中部六省高技术产业科技资源配置效率研究——基于超效率SBM-Global Malmquist指数模型

Study on the Efficiency of Science and Technology Resource Allocation in High-Tech Industries in Six Central Provinces—Based on the Super-Efficient SBM-Global Malmquist Index Model

摘要: 高技术产业是维护国家安全、增强国家国际竞争力的重要力量。文章运用基于全局参比的超效率SBM模型和Global Malmquist指数分别测算中部六省高技术产业科技资源配置静态以及动态效率。研究结果表明：从静态角度来看，中部六省高技术产业科技资源配置效率整体水平偏低，不同省份在各产业资源配置领域的表现也存在明显差异，江西省医药制造业科技资源配置效率最高，而安徽省在医疗仪器设备及仪器仪表制造业方面科技资源配置效率较高，山西省则在高技术产业其它两个行业表现较好。从动态角度来看，仅计算机及办公设备制造业在整个研究期内科技资源配置效率呈现出增长趋势，而另外三个行业因技术进步有限或技术效率降低，科技资源配置效率呈现下降趋势。基于此，提出优化中部六省科技资源配置效率的政策建议。

Abstract: High-tech industry is an important force to maintain national security and enhance national international competitiveness. The article applies the global reference-based super-efficiency SBM model and Global Malmquist Index to measure the static and dynamic efficiency of high-tech industry S&T resource allocation in the six central provinces respectively. The research results show that: from the static point of view, the overall level of high-tech industry S&T resource allocation efficiency in the six provinces in central China is on the low side, and there are obvious differences in the performance of different provinces in the field of resource allocation in various industries, with Jiangxi Province having the highest S&T resource allocation efficiency in the pharmaceutical manufacturing industry, Anhui Province having a high S&T resource allocation efficiency in the manufacturing industry of medical equipment and instruments, and Shanxi Province performing better in the other two sectors of the high-tech industry. Industry performance is better. From the dynamic point of view, only the computer and office equipment manufacturing industry in the whole study period of science and technology resources allocation efficiency shows a trend of growth, while the other three industries due to limited technological progress or technical efficiency, science and technology resources allocation efficiency shows a downward trend. Based on this, policy recommendations are proposed to optimise the efficiency of S&T resource allocation in the six central provinces.