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

Cun-Yang Xia | Zendy; Ze-Hui Yuan | Zendy; Wenyu He | Zendy; Ju-Hui Zhao | Zendy

Open Access

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

Author(s) -

Cun-Yang Xia,

Ze-Hui Yuan,

Wenyu He,

Ju-Hui Zhao

Publication year - 2021

Publication title -

education research international

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.29

H-Index - 5

eISSN - 2090-4002

pISSN - 2090-4010

DOI - 10.1155/2021/9699640

Subject(s) - china , index (typography) , productivity , construct (python library) , principal component analysis , malmquist index , entropy (arrow of time) , regional science , total factor productivity , econometrics , computer science , political science , mathematics , economics , geography , statistics , economic growth , physics , quantum mechanics , world wide web , law , programming language

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.

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