Spatio-temporal evolution of green innovation network and its multidimensional proximity analysis: Empirical evidence from China

The increase in green innovation provincial output comes from both green innovation activities and green innovation inter-provincial spillovers. In this study, the green innovation developments in China from 2007 to 2017 were divided into forming, boom and stable periods based on the green patent grants, after which an improved gravity model was employed to determine the provincial green innovation correlations. Finally, the green innovation network (GIN) evolution and the influence of the multidimensional proximities on its formation were analyzed using social network analysis (SNA) and a quadratic distribution program (QAP). It was found that: the green innovation developments across the provinces were increasingly closely related and had obvious spatial correlations and spillover effects, and most of the more developed eastern provinces, and especially those in the Yangtze river delta, the Pearl river delta and the Bohai rim regions, had strong abilities to absorb and control the green innovation resources. The geographical, cognitive, institutional and technological proximities were all found to contribute to the GIN formation, with the geographical proximity having a positive moderating effect between the non-geographical proximities and the interprovincial green innovation correlations, and both technological proximity and geographical proximity playing a critical role in the current stable period of green technology development. Therefore, it was concluded that: the provinces be given “one-to-one” support; differentiated development policies be developed based on local conditions; transportation infrastructure construction and talent education be strengthened in less developed provinces; and environmental regulation policies be implemented in accordance with local provincial conditions. •The research on innovation network has been extended from certain industry to the regional green innovation network (GIN).•The dynamic changes of GIN in different periods were revealed by social network analysis.•Multidimensional proximities and their interactions were considered as the influencing factors for the formation of GIN.•The geographical proximity between regions was creatively measured by the opening time of high-speed rail.