Business School, Ningbo University, Ningbo 315211, China.
Donghai Academy, Ningbo University, Ningbo 315211, China.
Int J Environ Res Public Health. 2022 Oct 23;19(21):13772. doi: 10.3390/ijerph192113772.
Based on data from 64 resource-based cities in China from 2010 to 2019, the efficiency of green innovation is evaluated by using the super-efficiency SBM Model with undesired outputs, while influencing factors of green innovation efficiency are analyzed by the spatial Durbin model. The results are as follows. First, as for the efficiency evaluation, the average green innovation efficiency in 62 resource-based cities from 2010 to 2019 is only 0.5689, while the green innovation efficiency of declining cities is the highest, and the growth type is the lowest in the comprehensive planning cities. Second, based on spatial self-correlation in resource-based cities, the government support, and the influencing factors including the industrial structure and economic development, have positive impacts, while the environmental regulations and opening to the outside world will inhibit the urban green innovation. Therefore, to enhance the green innovation efficiency in resource-based cities, some suggestions include formulating differentiated development strategies, forming regional cooperation mechanisms, increasing government scientific and technological support, determining the reasonable intensity of environmental regulations, setting entry barriers for polluting enterprises, and optimizing industrial structure.
基于中国 2010 年至 2019 年的 64 个资源型城市的数据，采用带非期望产出的超效率 SBM 模型对绿色创新效率进行评估，利用空间杜宾模型分析绿色创新效率的影响因素。结果表明：第一，从效率评价来看，2010 年至 2019 年 62 个资源型城市的绿色创新效率平均仅为 0.5689，其中衰退型城市的绿色创新效率最高，综合性规划城市的增长型城市最低。第二，基于资源型城市的空间自相关，政府支持以及包括产业结构和经济发展在内的影响因素具有积极影响，而环境法规和对外开放则会抑制城市的绿色创新。因此，为了提高资源型城市的绿色创新效率，需要制定差异化发展战略、形成区域合作机制、增加政府科技支持、确定合理的环境法规强度、为污染企业设置进入壁垒以及优化产业结构。
