政府干预视角下长三角城市群科技创新资源配置效率及影响因素研究

The Allocation Efficiency of S T Resources and Influencing Factors in the Yangtze River Delta Urban Agglomeration based on the Perspective of Government Intervention

摘要:

科技创新资源的优化配置是贯彻落实创新驱动发展战略的必然要求。长三角城市群作为我国经济社会运行和科技事业发展的先行区,其科技创新资源有效整合和开放共享对于深化科技体制改革和优化区域创新布局具有重要意义。本文以政府干预为研究视角,运用超效率DEA模型和 DEA-Malmquist模型对2011-2020年长三角城市群科技创新资源配置效率进行测算,并采用Tobit模型以政府干预为核心解释变量对长三角城市群科技创新资源配置的影响因素进行实证分析。研究发现,2011-2020年长三角城市群科技创新资源配置效率整体呈现递增趋势,但是城市群内部科技创新资源配置效率差异悬殊,区域空间格局极不平衡,而政府干预对提高科技创新资源配置具有显著正向影响。

Abstract:

The optimal allocation of technological innovation resources is an inevitable requirement for implementing the innovation driven development strategy. The Yangtze River Delta urban agglomeration, as a leading area for China"s economic and social operation and scientific and technological development, is of great significance for the effective integration and open sharing of scientific and technological innovation resources in deepening scientific and technological system reform and optimizing regional innovation layout. This paper takes government intervention as the research perspective, uses the super efficiency DEA model and DEA Malmquist model to measure the efficiency of scientific and technological innovation resource allocation in the Yangtze River Delta urban agglomeration from 2011 to 2020, and uses the Tobit model to empirically analyze the influencing factors of scientific and technological innovation resource allocation in the Yangtze River Delta urban agglomeration with government intervention as the core explanatory variable. Research has found that the overall efficiency of scientific and technological innovation resource allocation in the Yangtze River Delta urban agglomeration showed an increasing trend from 2011 to 2020. However, there are significant differences in the efficiency of scientific and technological innovation resource allocation within the urban agglomeration, and the regional spatial pattern is extremely unbalanced. Government intervention has a significant positive impact on improving the allocation of scientific and technological innovation resources.