吴飞美. 中国区域科技创新政策效率时空差异与时空演化研究[J]. 电子科技大学学报社科版, 2023, 25(2): 21-29. DOI: 10.14071/j.1008-8105(2022)-1103
引用本文: 吴飞美. 中国区域科技创新政策效率时空差异与时空演化研究[J]. 电子科技大学学报社科版, 2023, 25(2): 21-29. DOI: 10.14071/j.1008-8105(2022)-1103
WU Fei-mei. Research on the Spatial Difference and Spatial Evolution of Chinese Science and Technology Innovation Policies[J]. Journal of University of Electronic Science and Technology of China(SOCIAL SCIENCES EDITION), 2023, 25(2): 21-29. DOI: 10.14071/j.1008-8105(2022)-1103
Citation: WU Fei-mei. Research on the Spatial Difference and Spatial Evolution of Chinese Science and Technology Innovation Policies[J]. Journal of University of Electronic Science and Technology of China(SOCIAL SCIENCES EDITION), 2023, 25(2): 21-29. DOI: 10.14071/j.1008-8105(2022)-1103

中国区域科技创新政策效率时空差异与时空演化研究

Research on the Spatial Difference and Spatial Evolution of Chinese Science and Technology Innovation Policies

  • 摘要:
    目的/意义科技创新政策在推进国家自主创新的过程中起着越来越重要的作用,科技创新政策的效率直接影响到各个地区的技术创新与经济发展水平。
    设计/方法运用三阶段数据包络分析(DEA)方法,在剔除了环境因素影响后对2016~2020年我国30个省、市、自治区科技创新政策效率进行了测算,再利用探索性空间数据分析(EDSA)方法对我国区域科技创新政策效率值做空间相关性分析。
    结论/发现我国科技创新政策效率存在明显空间特征和显著正向空间相关性,区域之间呈现出东部高高集聚和西部低低集聚的两种集群,空间时空跃迁表现出较强的空间稳定性,空间分布格局不易变化。

     

    Abstract: Purpose/Significance The science and technology innovation policies(STIPs)play an increasingly important role in promoting the process of national independent innovation. Their efficiency directly affects the technological innovation and economic development in regions. Design/Methodology This paper uses the three-stage DEA method to measure the efficiency of 30 Chinese provincial STIPs in 2016~2020 after removing environmental factors, and then uses the EDSA method to analyze the spatial correlation of the efficiency of China’s STIPs. Conclusions/Findings The research shows that the STIPs in China has obvious spatial characteristics and significant positive spatial correlation. There are two clusters of eastern High-High agglomeration and western Low-Low agglomeration. The spatial space-time transition shows strong spatial stability and the spatial distribution pattern is not easy to change.

     

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