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By utilising policy reference network analysis and keyword timing analysis, this paper proposes a framework for measuring policy diffusion, which can delineate research focus, measurement indicators, and methods of science and technology policy diffusion from four dimensions: intensity, breadth, speed, and direction. Based on the framework, this paper collects and categorises China's policies on technology transfer and commercialisation from 1985 to 2017, and conducts quantitative research on the diffusion process and characteristics of those polices from the previously mentioned four dimensions, which enables us to investigate the diffusion law of knowledge, information, and experience among those policies. The paper can provide data support on the choice of policy type for subsequent specific policy formulation by exploring the characteristics of different types of policy diffusion. [ABSTRACT FROM AUTHOR]

Evaluating universities’ R&D performance can serve as a tool for policymakers, enabling them to identify the best R&D practitioners for benchmarking and develop strategies for enhancing performance by highlighting areas of weakness. This study divides universities’ R&D performance into two dimensions: efficiency and effectiveness. We employ a network data envelopment analysis approach to measure universities’ R&D efficiency, and separately use a multi-index comprehensive evaluation method to assess their R&D effectiveness from a multistage perspective. We calculate the comprehensive R&D performance of universities in 30 provinces in China from 2004 to 2014. An analysis of temporal variation reveals that universities’ R&D performance in some provinces improved rapidly, increasing gaps in performance as a whole. The spatial pattern for the 30 provinces shows that universities in provinces with medium or strong R&D performance are mainly in coastal provinces and central areas in China. Finally, universities’ R&D activities are considered ‘efficient and effective’ only in a small number of provinces, while in most provinces, these activities can generally be considered ‘less efficient and effective.’ Hence, universities in provinces with different R&D performance modes should implement targeted improvement strategies according to their characteristics. [ABSTRACT FROM AUTHOR]