|
|
|
| Research on the Relevance between Competitiveness and the Scientific Research Output of World-Class Universities |
| Zhang Weichong1, Meng Hao2, Wang Fang1 |
1. Nankai University, Tianjin 300071;
2. Institute of Scientific and Technical Information of China (ISTIC), Beijing 100038 |
|
|
|
|
Abstract Exploring the core elements characterizing the competitiveness of world-class universities and formulating the correct path to its improvement is of great significance for building a world-class university. This article examines the top 50 universities in the World University Rankings as samples. First, nine representative research output measurement indicators, X1-X9, were selected for statistical analysis, which included the four dimensions of productivity, influence, contribution, and level of internationalization. Second, X1-X9 were set as the independent variables and each university’s score in the QS/USNEWS/THE/ARWU university rankings was established as a dependent variable, Yi. The variable selection and parameter estimation experiments were carried out with four multiple linear regression models, Lasso/Ridge/LassoLars/BayesianRidge, and finally a well-fitting effect was obtained. The results reveal positive correlations between the impact factors of scientific research output, the total citation frequency, the number of cooperation organizations, and the annual average frequency of international cooperation with the competitiveness of world-class universities. However, results also showed that the number of papers per year, the growth rate of papers, the number of co-authors, the total annual frequency of institutional cooperation, and the frequency of cooperation between countries are not significantly related to the competitiveness of world-class universities.
|
|
Received: 26 September 2018
|
|
|
|
[1] 丁学良. 什么是世界一流大学[J]. 高等教育研究, 2001, 4(3): 4-9.
[2] 吕春燕, 孟浩, 何建坤. 研究型大学在国家自主创新体系中的作用分析[J]. 清华大学教育研究, 2005, 26(5): 1-7.
[3] 朱敬. 大学竞争力研究溯源及内涵演析[J]. 现代大学教育, 2008(1): 86-90.
[4] QS. QS world university rankings[EB/OL].[2018-6-8]. https://www. topuniversities.com/qs-world-university-rankings/methodology.
[5] USNews. How U.S. news calculated the best global universities rankings[EB/OL].[2018-6-8]. https://www.usnews.com/education/ best-global-universities/articles/methodology.
[6] THE. World university rankings 2016-2017 methodology[EB/OL]. [2018-6-8]. https://www.timeshighereducation.com/world-university- rankings/methodology-world-university-rankings-2016-2017.
[7] 上海软科. ARWU排名方法[EB/OL]. [2018-6-8]. http://www. zuihaodaxue.com/ARWU-Methodology-2017.html.
[8] Pouris A.Assessing scientific strengths of academic institutions: the example of the University of Pretoria[J]. South African Journal of Science, 2006, 102(1-2): 23-26.
[9] Campbell D, Picard-Aitken M, C Té G, et al. Bibliometrics as a performance measurement tool for research evaluation: The case of research funded by the National Cancer Institute of Canada[J]. American Journal of Evaluation, 2010, 31(1): 66-83.
[10] Abramo G, D’Angelo C A, Di Costa F. University-industry research collaboration: A model to assess university capability[J]. Higher Education, 2011, 62(2): 163-181.
[11] Siripitakchai N, Miyazaki K.Assessment of research strengths using co-citation analysis: The case of Thailand national research universities[J]. Research Evaluation, 2015, 24(4): 420-439.
[12] Pendlebury D A.Whitepaper using bibliometrics: A guide to evaluating research performance with citation data[R]. Thomson Reuters, 2008.
[13] 赵蓉英, 王嵩, 柴雯, 等. 2014-2015世界一流大学科研竞争力评价与结果分析[J]. 重庆大学学报(社会科学版), 2015, 21(1): 120-127.
[14] Liu W, Shi R F.Academic influence evaluation model for research institutes based on science network method: A case study[C]// Proceedings of the International Conference on Mechatronics, Electronic, Industrial and Control Engineering. Atlantis Press, 2014: 100-104.
[15] de Beaver D B, Rosen R. Studies in scientific collaboration - Part I. The professional origins of scientific co-authorship[J]. Scientometrics, 1978, 1(1): 65-84.
[16] 崔鹤, 王丹. 中国高等教育研究领域个体?机构及地域科研合作情况研究——基于2016年18家教育类中文核心期刊的合著文献分析[J]. 中国高教研究, 2017(4): 48-55.
[17] 刘利, 宋歌, 袁曦临, 等. 论文合著视角下的科研机构合作网络测度分析——以我国电信学科为例[J]. 现代情报, 2014, 34(1): 94-99.
[18] 何汶, 刘颖, 杨红梅. 图书情报学高被引论文国际合著及贡献研究——基于文献计量学角度[J]. 图书情报知识, 2017(2): 83-93.
[19] 邱均平, 欧玉芳. 面向世界一流大学建设的"985工程"高校科研竞争力评价分析——基于"十二五"期间RCCSE世界一流大学及学科竞争力评价报告[J]. 中国高教研究, 2016(4): 57-63.
[20] 顾东蕾, 张静, 刘旭明. 基于JCR和InciteTM中国大陆期刊的学科影响力研究[J]. 情报杂志, 2016, 35(8): 107-113.
[21] Abdi H, Williams L J.Principal component analysis[J]. Wiley Interdisciplinary Reviews: Computational Statistics, 2010, 2(4): 433-459.
[22] Tibshirani R.Regression shrinkage and selection via the lasso: a retrospective[J]. Journal of the Royal Statistical Society: Series B Statistical Methodology, 2011, 73(3): 273-282.
[23] 贾元乔. 基于lasso的两级变量选择方法[D]. 杭州: 浙江大学, 2013.
[24] Efron B, Hastie T, Johnstone I, et al.Least angle regression[J]. Annals of Statistics, 2004, 32(2): 407-451.
[25] 周雁舟, 乔辉, 吴晓萍, 等. 基于LASSO-LARS的软件复杂性度量属性特征选择研究[J]. 计算机科学, 2013, 40(11): 169-173.
[26] Scikit-learn. Generalized linear model: Bayesian regression [EB/OL]. [2018-06-10]. http://scikit-learn.org/stable/supervised_ learning.html#supervised-learning.
[27] Efendi A, Effrihan. A simulation study on Bayesian Ridge regression models for several collinearity levels[C]// Proceedings of the International Conference and Workshop on Mathematical Analysis and ITS Applications, 2017. |
|
|
|
