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The Spatial Analysis of Regional Innovation Performance and Industry-University-Research Institution Collaborative Innovation—An Empirical Study of Chinese Provincial Data

Xu Wang (), Hong Fang (), Fang Zhang () and Siran Fang ()
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Xu Wang: School of Economics and Management, Beihang University, Beijing 100191, China
Hong Fang: School of Economics and Management, Beihang University, Beijing 100191, China
Fang Zhang: School of Economics and Management, Beihang University, Beijing 100191, China
Siran Fang: School of Engineering, Nanjing Agricultural University, Nanjing 210031, China

Sustainability, 2018, vol. 10, issue 4, 1-16

Abstract: Previous studies have pointed out that Industry-University-Research Institution (IUR) collaborative innovation is an important means to ensure the sustainable development of regional innovation, and there may be spillover effects among different regional innovation systems. However, the impact of regional spatial correlation and IUR collaborative innovation synergy degree on regional innovation performance is not that clear. Based on the panel data of 31 regions in China from 2006 to 2015, we construct static and dynamic spatial econometrics models to analysis the relationships among regional innovation performance, IUR collaborative innovation and spatial correlation. The research results show that there are significant positive spillover effects among different regions, indicating that the dynamic flows of innovation elements among regions is conducive to improve the regional innovation performance. In addition, IUR collaboration innovation also has a positive impact on regional innovation performance: the current period of IUR synergy degree has a negative impact, while the lagged one has a positive impact. It means that it will take a while for IUR collaborative innovation to be effective and it will have far-reaching contributions to long-term improvements rather than short-term benefits in social development. The results are significant for both static and dynamic spatial econometrics models. The conclusions of this paper have important policy significance to fully understand the coordination of innovative elements and promote the sustainable development of regional innovation systems.

Keywords: IUR collaborative innovation; regional innovation performance; spatial econometrics model; sustainable development (search for similar items in EconPapers)
JEL-codes: Q Q0 Q2 Q3 Q5 Q56 O13 (search for similar items in EconPapers)
Date: 2018
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