Abstract

The aim of this study was to investigate the spatio-temporal characteristics of the industry–university research (IUR) collaboration efficiency of Chinese mainland colleges and universities, from 2008 to 2018. A comparative analysis method was used to analyze the data from the Statistical Yearbook of China’s Education Funds, the Compilation of Science and Technology Statistics of Colleges and Universities, and the China Statistical Yearbook. The principal components were extracted from relevant indicators of IUR capability in colleges and universities, with a principal component analysis (PCA) method. The principal component scores and comprehensive scores of 31 provinces in mainland China were calculated. The results showed that the efficiency of IUR collaboration in Chinese colleges and universities has increased rapidly within the 11 years studied. The efficiency in the eastern region has grown faster than that in the western region, and the gap between the southern region and the northern region has also continued to widen. The results also showed that the development of IUR collaboration efficiency of colleges and universities in mainland China is unbalanced. Scientific and technological funds, and scientific and technological manpower, were excessively concentrated in the southeast. Therefore, there is large room for improvement in the overall development of IUR collaboration in Chinese colleges and universities.

Highlights

  • With the rapid increase in the quantity and the quality of Chinese colleges and universities, the function of these higher education institutions has gradually developed from talent training to scientific research and social services

  • The results showed that the development of industry– university research (IUR) collaboration efficiency of colleges and universities in mainland

  • Principal component analysis (PCA) is a commonly used multivariate analysis method, which uses mathematical methods to reduce a large number of variables into fewer and mutually independent underlying factors that summarize the essential information contained in the variables [36], increasing the interpretability of the study results [37]

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Summary

Introduction

With the rapid increase in the quantity and the quality of Chinese colleges and universities, the function of these higher education institutions has gradually developed from talent training to scientific research and social services. The competitiveness of colleges and universities depends heavily on their IUR collaboration efficiency [1]. These higher education institutions have leading roles in the national innovation system, and are responsible for innovation and knowledge distribution [2]. Companies rely heavily on graduates and research sourced from colleges and universities. They take advantages of university knowledge bases and technologies to develop products and improve production processes, enhancing their competitiveness and profitability [3].

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