whereas inland provinces show insignificant effects and low-manufacturing-foundation regions exhibit weaker or even negative effects under some matrices. These findings highlight that green transformation is shaped by both local innovation capacity and spatially mediated knowledge diffusion, and underscore the need for coordinated, regionally differentiated policies.