长江流域资源与环境 >> 2023, Vol. 32 >> Issue (9): 1783-1795.doi: 10.11870/cjlyzyyhj202309002

• 长江经济带高质量发展(专栏) • 上一篇    下一篇

长江经济带创新发展水平综合测度与空间异质性分析

于灵慧1,2,徐紫腾3,袁  丰1,4*   

  1. (1. 中国科学院南京地理与湖泊研究所/中国科学院流域地理学重点实验室,江苏 南京 210008;2. 中国科学院大学,北京 100049; 3. 河南大学黄河文明与可持续发展研究中心,河南 开封 475001; 4. 中国科学院大学南京学院,江苏 南京 211135)
  • 出版日期:2023-09-20 发布日期:2023-09-22

Comprehensive Measurement and Spatial Heterogeneity Analysis of  Level of Innovation and Development in Yangtze River Economic Belt

YU Ling-hui1,2,XU Zi-teng3,YUAN Feng1,4   

  1. (1. Nanjing Institute of Geography and Limnology/ Key Laboratory of Watershed Geographic Sciences, Chinese Academy of Sciences, Nanjing 210008, China; 2. University of Chinese Academy of Sciences, Beijing 100049, China; 3. Key Research Institute of Yellow River Civilization and Sustainable Development of Henan Province, Henan University, Kaifeng 475001, China; 4. University of Chinese Academy of Sciences, Nanjing, Nanjing 211135, China)
  • Online:2023-09-20 Published:2023-09-22

摘要: 创新是推动经济发展的新引擎,探究创新发展对促进长江经济带的高质量发展具有重要意义。基于2010、2015、2020年长江经济带108个地级及以上城市的数据,从创新发展的内涵出发,构建涵盖创新资源、创新投入、创新绩效、创新环境4个维度的综合评价指标体系。运用基于熵权法的Topsis评估对长江经济带城市创新发展总体及分维度水平进行测算,并运用Dagum基尼系数分解等方法探究城市群创新发展水平的时空差异性、演化梯度性特征。研究表明:(1)长江经济带创新资源、创新投入、创新绩效逐年优化,但创新环境呈现出先上升后下降的趋势,高值区主要集中在核心城市和经济较为发达的城市;(2)总体创新发展水平不断提升,空间分布上表现出从上游到中游到下游阶梯式递增特征;(3)总体创新发展水平的基尼系数呈现先上升后下降的趋势,城市群间的差异是影响长江经济带创新发展不平衡的主要因素。

Abstract: Innovation is a new engine to promote economic development. Exploring the development of innovation is of great significance to promoting the high-quality development of the Yangtze River Economic Belt. Based on the data of 108 prefecture-level and above cities in the Yangtze River Economic Belt in 2010, 2015, and 2020, starting from the connotation of innovation and development, a comprehensive evaluation index system covering four dimensions of innovation resources, innovation investment, innovation performance, and innovation environment is constructed. Using the Topsis assessment based on the entropy weight method to measure the overall and subdimension levels of urban innovation in the Yangtze River Economic Belt. Using methods such as Dagum’s Gini coefficient decomposition to explore the spatial and temporal differences and evolution gradient characteristics of the urban agglomeration’s innovation and development level. The research shows that: (1) The innovation resources, innovation investment, and innovation performance of the Yangtze River Economic Belt are being optimized year by year, but the innovation environment shows a trend of rising first and then declining, and the high-value areas are mainly concentrated in core cities and cities with relatively developed economies. (2) The overall level of innovation continues to improve, and the spatial distribution shows a stepwise increase from the upper reaches to the middle reaches to the lower reaches. (3) The Gini coefficient of the overall innovation and development level shows a trend of rising first and then falling. The difference between urban agglomerations is the main factor that affects the imbalance of innovation development in the Yangtze River Economic Belt.

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