中国科技创新效率测度及时空特征研究  

Research on the Measurement and Spatial and Temporal Characteristics of China’s Scientific and Technological Innovation Efficiency

作　　者：杨丽萍 

机构地区：[1]成都信息工程大学统计学院,四川 成都

出　　处：《可持续发展》2024年第12期2931-2939,共9页Sustainable Development

摘　　要：高校作为科技创新的重要基地,本文对2013~2022年的中国高校科技统计资料,通过BCC-DEA模型并结合Malmquist指数对中国高校科技创新效率进行静态和动态测度,同时综合各省市自治区地理空间关系,建立空间杜宾模型探究其空间特征,得出如下结论:技术进步是推动科技创新综合效益提升的关键因素;科技创新效率地区差异显著,DEA有效主要集中在北京、上海、江苏、浙江、陕西等经济基础雄厚和教育资源丰富地区;中国高校科技创新效率存在负向的空间溢出效应。最后结合实际情况,提出建议。Universities are important bases for scientific and technological innovation. This article uses the BCC-DEA model and the Malmquist index to conduct static and dynamic measurements of the scientific and technological innovation efficiency of Chinese universities based on the scientific and technological statistics of Chinese universities from 2013 to 2022. At the same time, it combines the geography of various provinces, municipalities and autonomous regions. Spatial relationship, a spatial Durbin model was established to explore its spatial characteristics, and the following conclusions were drawn: technological progress is a key factor in promoting the improvement of comprehensive benefits of scientific and technological innovation;regional differences in scientific and technological innovation efficiency are significant, and the effectiveness of DEA is mainly concentrated in Beijing, Shanghai, Jiangsu, In areas with strong economic foundations and rich educational resources such as Zhejiang and Shaanxi, there is a negative spatial spillover effect on the scientific and technological innovation efficiency of universities in China. Finally, suggestions are made based on the actual situation.

关 键 词：空间计量 BCC-DEA模型 MALMQUIST指数 

分 类 号：F42[经济管理—产业经济]