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- Publisher Website: 10.1016/j.apenergy.2017.05.082
- Scopus: eid_2-s2.0-85020001941
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Article: Who are leading the change? The impact of China's leading PV enterprises: A complex network analysis
Title | Who are leading the change? The impact of China's leading PV enterprises: A complex network analysis |
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Authors | |
Keywords | Conduction effect Diffusion effect Inherent influence ability Leading PV enterprises Partial correlation coefficient |
Issue Date | 2017 |
Citation | Applied Energy, 2017, v. 207, p. 477-493 How to Cite? |
Abstract | In this paper, China's PV market is studied from a new perspective of complex network theory. An influence index threshold network (IITN) model is been built by using partial correlation coefficients. Complex network theory is then used to provide a detailed description of the interactions of enterprises, their inherent influencing ability to conduct and control the interactions of the enterprise in the PV industry. This paper also analyses the diffusion effect of the inherent influencing ability and the conduction effect of the relationship of the enterprise in the PV industry. In addition, the leading enterprises in the industrial chain are been identified using their degree, degree centrality, betweenness and net profit ranking. The results show that the average betweenness of the top enterprises is contrary to the evolution of new installed PV capacity globally. Finally, the reasons for identifying leading enterprises are stated in detail and policy suggestions are made to promote the sustainable development of the World's PV market. |
Persistent Identifier | http://hdl.handle.net/10722/333276 |
ISSN | 2023 Impact Factor: 10.1 2023 SCImago Journal Rankings: 2.820 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Zhang, Peipei | - |
dc.contributor.author | Sun, Mei | - |
dc.contributor.author | Zhang, Xiaoling | - |
dc.contributor.author | Gao, Cuixia | - |
dc.date.accessioned | 2023-10-06T05:18:05Z | - |
dc.date.available | 2023-10-06T05:18:05Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Applied Energy, 2017, v. 207, p. 477-493 | - |
dc.identifier.issn | 0306-2619 | - |
dc.identifier.uri | http://hdl.handle.net/10722/333276 | - |
dc.description.abstract | In this paper, China's PV market is studied from a new perspective of complex network theory. An influence index threshold network (IITN) model is been built by using partial correlation coefficients. Complex network theory is then used to provide a detailed description of the interactions of enterprises, their inherent influencing ability to conduct and control the interactions of the enterprise in the PV industry. This paper also analyses the diffusion effect of the inherent influencing ability and the conduction effect of the relationship of the enterprise in the PV industry. In addition, the leading enterprises in the industrial chain are been identified using their degree, degree centrality, betweenness and net profit ranking. The results show that the average betweenness of the top enterprises is contrary to the evolution of new installed PV capacity globally. Finally, the reasons for identifying leading enterprises are stated in detail and policy suggestions are made to promote the sustainable development of the World's PV market. | - |
dc.language | eng | - |
dc.relation.ispartof | Applied Energy | - |
dc.subject | Conduction effect | - |
dc.subject | Diffusion effect | - |
dc.subject | Inherent influence ability | - |
dc.subject | Leading PV enterprises | - |
dc.subject | Partial correlation coefficient | - |
dc.title | Who are leading the change? The impact of China's leading PV enterprises: A complex network analysis | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1016/j.apenergy.2017.05.082 | - |
dc.identifier.scopus | eid_2-s2.0-85020001941 | - |
dc.identifier.volume | 207 | - |
dc.identifier.spage | 477 | - |
dc.identifier.epage | 493 | - |
dc.identifier.isi | WOS:000417229300042 | - |