摘要
“211”“985”建设的重点高校是我国“双一流”高校建设的领头院校,探究其优质科研成果产出绩效水平,对推进我国建设“双一流”高校具有重要的指导意义。文章首先基于因子分析法构建体现高质量科研产出成果的评价指标体系,其次运用DEA模型对“双一流”建设领头院校的2015—2016年科研效率进行实证分析。研究结果发现“双一流”建设实施前后领头院校的高质量科研效率水平提升幅度较小,大部分院校虽然呈上升趋势但依旧处于无效水平,且具有较大的提升空间,说明“双一流”建设实施成果初步有效但还有很大的完善空间,据此提出完善科研运行机制、创新激励体制等改进措施。
The key universities in“211”and“985”construction are the leading universities in the construction of“double first-class”universities in China.It is of great guiding significance to explore the output performance level of their high-quality scientific research achievements to promote the construction of“double first-class”universities in China.This paper first builds an evaluation index system of high-quality scientific research output based on factor analysis method,and then makes an empirical analysis of the scientific research efficiency of leading universities in the construction of“double first-class”from 2015 to 2016 by DEA model.The results show that the efficiency of high-quality scientific research of leading universities before and after the implementation of the“double First-class”construction has a small improvement range,and most of the universities are still at the invalid level despite an upward trend,and there is a large room for improvement,indicating that the implementation results of the“double first-class”construction are initially effective,but there is still a lot of room for improvement.On this basis,some measures are put forward to improve the scientific research operation mechanism and innovation incentive system.
作者
徐子涵
李刚
XU Zihan;LI Gang(Finance Office,Shaanxi University of Technology,Hanzhong 723000,China;School of Economics and Management,Xi an University of Posts&Telecommunications,Xi an 710000,China)
出处
《科技与经济》
2022年第6期66-70,共5页
Science & Technology and Economy
基金
陕西省软科学研究项目——“互联网+背景下陕西省制造企业绿色竞争力发展策略”(项目编号:2019KRM162,项目负责人:李刚)成果之一
陕西省软科学研究项目——“媒体融合背景下陕西省党媒商业模式转型及引导力提升策略研究”(项目编号2020KRM185,项目负责人:李刚)成果之一。
关键词
“双一流”建设
高质量科研效率
因子分析法
DEA模型
“double first-class”construction
efficiency of high quality scientific research
factor analysis
DEA model