Assessing the research efficiency of Chinese higher education institutions by data envelopment analysis

Jiang, Jiali; Lee, Soo Kyoung; Rah, Min-joo

doi:10.1007/s12564-020-09634-0

Cited by 33 publications

(34 citation statements)

References 8 publications

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“…First of all, this paper explores the current situation of universities and research institutions in different provinces and their influencing factors. For example, Lu and Liu [15,16], Luo and Guo [17], Chen Jingyi and Zong [18], and Jiang et al [19] used DEA model to comprehensively evaluate the scientific research efficiency of universities directly under the Ministry of Education and found that there was a significant inconsistency between the comprehensive strength ranking and the scientific research efficiency ranking, and some universities with weaker strength were ahead of the universities with stronger strength in scientific research efficiency. Xu [20], Li et al [21], Shen and Zhao [22], and Liu Tianzuo [23] paid close attention to the scientific research efficiency and its influencing factors of 31 provinces and cities in China.…”

Section: Literature Reviewmentioning

confidence: 99%

Research on the Scientific Research Efficiency of Provincial Universities Based on the DEA Model

Wang

Tan

2021

Mobile Information Systems

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As the main factor of China’s higher education, effective evaluation of the scientific research efficiency of domestic universities is extremely significant to improve the scientific research management system of local universities, optimize the allocation of scientific research resources, and promote regional economic development. Based on the ten-year statistical data of the compilation of science and technology statistics of colleges and universities, this paper adopts the data envelopment analysis (DEA) model to study the scientific research efficiency of 31 provincial universities in Shandong Province from three dimensions: level, type, and region. The results show that, first, the overall scientific research efficiency of the sample universities is not high and takes on a downward trend; there are some differences, changes in the same direction, and level convergence in each dimension of scientific research efficiency. Second, there is a positive correlation between the comprehensive scientific research strength of the sample universities and the technical efficiency. Third, the level of regional economic development has a positive impact on the scale efficiency of scientific research, which is closely related to the technical efficiency, and there is no positive correlation between these two. Thus, the research suggests that, in the future, colleges and universities should formulate differentiated management policies, build a “Government University” two-level scientific research performance evaluation system guided by scientific research quality, change the concept of scientific research managers, and improve the ability of personnel to improve the efficiency of scientific research in colleges and universities.

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Section: Literature Reviewmentioning

confidence: 99%

Research on the Scientific Research Efficiency of Provincial Universities Based on the DEA Model

Wang

Tan

2021

Mobile Information Systems

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“…For example, the resources of scientific research personnel attracted by various schools and the financial resources invested by the state were uneven. Jiang (2020) discovered that only a few universities were considered to be highly efficient and innovative in digital R&D. Since schools without national key construction projects lack national financial support, the research efficiency was relatively low. In universities the leadership was not moving toward Dynamic operating logic.…”

Section: Analysis Of Resultsmentioning

confidence: 99%

Digitization Innovation in University Education

2022

Proceedings of the 16th International Conference on E-Learning (EL 2022)

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Covid-19 pandemic and post-pandemic had led to the confrontation of higher education system with enormous challenges. That necessitated the urgent transition from face-to-face -teaching to online -teaching. The change was an innovation in higher education. A comparative study of digital education based on the survey in 2020-2021 in seven different countries was conducted at Shanghai University. The study was based on grey comprehensive evaluation model. In general, developed countries had high comprehensive evaluation value, while Finland, United States of America, South-Korea and Latvia had relatively low grey correlation coefficient in several certain indicators, leading to a sharp drop in the overall score. Romania ranked last while China ranked second as a developing country as well. The study launched a conclusion that research and development personnel, infrastructure funds and university financial investment in digital education had relatively more obvious effects on improving the innovations and quality of higher education system including the leadership system of universities.

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“…For example, the resources of scientific research personnel attracted by various schools and the financial resources invested by the state are uneven. Jiang (2020) discovers that only a few universities are considered to be highly efficient in digital R&D. Since schools without national key construction projects lack national financial support, the research efficiency is relatively low. According to the analysis of China's grey correlation coefficient, it can be found that the statuses of scientific research, university construction investment as well as university financial investment are far below the optimal sequence.…”

Section: Analysis Of Resultsmentioning

confidence: 99%

The Digital Leap of E-Learning in Higher Education

Liu¹,

Tenhunen²,

Chen³

et al. 2021

Proceedings of the 15th International Conference on E-Learning (EL 2021)

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COVID-19 pandemic has led to the confrontation of higher education system with enormous challenges. This necessitated the urgent transition from face-to-face teaching to online teaching. A comparative study of digital education in seven different countries was conducted. This study established grey comprehensive evaluation model based on entropy weight method, which was successfully validated by reliability test. In general, developed countries tend to have high comprehensive evaluation value while Finland, South-Korea and Latvia have relatively low grey correlation coefficient in several certain indicators, leading to a sharp drop in the overall score. Romania ranked last while China ranked second as a developing country as well. This is followed by model optimization though input-output analysis method based on the upgrading of higher education system due to the pandemic's influence. The study launched a conclusion that research and development personnel, infrastructure funds and university financial investment in digital education have relatively more obvious effects on improving the quality of higher education system.

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Assessing the research efficiency of Chinese higher education institutions by data envelopment analysis

Cited by 33 publications

References 8 publications

Research on the Scientific Research Efficiency of Provincial Universities Based on the DEA Model

Research on the Scientific Research Efficiency of Provincial Universities Based on the DEA Model

Digitization Innovation in University Education

The Digital Leap of E-Learning in Higher Education

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