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• W3165351460 abstract "Based on the provincial panel data of China from 2001 to 2016, this study uses the social network analysis approach to empirically investigate the characteristics and driving factors of the spatial association network of China’s interprovincial renewable energy technology innovation. The findings are as following. 1) The spatial association of China’s interprovincial renewable energy technology innovation exhibits a typical network structure. Moreover, its network density, network hierarchy and network efficiency are 0.3696, 0.6667 and 0.7833 in 2001 and 0.4084, 0.4764 and 0.7044 in 2016, respectively, implying the spatial association network became more and more complex and the interprovincial association strengthened during the sample period. 2) This spatial association network presents a “core-edge” distribution pattern. The positions and roles of various provinces vary greatly in the spatial association network. Specifically, the developed coastal regions such as Shanghai, Beijing and Tianjin have a degree centrality, closeness centrality and betweenness centrality of above 75, 80 and 10, respectively, indicating that they always play a central role in the network. However, the northeastern regions and the relatively backward central and western regions such as Heilongjiang, Jilin, Xinjiang, Hainan and Hebei only have a degree centrality, closeness centrality and betweenness centrality of below 20, 55 and 0.1, respectively, indicating that they are at a relatively marginal position. 3) The geographical proximity and the expansion of the differences in economic development level and R&amp;D inputs are conducive to the enhancement of the spatial association of China’s renewable energy technology innovation." @default.
• W3165351460 created "2021-06-07" @default.
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• W3165351460 date "2021-05-25" @default.
• W3165351460 modified "2023-10-18" @default.
• W3165351460 title "Characteristics and Driving Factors of Spatial Association Network of China’s Renewable Energy Technology Innovation" @default.
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• W3165351460 doi "https://doi.org/10.3389/fenrg.2021.686985" @default.
• W3165351460 hasPublicationYear "2021" @default.
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