摘要
目的 对某医学高校省级重点学科科研绩效进行探索性评价,为研究学科评价相关课题提供依据.方法 本文选取某医学高校29个省级重点学科作为评价系统,用数据包络分析(DEA)法评价其科研绩效水平,同时运用TOPSIS法和灰色关联分析法对其科研效率进行排序,并对三种方法所得出的结果进行统计学相关性分析.结果 数据包络分析法的评价结果:DEA有效单元18个,非DEA有效单元11个,其中8个学科需要减少资源投入,3个学科需要增加科研产出;TOP-SIS法和灰色关联分析法对29个重点学科的排序结果与之呈显著的正相关关系,三者间的相关系数分别为rs1=0.797(P =0.000);rs2=0.583(P =0.007);rs3=0.536(P =0.003).结论 相较于TOPSIS法和灰色关联分析法,数据包络分析模型不仅能评价学科的办学效益水平,而且能够对非技术有效的学科提供改进依据.
Objective This article was aimed to take exploratory evaluation on the scientific research performance of provincial key disciplines in a medical university,and to provide a scientific basis for the discipline evaluation related topics.Methods This paper took 29 provincial key disciplines in a medical university as the evaluation system.We calculated the scientific research performance of key disciplines.Data envelopment analysis (DEA) method was used to evaluate the scientific level of performance,while the use of TOPSIS and gray correlation analysis method to rank the efficiency of its research,and the results obtained by the three methods was used for statistical correlation analysis.Results According to the results calculated by DEA Method,there were 18 DEA efficient units and 11 non-DEA efficient units.While in this 11 non-DEA efficient units,8 of them needed to reduce re source inputs and the other 3 units needed to increase research outputs.Meanwhile there were significant positive correlations between evaluation results of TOPSIS Method andGrey Correlation Analysis Method with Data Envelopment Analysis Method,respectively [the correlation coefficient:rs 1 =0.797(P =0.000); rs 2=0.583(P =0.007); rs 3-0.536(P =0.003)].Conclusions Compared to TOPSIS Method and Grey Correlation Analysis Method,DEA Method not only could evaluate the ef fectiveness of discipline,but also provide evidence to improve the non-DEA efficient units.
出处
《中华医学科研管理杂志》
2015年第1期80-84,共5页
Chinese Journal of Medical Science Research Management
关键词
重点学科
科研绩效
数据包络分析
综合评价
Key disciplines
Scientific Research Performance
Data Envelopment Analysis Method
Comprehensive Evaluation