长江流域资源与环境 >> 2022, Vol. 31 >> Issue (4): 738-749.doi: 10.11870/cjlyzyyhj202204002

• 区域可持续发展 • 上一篇    下一篇

基于DEA-Malmquist和Tobit模型的长三角城市群绿色创新绩效研究

葛世帅,曾  刚,杨  阳,苏  灿,陈鹏鑫   

  1. (华东师范大学中国现代城市研究中心/城市与区域科学学院,上海 200062)
  • 出版日期:2022-04-20 发布日期:2022-04-21

Research on Green Innovation Performance of Yangtze River Delta Urban Agglomerations Based on DEA-Malmquist and Tobit Model

GE Shi-shuai, ZENG Gang, YANG Yang, SU Can, CHEN Peng-xin   

  1. (Center for Modern Chinese City Studies, School of City and Regional Science, East China Normal University, Shanghai 200062, China)
  • Online:2022-04-20 Published:2022-04-21

摘要: 应用DEA-Malmquist方法对长三角城市群2012~2018年的绿色创新绩效进行了测度,并运用Tobit回归分析法对影响研究区绿色创新绩效的因素进行分析,实证结果表明:(1)长三角城市群城市绿色创新绩效参差不齐,差距明显;绿色创新绩效整体有所提升,即新的知识技术等促进了绿色经济发展,但效果并不明显;对全要素增长率的贡献主要来自于技术进步水平的提高,说明技术进步仍然是区域绿色创新绩效提升的主要手段,从2012~2018年绿色创新绩效动态发展来看,更印证了提升技术进步的重要性;城市在发展过程中对追求技术进步和在现有资源禀赋下对技术的利用情况的协调欠佳。(2)城市群城市间绿色创新绩效空间分异特征明显,整体上“东高西低”。绩效水平较高的城市在空间上形成一定的集聚,呈“Z”字型的空间分布特征;江苏省绿色创新绩效水平整体表现较为突出,安徽省多数城市绩效较差。(3)产业结构对绿色创新绩效的影响较显著,推进产业结构优化升级是区域提升绿色创新绩效的重要途径。增强区域间信息的通达性能够带来创新绩效水平的提升。

Abstract:  This paper uses the DEA-Malmquist method to measure the green innovation performance of the Yangtze River Delta Urban Agglomerations from 2012 to 2018, and uses Tobit regression analysis to analyze the factors affecting the green innovation performance of the study area. The empirical results show that: (1) From the green innovation performance scores, the green innovation efficiency of cities in the Yangtze River Delta Urban Agglomerations is uneven, and the gap is obvious; the overall green innovation efficiency has been improved, that is, new knowledge and technology have promoted the development of green economy, but the effect is not obvious; The contribution of the total factor growth rate mainly comes from the improvement of the level of technological progress, indicating that technological progress is still the main means to improve the performance of regional green innovation. The dynamic development of green innovation performance from 2012 to 2018 further confirms the importance of enhancing technological progress; In the process of urban development, there is a poor coordination between the pursuit of technological progress and the utilization of technology under the existing resource endowment. (2) The spatial differentiation of green innovation performance among cities in the urban agglomeration is obvious, with “high in the east and low in the west” as a whole. Certain spatial agglomeration, forming a “Z”-shaped spatial distribution characteristic; Jiangsu Province has a more outstanding overall performance level, and most cities in Anhui Province have poor green innovation performance. (3) The regression analysis on the influencing factors of green innovation capability shows that the industrial structure has a significant impact on the efficiency of green innovation. Enhancing the accessibility of information between regions can improve the level of innovation performance.

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