关键词: 黄河流域, 绿色低碳, 创新能力, SBM-GML模型, 基尼系数, 核密度分析

Abstract: Understanding the spatial–temporal evolution of green innovation capacity in the nine provinces along the Yellow River is of great significance for promoting ecological conservation and high-quality development in the Yellow River Basin, as well as for implementing China’s national green and low-carbon strategies. Based on relevant data from these provinces from 2014 to 2023, this study constructs an evaluation indicator system for green innovation capacity and conducts an in-depth analysis using the super-efficiency SBM-GML model, Dagum Gini coefficient decomposition, and kernel density estimation. The results reveal several key findings: the green technological innovation capacity of the nine provinces shows a significant policy-driven effect but lacks sustainability; spatial disparities among regions exhibit gradient differentiation; the dynamic evolution demonstrates both polarization and convergence; and long-term performance is determined by the alignment of green innovation with resource endowments and industrial structures. In response, this study proposes that enhancing green technological innovation in these provinces requires breakthroughs in three dimensions: policy coordination, regional differentiation, and technological adaptability. This can be achieved by stabilizing expectations through market mechanisms, promoting collaboration through ecological compensation, optimizing spatial patterns through growth-pole diffusion, and improving resilience through the integration of industrial innovation, ultimately enabling the sustainable and balanced development of green innovation capacity across the basin.

Key words: Yellow River Basin, green and low-carbon, innovation capacity, SBM-GML model, Gini coefficient, kernel density analysis