Sustainable Evaluation of Social Science Research in Higher Education Institutions Based on Data Envelopment Analysis

Abstract

This paper divides the typical social scientific research process into two stages: the research development stage and the research innovation stage, with personnel as a shared input between them. We construct an input-shared multi-period two-stage DEA (data envelopment analysis) model as measurement of sustainability capacities of social scientific research, and then measure both the overall efficiencies and the stage efficiencies of scientific research of 18 HEIs (higher education institutions) in Jiangsu province of China from 2010 to 2014. There are some revelatory traits among the overall efficiencies and stage efficiencies of HEIs. As for the HEIs, the efficiencies of the first stage of certain HEIs that are better in social science are higher than those which have advantage in natural science. The results are the opposite in the second stage. Additionally, in virtue of common-weight global MPI (Malmquist Productivity Index), we figure out the dynamic efficiencies within and between HEIs. Finally, we appeal to administration departments to establish academic sharing systems and construct interdisciplinary ecosystems among HEIs, which aims to pool the knowledge, experience, and capacities of the region's academic actors and improve the sustainable development and innovation abilities of social scientific research. In addition, collaborating with industrial organizations is also a strategic avenue to improve their research abilities, which can push the boundaries of sustainable development and also bring vigor in social scientific research.

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

“…Higher education institutions are the primary sources to produce high-level innovative talents and the main reference to solve scientific and technological issues, and enhance research outputs. Moreover, higher institutions' universities' initiatives towards scientific research activities are essential to expand social and pure science research scope and catalyze social and economic development [14]. Therefore, considering this study motivates Author Contributions: Conceptualization, W.X.…”

“…Ref. [14] conducted a study based on 18 higher education institutions and measured overall efficiency into two divisions. The research development stage and research innovation stage presented that HEIs with social science research are better and proposed to establish an academic sharing system, which eventually pools the experience, knowledge, and capacities of the academic profession within and between regions.…”

A Fuzzy Comprehensive Evaluation Method on the Construction of High-Level Universities Based on Data from Jiangsu Province

“…In constructing high-level universities in Jiangsu, scientific research has gradually developed into a function that distinguishes universities from daily teaching [26,27]. In this context, a scientific teacher-student ratio can provide solid faculty support for students [28].…”

Sustainability in Chinese Higher Educational Institutions’ Social Science Research: A Performance Interface toward Efficiency

“…In the foundation stage, the inputs-staff, expenditure, and equipment-are applied to produce intermediate products [35], i.e., the newly approved projects and the completed projects for the year. These intermediate products are the critical elements that the HEIs' research relies on in order to produce the final outputs, i.e., published works, published papers and research, and consulting reports [15,36].…”

“…Meanwhile, the research equipment is shared by many production activities and hardly allotted at a reasonable use rate in terms of different activities, so we remove this variable. In view of the research and consulting reports having a certain phase-out rate in the process of application, this paper converts it with a utilization rate [36]. In addition, the weight coefficients of the published works are almost all equal to zero when we initially compute the model with those variables, which shows that the published works as composite achievements make no difference to the simulation results, so we delete this variable in the following section.…”