1. Evaluation of university scientific research ability based on the output of sci-tech papers: A D-AHP approach
- Author
-
Fan Zong and Lifang Wang
- Subjects
Computer science ,Research Quality Assessment ,Social Sciences ,Analytic hierarchy process ,lcsh:Medicine ,02 engineering and technology ,Geographical Locations ,Governments ,Citation analysis ,Medicine and Health Sciences ,0202 electrical engineering, electronic engineering, information engineering ,Psychology ,lcsh:Science ,Multidisciplinary ,Management science ,Publications ,05 social sciences ,050301 education ,Research Assessment ,Built Structures ,Multiple-criteria decision analysis ,Preference ,Work (electrical) ,Behavioral Pharmacology ,Scientific method ,Physical Sciences ,Engineering and Technology ,020201 artificial intelligence & image processing ,Research Article ,China ,Asia ,Universities ,Psychometrics ,Structural Engineering ,Science ,Political Science ,Oceania ,Research and Analysis Methods ,Pharmacology ,Structure (mathematical logic) ,Models, Statistical ,Research ,lcsh:R ,Australia ,Biology and Life Sciences ,Algebra ,Linear Algebra ,People and Places ,lcsh:Q ,Eigenvectors ,0503 education ,Mathematics - Abstract
University scientific research ability is an important indicator to express the strength of universities. In this paper, the evaluation of university scientific research ability is investigated based on the output of sci-tech papers. Four university alliances from North America, UK, Australia, and China, are selected as the case study of the university scientific research evaluation. Data coming from Thomson Reuters InCites are collected to support the evaluation. The work has contributed new framework to the issue of university scientific research ability evaluation. At first, we have established a hierarchical structure to show the factors that impact the evaluation of university scientific research ability. Then, a new MCDM method called D-AHP model is used to implement the evaluation and ranking of different university alliances, in which a data-driven approach is proposed to automatically generate the D numbers preference relations. Next, a sensitivity analysis has been given to show the impact of weights of factors and sub-factors on the evaluation result. At last, the results obtained by using different methods are compared and discussed to verify the effectiveness and reasonability of this study, and some suggestions are given to promote China’s scientific research ability.
- Published
- 2017