多方法融合视角下的中国最好大学评估检验  

The Evaluation and Verification of the Best Chinese Universities Based on the Combinatorial Analysis of Multi-Methods

作　　者：胡泽文 曹玲 尹献 Hu Zewen;Cao Ling;Yin Xian(School of Management Science and Engineering,Nanjing University of Information Science &Technology,Nanjing 210044,China)

机构地区：[1]南京信息工程大学管理工程学院,江苏南京210044

出　　处：《现代情报》2021年第6期149-160,共12页Journal of Modern Information

基　　金：国家社会科学基金项目“面向海量科技文献的潜在‘精品’识别方法与应用研究”(项目编号:20CTQ031);江苏省高等教育教改研究立项课题“大数据驱动的信息管理与信息系统品牌专业建设探索与实践研究”(项目编号:2019JSJG299)。

摘　　要：[目的/意义]高校评估指标设置和权重测量分配等环节出现的主观性因素,使得不同评估报告中的高校排名结果之间存在一定差异。[方法/过程]为此,笔者融合面板数据模型和层次分析模型构建一个测度指标权重的全定量测度模型,并设计和实现融合新型指标测度模型的改进型TOPSIS模型和灰色关联模型,评估分析了2017年中国最好大学排名的TOP100高校,并与TOPSIS模型、融合熵值法权重的改进TOPSIS模型等传统定量评估方法的评估结果进行比较。[结果/结论]融合面板数据模型和层次分析模型权重的新型评估方法具有较好的评估效果,与中国最好大学排名结果之间保持较高的一致性;高校排名结果会受到指标权重和评估方法的影响,不同评估方法评估出的高校最高最低名次差值的平均值相对较高,为10.84。[Purpose/Significance]The subjectivity in the process from the setting of evaluation indicators to the distribution of weights has always affected the evaluation of universities and also affected the ranking results.[Method/Process]This paper designed a new measurement model of indicator weights based on the panel data model and analytic hierarchy process model,and implements the two improved evaluation model including TOPSIS model and gray correlation model based on our proposed new measurement model of indicator weights.Then this paper utilized two improved TOPSIS model and gray correlation model to evaluate and compare the differences among the ranking results from the 2017 Best Chinese Universities Ranking and from two traditional evaluation model including the TOPSIS model and TOPSIS model based on the entropy weights.[Result/Conclusion]As a result,it is found that the evaluation model of universities based on our proposed new measurement model of indicator weights was of the better effect of evaluation,and keep the higher coincidence degree with the 2017 Best Chinese Universities Ranking results.However,the ranking results of universities were easily influenced by the differences of indicator weights and evaluation methods that can be reflected by the high average value of the difference between the minimum and maximum values of each university obtained by different kinds of ranking methods.

关 键 词：高校评估 大学排名 评价指标 TOPSIS模型 面板数据模型 层次分析模型 灰色关联模型 

分 类 号：G250.252[文化科学—图书馆学]