Measuring scientific productivity in China using malmquist productivity index
(2019) In Journal of Data and Information Science 4(1). p.32-59- Abstract
This paper aims to investigate the scientific productivity of China's science system. This paper employs the Malmquist productivity index (MPI) based on Data Envelopment Analysis (DEA). The results reveal that the overall efficiency of Chinese universities increased significantly from 2009 to 2016, which is mainly driven by technological progress. From the perspective of the functions of higher education, research and transfer activities perform better than the teaching activities. As an implication, the indicator selection mechanism, investigation period and the MPI model can be further extended in the future research. The results indicate that Chinese education administrative departments should take actions to guide and promote the... (More)
This paper aims to investigate the scientific productivity of China's science system. This paper employs the Malmquist productivity index (MPI) based on Data Envelopment Analysis (DEA). The results reveal that the overall efficiency of Chinese universities increased significantly from 2009 to 2016, which is mainly driven by technological progress. From the perspective of the functions of higher education, research and transfer activities perform better than the teaching activities. As an implication, the indicator selection mechanism, investigation period and the MPI model can be further extended in the future research. The results indicate that Chinese education administrative departments should take actions to guide and promote the teaching activities and formulate reasonable resource allocation regulations to reach the balanced development in Chinese universities. This paper selects 58 Chinese universities and conducts a quantified measurement during the period 2009-2016. Three main functional activities of universities (i.e. teaching, researching, and application) are innovatively categorized into different schemes, and we calculate their performance, respectively.
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- author
- Song, Yaoyao ; Schubert, Torben LU ; Liu, Huihui and Yang, Guoliang
- organization
- publishing date
- 2019
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Analysis (DEA), Chinese higher education, Data Envelopment, Malmquist Productivity Index (MPI), Scientific productivity
- in
- Journal of Data and Information Science
- volume
- 4
- issue
- 1
- pages
- 28 pages
- publisher
- De Gruyter Open
- external identifiers
-
- scopus:85062526021
- ISSN
- 2543-683X
- DOI
- 10.2478/jdis-2019-0003
- language
- English
- LU publication?
- yes
- id
- 6be0c12e-0d04-40bb-80e8-b1fb52381be9
- date added to LUP
- 2019-03-18 14:35:00
- date last changed
- 2024-01-15 16:11:52
@article{6be0c12e-0d04-40bb-80e8-b1fb52381be9,
abstract = {{<p>This paper aims to investigate the scientific productivity of China's science system. This paper employs the Malmquist productivity index (MPI) based on Data Envelopment Analysis (DEA). The results reveal that the overall efficiency of Chinese universities increased significantly from 2009 to 2016, which is mainly driven by technological progress. From the perspective of the functions of higher education, research and transfer activities perform better than the teaching activities. As an implication, the indicator selection mechanism, investigation period and the MPI model can be further extended in the future research. The results indicate that Chinese education administrative departments should take actions to guide and promote the teaching activities and formulate reasonable resource allocation regulations to reach the balanced development in Chinese universities. This paper selects 58 Chinese universities and conducts a quantified measurement during the period 2009-2016. Three main functional activities of universities (i.e. teaching, researching, and application) are innovatively categorized into different schemes, and we calculate their performance, respectively.</p>}},
author = {{Song, Yaoyao and Schubert, Torben and Liu, Huihui and Yang, Guoliang}},
issn = {{2543-683X}},
keywords = {{Analysis (DEA); Chinese higher education; Data Envelopment; Malmquist Productivity Index (MPI); Scientific productivity}},
language = {{eng}},
number = {{1}},
pages = {{32--59}},
publisher = {{De Gruyter Open}},
series = {{Journal of Data and Information Science}},
title = {{Measuring scientific productivity in China using malmquist productivity index}},
url = {{http://dx.doi.org/10.2478/jdis-2019-0003}},
doi = {{10.2478/jdis-2019-0003}},
volume = {{4}},
year = {{2019}},
}