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An Empirical Study on Scientific Research Performance of Universities in Different Regions of China Based on PCA and Malmquist Index Method

Bibliographic Data

ID7759469
AuthorsCun-Yang Xia (0000-0002-8798-7957), Ze-Hui Yuan (0000-0003-2522-5284), Wen-Yu He (0000-0001-8263-0564), Wenyu He, Ju-Hui Zhao (0000-0002-4516-1209)
EditorsEhsan Namaziandost (0000-0002-8393-2537)
Year2021
Volume2021
Pages1-11
Publication date2021-08-12
Open AccessYes
TypeARTICLE
VenueEducation Research International (JOURNAL)
Journal identifiersISSN: 2090-4010 • E-ISSN: 2090-4002
PublisherWiley (PUBLISHER • GB)
DOI10.1155/2021/9699640
OpenAlexW3194650013
LanguageEN
Citations received4

This paper uses principal component analysis (PCA) and entropy method to construct the evaluation index system of the scientific research performance of universities in 31 provinces and cities in China. Based on the traditional DEA model, the development trend of the scientific research performance of the research objects from 2015 to 2019 is dynamically evaluated by the Malmquist index method. The results show that the scientific research performance of universities in various regions of China is not ideal, and the level of scientific research performance is declining. The total factor productivity of scientific research in the central and western regions is much higher than that in the eastern region. The main factor that hinders the improvement of scientific research performance is the efficiency of technological progress. Finally, aiming at the existing problems, some feasible suggestions are put forward to further improve the input-output efficiency of scientific research in universities

China · Construct (python library · Econometrics · Economic growth · Economics · Entropy (arrow of time · Geography · Index (typography · Malmquist index · Political science · Principal component analysis · Productivity · Regional science · Statistics · Total factor productivity · Advanced Technologies in Various Fields · Computer Science · Economic and Technological Innovation · Mathematics · scientometrics and bibliometrics research

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Citations per year1.33
Citation span2023 - 2025 (3)
Highly citedNo

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