Assessing the Static and Dynamic Efficiency of Scientific Research of HEIs China: Three Stage DEA–Malmquist Index Approach

Abstract

Higher education institutions (HEIs) are the key to the economic and social development of a country. However, the recent advancements of higher education institutions’ universities in China have become a pivotal factor contributing to their swift growth. Considering the impact of the external environment, applying a three-stage data-envelopment analysis (DEA) and the Malmquist index method, we evaluated the static and dynamic efficiency of input–output data of scientific research produced by universities directly under the Ministry of Education in the period of 2010 to 2017. Results showed that the three stage DEA model is more accurate than the traditional DEA method for measuring the efficiency of scientific research input and universities’ output. The overall efficiency of universities’ scientific research activities increased at an average annual rate of 3.7% from 2010 to 2017. Further analysis showed that the optimization of the scale was the primary internal factor able to promote the efficiency of scientific research in universities. Technological progress slightly diminishes the efficiency of scientific research in universities, which should, therefore, take measures to improve pure technical efficiency to enlarge the scale of their scientific research according to the characteristics of scientific research efficiency. Such steps will strengthen internal motivation towards scientific research efficiency in universities.

Research on the Transformation Efficiency of Scientific and Technological Achievements of Minis-try-affiliated Universities Based on Network DEA

“…Since the transformation of scientific and technological achievements in universities is a complex process involving multiple indicators and stages, the stochastic frontier method is difficult to solve these difficult problems, so the non-parametric method represented by DEA has been widely used in the study of the efficiency of scientific and technological innovation in universities. For example, Xue Wuzhao et al used three-stage DEA and Malmquist index methods to evaluate static and dynamic efficiency of research input-output data of universities directly under the Ministry of Education from 2010-2017 [3]; Zhang Chonghui et al proposed a three-stage multicriteria decision making (MCDM) non-radial super-efficient data envelopment analysis with Bootstrapping [4]. Aleksandra Parteka et al studied the productivity change patterns of 266 public higher education institutions in European countries based on the Bootstrapped Malmquist index and concluded that there was a large national significance in productivity change [5].…”

Static and Dynamic Evaluation of Financing Efficiency in Enterprises’ Low-Carbon Supply Chain: PCA–DEA–Malmquist Model Method

“…When using the DEA-Malmquist index model to measure efficiency, we can not only attain the final result of efficiency level but also find out the cause of the low efficiency of the unit according to the analysis results. Finally, suggestions for optimization are put forward according to specific influencing factors [53][54][55]. Based on the above analysis, we adopted the PCA-DEA-Malmquist index model to comprehensively measure the financing efficiency of enterprises' low-carbon supply chain.…”

The contemporary value, basic framework and realization mechanism of the rule of law in rural revitalization

“…In 1982, Cave and other scholars measured the change of production efficiency for the first time by using the Malmquist index [28]. In 1994, Fare and other scholars improved this model, and by combining this model with the DEA method to construct the Malmquist index of total factor efficiency growth, which made the Malmquist index widely used [29]. The formula of the Malmquist index model is shown below.…”