长江流域资源与环境 >> 2022, Vol. 31 >> Issue (12): 2582-2596.doi: 10.11870/cjlyzyyhj202212003

•　区域可持续发展　• 上一篇    下一篇

长江中游城市群创新效率时空变化及溢出效应

仇  怡1,2，郑  泽1，吴建军1   

  1. （1.湖南科技大学商学院，湖南 湘潭 411201；2.湖南省高校哲学社会科学重点研究基地“产业经济高质量发展研究中心”，湖南 长沙 410004）
  • 出版日期:2022-12-20 发布日期:2023-01-13

Spatial-temporal Evolution and Spillover Effects of Innovation Efficiency of Urban Agglomeration in Middle Reaches of Yangtze River

QIU Yi1,2, ZHENG Ze1, WU Jan-jun1   

  1. (1.School of Business, Hunan University of Science and Technology, Xiangtan 411201, China;2. Research Center of High quality Development of Industrial Economy, Central South University of Forestry and Technology, Changsha 410004, China)
  • Online:2022-12-20 Published:2023-01-13

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摘要： 选取2008~2019年长江中游城市群28个城市的面板数据，构建创新效率评价指标体系，运用三阶段DEA模型测算城市创新效率并揭示其时空变化特征。在此基础上，构建多种空间权重矩阵，运用空间杜宾模型分析影响城市创新效率的主要因素及其空间溢出效应。研究结果表明：（1）长江中游城市群创新效率整体呈波动变化趋势，各城市创新效率差异明显，其中南昌、武汉、宜昌、荆州和长沙等城市创新效率相对较高，景德镇、鹰潭、新余、孝感、岳阳和常德等城市相对较低。（2）城市创新效率空间格局总体呈现以武汉为核心、南昌和长沙为重要创新节点，向周围城市逐渐递减的特征，其中高效率地区由西向东演化的趋势日益明显，较高效率地区由分散布局转向相对集中分布，中效率地区集中成片分布，而低效率地区散落式分布且有减少趋势。（3）城市创新效率存在显著为正的空间溢出效应，并对关联城市的科技创新发展形成“涓滴效应”。（4）地区经济发展、教育支持和交通水平对城市创新效率具有显著的促进作用，而对外开放有负效应，市场结构、金融发展和人力资本能促进本城市创新效率提升，但对关联城市有负向溢出效应；固定资产投资对本城市创新效率有阻碍作用，但能促进关联城市创新发展。

Abstract: Based on the panel data of 28 cities in the urban agglomeration in the middle reaches of the Yangtze River from 2008 to 2019, this paper has constructed the innovation efficiency evaluation index system, and used the three-stage DEA model to measure urban innovation efficiency and reveal its temporal and spatial characteristics. On this basis, by constructing a variety of spatial weight matrices and using the spatial Dubin model, the main factors and spatial spillover effects of the urban innovation efficiency has been analyzed. The results show that: (1) The urban innovation efficiency of urban agglomeration in the middle reaches of the Yangtze River shows a fluctuating development trend as a whole. The innovation efficiency of each city is obviously different, among which the innovation efficiency of Nanchang, Wuhan, Yichang, Jingzhou and Changsha have relatively high innovation efficiency, cities such as Jingdezhen, Yingtan, Xinyu, Xiaogan, Yueyang and Changde are relatively low. (2) The overall spatial pattern of urban innovation efficiency is characterized by Wuhan as the core, Nanchang and Changsha as important innovation nodes, and gradually decreasing to the surrounding cities, among which the trend of the evolution of high-efficiency areas from west to east is increasingly obvious, higher efficiency areas have shifted from scattered layout to relatively concentrated distribution, medium-efficiency areas are concentrated in patches, while low-efficiency areas are scattered and have a decreasing trend. (3) Urban innovation efficiency has a significant positive spatial spillover effect, which can produce a “trickle-down effect” to the science and technology innovation development of related cities.(4) Regional economic development, education support and transportation level have a significant role in promoting urban innovation efficiency, while opening to the outside world has a negative effect, market structure, financial development and human capital can promote the innovation efficiency of the city, but it has a negative spillover effect on the associated cities; fixed asset investment has a hindering effect on the innovation efficiency of the city, but it can promote the innovation and development of the associated cities.

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