Characteristics and Driving Factors of Spatial Association Network of China's Renewable Energy Technology Innovation

被引:10
|
作者
Feng, Chen [1 ]
Wang, Yuansheng [2 ]
Kang, Rong [3 ]
Zhou, Lei [4 ]
Bai, Caiquan [4 ]
Yan, Zheming [5 ]
机构
[1] Shanghai Univ Finance & Econ, Sch Publ Econ & Adm, Shanghai, Peoples R China
[2] Nankai Univ, Sch Finance, Tianjin, Peoples R China
[3] Northwest Univ, Sch Econ & Management, Xian, Peoples R China
[4] Shandong Univ, Ctr Econ Res, Jinan, Peoples R China
[5] Xi An Jiao Tong Univ, Sch Econ & Finance, Xian, Peoples R China
来源
FRONTIERS IN ENERGY RESEARCH | 2021年 / 9卷 / 09期
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
renewable energy technology innovation; spatial association; driving factor; social network analysis; China; RESEARCH-AND-DEVELOPMENT; CARBON EMISSIONS; KNOWLEDGE NETWORKS; TEMPORAL EVOLUTION; EMPIRICAL-EVIDENCE; ECONOMIC-GROWTH; CO2; EMISSIONS; PANEL; POWER; CONSUMPTION;
D O I
10.3389/fenrg.2021.686985
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
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&D inputs are conducive to the enhancement of the spatial association of China's renewable energy technology innovation.
引用
收藏
页数:14
相关论文
共 50 条
  • [41] Impacts of FDI Renewable Energy Technology Spillover on China's Energy Industry Performance
    Liu, Weiwei
    Xu, Xiandong
    Yang, Zhile
    Zhao, Jianyu
    Xing, Jing
    SUSTAINABILITY, 2016, 8 (09)
  • [42] Driving factors of carbon emissions in China's municipalities: a LMDI approach
    Liu, Yuanxin
    Jiang, Yajing
    Liu, Hui
    Li, Bo
    Yuan, Jiahai
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2022, 29 (15) : 21789 - 21802
  • [43] The role of technology innovation and renewable energy in reducing environmental degradation in Malaysia: A step towards sustainable environment
    Suki, Norazah Mohd
    Suki, Norbayah Mohd
    Sharif, Arshian
    Afshan, Sahar
    Jermsittiparsert, Kittisak
    RENEWABLE ENERGY, 2022, 182 : 245 - 253
  • [44] Trends and driving forces of low-carbon energy technology innovation in China's industrial sectors from 1998 to 2017: from a regional perspective
    Zhang, Xi
    Geng, Yong
    Tong, Yen Wah
    Kua, Harn Wei
    Dong, Huijuan
    Pan, Hengyu
    FRONTIERS IN ENERGY, 2021, 15 (02) : 473 - 486
  • [45] Analyzing the regional inequality of renewable energy consumption and its driving factors: Evidence from China
    Li, Menghan
    Liu, Xiaoxiao
    Yang, Mian
    RENEWABLE ENERGY, 2024, 223
  • [46] The impact of ecological environment pressure on renewable energy technology innovation: evidence from China's Yangtze River Economic Belt
    Yin, Shanggang
    Zhou, Junjie
    Zhou, Yijing
    Xiao, Weiwei
    Bai, Caiquan
    ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, 2024,
  • [47] Analysis of the generation efficiency of disaggregated renewable energy and its spatial heterogeneity influencing factors: A case study of China
    Yu, Bolin
    Fang, Debin
    Meng, Jingxuan
    ENERGY, 2021, 234
  • [48] Spatial distribution of China's renewable energy industry: Regional features and implications for a harmonious development future
    Dong, Liang
    Liang, Hanwei
    Gao, Zhiqiu
    Luo, Xiao
    Ren, Jingzheng
    RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2016, 58 : 1521 - 1531
  • [49] The Driving Factors of Carbon Emissions in China's Transportation Sector: A Spatial Analysis
    Xu, Xingbo
    Xu, Haicheng
    FRONTIERS IN ENERGY RESEARCH, 2021, 9
  • [50] Renewable Energy Green Innovation, Fossil Energy Consumption, and Air Pollution-Spatial Empirical Analysis Based on China
    Shen, Neng
    Wang, Yifan
    Peng, Hui
    Hou, Zhiping
    SUSTAINABILITY, 2020, 12 (16)