Navigating from spatial heterogeneity to synergistic convergence: The dynamics of innovation efficiency in China's regional innovation ecosystems

This study develops an operational framework for evaluating the efficiency of regional innovation ecosystems (RIEs) based on the innovation value chain perspective. Using methodological tools including the super-efficiency network SBM model, the Global Malmquist–Luenberger (GML) index, the Dagum Gini coefficient, and convergence tests, we conduct an empirical analysis of innovation efficiency in China’s RIEs from 2014 to 2023. The main findings are as follows: (1) Static efficiency shows sustained growth at an average annual rate, with the application innovation phase exhibiting the highest growth, while basic research efficiency displays a declining trend. Spatially, static efficiency follows a gradient pattern of high in the east and low in the west. (2) Dynamic efficiency evolves in an M-shaped trajectory, with the greatest volatility in the product innovation phase and the least in basic research. Regionally, dynamic efficiency exhibits a reverse gradient, with higher levels observed in the west and lower levels in the east. (3) Although overall regional disparities are narrowing, inter-regional differences remain the primary source of inequality. Increasing hypervariable density signals a transition from fragmented development toward synergistic coordination. (4) In terms of convergence characteristics, both σ- and β-convergence are observed in the innovation efficiency of China’s RIEs, indicating that regional disparities tend to diminish over time. Notably, the eastern and western regions converge faster than the central region. These findings clarify the sources of efficiency differences and offer actionable pathways for improving China’s RIEs.