A delay grey incidence analysis framework for assessing drivers and obstacles of R&D performance at Chinese universities

The purpose of this paper is to construct a novel delay grey incidence analysis model to analyze drivers and obstacles of university R&D performance.

With respect to the fact that university R&D activities typically experience two stages of knowledge creation and technology transfer, and different drivers and obstacles come into play to affect the conversion of R&D investment to outcomes at each stage, based on the thought of grey incidence analysis and the specific characteristics of science and technology (sci-tech) development, a novel delay grey incidence analysis model is proposed in this paper, and then according to the yearbook statistical data, Chinese university R&D activities are investigated and the drivers and obstacles of university R&D performance are analyzed.

The results show that the R&D full-time staff and R&D funds of basic research are the key drivers of influencing factors, and the sci-tech innovation talents in universities’ R&D institutions and experiment development funds are the restraining factors to improve R&D performance in the stage of knowledge creation; the expenses of R&D achievement application and technology service and the full-time staff of achievement application and technology service are the key drivers and obstacles of influencing the aggregate amount of patent sale respectively.

This research helps policy makers to reflect on their university R&D policies and understand how to enhance the technology transfer rate in China.

The paper succeeds in identifying key drivers and obstacles of affecting university R&D performance in China by examining the input and output incidence at both the knowledge creation and technology transfer stages.