Educational Sciences: Theory & Practice

ISSN: 2630-5984

Empirical Study of the Knowledge Innovation Efficiency of Universities in Different Regions of China: Panel Data Analysis Based on mSBM.

Xuefeng Li
School of Public Affairs, Chongqing University, Chongqing 400044, China.
Zhi Li
School of Public Affairs, Chongqing University, Chongqing 400044, China.
Guangming Yang
School of Management, Chongqing University of Technology, Chongqing 400054, China.
Dalai Ma
School of Management, Chongqing University of Technology, Chongqing 400054, China

Abstract

In this paper, the method of minimum distance to the strong frontier is adopted to research the knowledge innovation efficiency of universities in 30 provinces of China during 2005-2015. The greatest strength of this method is that, to a decision-making unit under estimation, improvements in input or output are minimized to reach the cutting edge of production. According to research findings, a significant difference exists in the knowledge innovation efficiency of universities among provinces in China. Provinces with a high efficiency are mostly distributed in the eastern coastal region and provinces with a low efficiency in the hinterland of central and western regions. Judging from region, the efficiency in the eastern region is the highest; the efficiency in the central region is the second highest; the efficiency in the western region is the lowest. Judging from contribution to inefficiency, the contribution to inefficiency made by Human input, Capital input, and technology service declines but the contribution to inefficiency made by paper output and achievement assessment improves. While China practice the plan of revitalizing education, it will focus on the following 5 provinces: Guangxi, Inner Mongolia, Guizhou, Gansu, Qinghai. In addition, in the long run, the gap between different provinces has a tendency to be narrowed in the knowledge innovation efficiency of universities.

Keywords
Knowledge Innovation Efficiency of Universities, mSBM Model, Cluster Analysis, Kernel Density Analysis.