区域科技创新资源配置效率测度——以珠三角为例

为提高珠三角科技创新资源配置效率，推动粤港澳大湾区创新协同发展，采用非期望产出的超效率SBM模型，对珠三角9市2014—2018年的科技创新资源配置效率进行测度，运用Malmquist指数进一步评估效率的动态变化，并就资源整合提出建议. 结果表明:(1)科技创新资源主要集中在广州、深圳、佛山等经济发展水平较高的城市；(2)工业污染对科技创新资源配置效率的提高具有一定的抑制作用；(3)珠三角科技创新资源配置效率总体较高, 其中深圳市领跑，江门、肇庆市居后；(4)由Malmquist指数分解来看，技术进步是决定科技创新资源配置效率差异的重要因素.

Measuring the Efficiency of Regional Scientific and Technological Innovation Resources Allocation: A Case Study of the Pearl River Delta

The super-efficiency SBM model which considers undesirable outputs is used to measure the efficiency of scientific and technological innovation resources allocation in the Pearl River Delta from 2014 to 2018 and the Malmquist index is used to evaluate the dynamic changes of the efficiency for the purpose of its improvement and the coordinated development of innovation in the Guangdong-Hong Kong-Macao Greater Bay Area. The suggestions on resource integration was finally put forward. As the results show, the scientific and technological innovation resources are mainly concentrated in cities with high level of economic development such as Guangzhou, Shenzhen and Foshan; industrial pollution places restrictions on improving the efficiency of scientific and technological innovation resources allocation; and the overall efficiency of scientific and technological innovation resources allocation in the Pearl River Delta is high, with Shenzhen ranking first and Jiangmen and Zhaoqing ranking last. According to the Malmquist index decomposition, technological development is an important factor in the difference of efficiency of scientific and technological innovation resources allocation.