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基于区域视角的科技成果转化绩效评价指标体系研究
引用本文:胡中慧,陶润生,袁洋.基于区域视角的科技成果转化绩效评价指标体系研究[J].科技和产业,2018(1):57-62.
作者姓名:胡中慧  陶润生  袁洋
作者单位:浙江师范大学 经济与管理学院, 浙江 金华 321004,浙江师范大学 经济与管理学院, 浙江 金华 321004,浙江师范大学 经济与管理学院, 浙江 金华 321004
摘    要:运用管理学、现代数学等理论,对科技成果转化系统和机制进行客观分析,从科技成果应用、科技成果商业化、科技成果产业化、科技成果国际化四个方面,将其细分为8个指标因素,各指标权重运用主成分分析法确定,以2010-2016年全国30个地区为样本,计算了各地区科技成果转化绩效值。结果发现,技术市场成交合同额对科技成果转化绩效评价的影响最大,中国的科技成果转化绩效仍然处于一个比较低的水平,不同地区科技成果转化发展不平衡,存在明显的差异性,对于科技成果转化的影响因素有深入分析的必要,从而达到从根本上提高科技成果转化绩效的目的。最后对本文的创新和不足之处作了总结。

关 键 词:科技成果  绩效  主成分分析法

Research on Performance Evaluation Index System of Scientific and Technological Achievement Transformation Based on Regional
Abstract:This paper uses the theory of management and modern mathematics to analyze the scientific system and the mechanism of scientific and technological achievements, and analyzes it from the four aspects of the application of scientific and technological achievements, the commercialization of scientific and technological achievements, the industrialization of scientific and technological achievements and the internationalization of scientific and technological achievements And the weight of each index is determined by principal component analysis. In this paper, the performance of scientific and technological achievements in each region is calculated based on 30 regions in 2010-2016. The results show that the contract volume of technical market has the greatest impact on the performance evaluation of scientific and technological achievements. The performance of China''s scientific and technological achievements is still at a relatively low level. The development of scientific and technological achievements in different regions is unbalanced, and there are obvious differences. The influencing factors have the necessity of in-depth analysis, so as to achieve the purpose of fundamentally improving the performance of scientific and technological achievements. Finally, the innovation and shortcomings of this paper are summarized.
Keywords:scientific and technological achievements  performance  principal component analysis
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