广东省生产力服务体系科技创新服务能力评价模型构建研究

Research on the Construction of the Evaluation Model of Scientific and Technological Innovation Service Ability of Productivity Service System in Guangdong Province

摘要:

“十三五时期”，广东省生产力服务体系快速发展，规模逐年壮大，服务内容从传统的中介服务逐步向全链条创新服务转变，发展趋势不断往专业化、网络化、集成化和国际化转变，逐步成为粤港澳大湾区国际科技创新中心和广东科技创新强省建设的重要支撑。为适应广东省生产力服务体系发展的新形势，进一步提升生产力中心系统的科技创新服务能力，亟需建立一套系统、全面的生产力科技创新服务能力评价体系，客观、科学地推进生产力体系的创新发展，作为其动态管理及政策支持的重要依据。因此，本文运用基于熵权法的TOPSIS综合评价方法，构建广东省生产力服务体系科技创新服务能力评价模型，并通过灰色关联分析法验证了评价模型的合理性，确定了关键影响因素。经实证研究发现，2010-2018年间广东省生产力服务体系科技创新服务能力总体呈上升趋势；各区域生产力促进中心发展不均衡，珠三角地区遥遥领先于粤东西北地区；企业服务能力、人力资源、科技创新资源对生产力服务体系科技创新服务能力影响相对显著。

Abstract:

During the 13th Five Year Plan period, the productivity service system of Guangdong Province developed rapidly and its scale grew year by year. The service content gradually changed from the traditional intermediary service to the whole chain innovation service. The development trend continued to change to specialization, networking, integration and internationalization, and gradually became an important support for the construction of the international science and technology innovation center of Guangdong-Hong Kong-Macao Greater Bay Area and the strong province of Guangdong science and technology innovation. In order to adapt to the new situation of the development of productivity service system in Guangdong Province and further improve the technological innovation service ability of productivity center system, it is necessary to establish a systematic and comprehensive evaluation system of productivity technological innovation service ability, objectively and scientifically promote the innovation and development of productivity system as an important basis for its dynamic management and policy support. Therefore, this paper uses the TOPSIS comprehensive evaluation method based on entropy weight method to build the evaluation model of scientific and technological innovation service capacity of productivity service system in Guangdong Province, and verifies the rationality of the evaluation model and determines the key influencing factors through the grey correlation analysis method. Through empirical research, it is found that the service capacity of scientific and technological innovation of productivity service system in Guangdong Province is on the rise from 2010 to 2018; the development of productivity promotion centers in various regions is unbalanced, and the Pearl River Delta region is far ahead of the East and northwest of Guangdong; the influence of enterprise service capacity, human resources and scientific and technological innovation resources on the service capacity of scientific and technological innovation of productivity service system is relatively significant.