中国高技术产业科技创新效率评价研究——基于三阶段超效率DEA模型

Research on the Evaluation of Innovation Efficiency of China's High-tech Industry--Based on the Three-Stage Super-Efficiency DEA Model

本文以2019年中国30个省份为研究对象,构建三阶段超效率DEA模型并对数据进行测算排名,对高技术产业创新效率进行评价。实证结果表明,相较于第一阶段超效率DEA的测算结果,第三阶段的测算结果效率值有所下降,而且各省份间差异明显,呈现为区域发展不平衡。在经济、政策、科技、贸易等诸多方面的影响中,地区人均生产总值和有R&D活动的企业数是提升高技术产业创新效率的有利因素,科学技术支出占地方财政支出比重和进出口额占GDP比重则是不利因素。基于此,从实行差别化创新、学习先进科学技术、鼓励梯次联动区域创新角度提出建议,为解决高技术产业科技创新效率无效的区域问题提供研究视角与改进思路。

This article takes 30 provinces in China in 2019 as the research object,constructs a three-stage super efficiency DEA model,calculates and ranks the data,and evaluates the innovation efficiency of high-tech industries.The empirical results indicate that compared to the calculation results of the super efficiency DEA in the first stage,the efficiency value of the calculation results in the third stage has decreased,and there are significant differences among provinces,presenting an imbalance in regional development.Among many factors affecting the economy,policies,technology,trade,and other aspects,the per capita GDP of a region and the number of enterprises with R&D activities are favorable factors for improving the innovation efficiency of high-tech industries,while the proportion of science and technology expenditure to local fiscal expenditure and the proportion of import and export volume to GDP are unfavorable factors.Based on this,suggestions are proposed from the perspectives of implementing differentiated innovation,learning advanced science and technology,and encouraging hierarchical linkage of regional innovation,providing a research perspective and improvement ideas to solve the regional problem of ineffective technological innovation efficiency in high-tech industries.