中国区域创新生态系统动态运行效率的区域差异分解及形成机制研究

Research on the Decomposition and Formation Mechanism of Regional Differences in the Dynamic Operating Efficiency of China’s Regional Innovation Ecosystem

伴随创新驱动战略的大力落实,区域创新生态系统的构建与优化,已成为政府和学界共同关注的焦点。以社会生态系统为逻辑起点,将自然生态系统和社会生态系统的运行特点融合演化类比出区域创新生态系统的概念,以创新生态环境为投入,创新生态主体为产出,采用SE-SBM DEA模型和Malmquist-Luenberger指数测度了2007—2018年中国八大综合经济区创新生态系统动态运行效率,并采用Dagum基尼系数和PVAR模型,实证检验了创新生态系统动态运行效率的区域差异分解及形成机制。结果发现:在2007—2018年间,各地区创新生态系统动态运行效率和技术效率整体呈下降趋势,而技术进步呈上升趋势;技术效率的衰退是导致创新生态系统动态运行效率衰退的主要原因。技术进步弥补了因技术效率衰退带来的消极影响。组间差距和超变密度是导致中国创新生态系统动态运行效率、技术效率与技术变化差距的主要原因。在年际变化上,组间差距的贡献在逐渐降低,而超变密度的贡献在逐渐上升,表明各地区的创新生态系统动态运行效率、技术效率与技术变化在空间上呈“离散”分布。上述现象形成的主要原因在于技术效率、技术变化与动态效率的相互作用关系存在显著的区域异质性特征。为此,需针对不同地区的创新生态系统运行的技术效率和技术变化展开治理手段。对技术效率的提升主要强调创新管理制度的革新,对技术进步的提升强调推动区域互动合作。

The construction and optimization of the regional innovation ecosystem have become the government and academia’s focus in the background of implementing an innovation-driven strategy. This paper is based on the social ecosystem as the logical starting point, constructs a concept of the regional innovation ecosystem by analogy with the operational characteristics of the natural ecosystem and the social ecosystem and measures the dynamic operational efficiency of innovation ecosystems in China’s eight comprehensive economic zones from 2007 to 2018 by using SE-SBM DEA model which taking the innovative ecological environment as the input and the innovative ecological main body as the output and Malmquist-Luenberger index. Meanwhile, it adopts the Dagum Gini coefficient and PVAR model to empirically test the regional difference decomposition and formation mechanism of the dynamic operating efficiency of innovation ecosystems. The study finds that from 2007 to 2018, the dynamic operational efficiency and technical efficiency of innovation ecosystems in various regions show a downward trend, while technological change shows an upward movement.The decline of technical efficiency is the main reason for decreasing the dynamic operational efficiency of innovation ecosystems. Technological change compensates for the negative impact of the decrease in technological efficiency. The gap between groups and transvariation density is the main reason for the gap between the dynamic operational efficiency, technical efficiency, and technological change of China’s innovation ecosystem. From the perspective of inter-annual variation,the contribution of the between-group gap gradually decreases, while the contribution of transvariation density increases progressively. It indicates the dynamic operational efficiency, technical efficiency, and technological change of innovation ecosystems in various regions are spatially discrete distribution. The main reason for the above phenomenon is significant regional heterogeneity in the interaction relationship between technical efficiency, technological change and dynamic efficiency. Specifically, there is an interaction between dynamic operating efficiency, technical efficiency and technological change on the northern coast, the eastern coast, and the northwest. There is no interaction between dynamic operational efficiency, technical efficiency and technological change on the southern coast. In the northeast region and the middle Yangtze River region, the dynamic operational efficiency and technological changes jointly affect the technical efficiency. In the middle Yellow River region, dynamic operational efficiency and technological changes can affect technical efficiency.There is an interaction between dynamic operational efficiency and technical efficiency in the southwest region, and both of them are affected by technological change. Therefore, the paper proposes that the authorities carry out governance measures according to innovation ecosystem operation’s technical efficiency and technological change in different regions. The improvement of technical efficiency mainly emphasizes the innovation of innovation management institutions, and the upgrading of technological change emphasizes the promotion of regional innovation cooperation. The main contribution of this paper is that the connotation of the regional innovation ecosystem constructed by analogy with the characteristics of natural ecosystems and social ecosystems is helpful to enrich the theoretical framework of innovation management and provide the theoretical basis for governments at all levels to manage regional innovation ecosystem. On the other hand,the paper reveals the internal structure of dynamic operational efficiency of the innovation ecosystem and analyzes the formation reasons for regional heterogeneity characteristics and provides theoretical reference and empirical evidence for local governments to optimize the regional innovation ecosystem and explore ways to narrow regional differences.