Influential Nodes in the OBOR Fossil Energy Trade Network Based on D-S Theory: Detection and Evolution Analysis
The structure formed by fossil energy trade among countries can be divided into multiple subcommodity networks. However, the difference of coupling mode and transmission mechanism between layers of the multirelationship network will affect the measurement of node importance. In this paper, a framewo...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2022/9557722 |
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| author | Cuixia Gao Simin Tao Kehu Li Yuyang He |
| author_facet | Cuixia Gao Simin Tao Kehu Li Yuyang He |
| author_sort | Cuixia Gao |
| collection | DOAJ |
| description | The structure formed by fossil energy trade among countries can be divided into multiple subcommodity networks. However, the difference of coupling mode and transmission mechanism between layers of the multirelationship network will affect the measurement of node importance. In this paper, a framework of multisource information fusion by considering data uncertainty and the classical network centrality measures is build. Then, the evidential centrality (EVC) indicator is proposed, by integrating Dempster–Shafer evidence theory and network theory, to empirically identify influential nodes of fossil energy trade along the Belt and Road Initiative. The initial result of the heterogeneity characteristics of the constructed network drives us to explore the core node issue further. The main detected evidential nodes include Russia, Kazakhstan, Czechia, Slovakia, Egypt, Romania, China, Saudi Arabia, and Singapore, which also have higher impact on network efficiency. In addition, cluster analysis discovered that resource endowment is an essential factor influencing country’s position, followed by geographical distance, economic level, and economic growth potential. Therefore, the above aspects should be considered when ensuring national trade security. At last, the rationality and comprehensiveness of EVC are verified by comparing with some benchmark centralities. |
| format | Article |
| id | doaj-art-09248c4fc5e844659451de1f6d2fd186 |
| institution | Kabale University |
| issn | 1099-0526 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-09248c4fc5e844659451de1f6d2fd1862025-02-03T06:05:31ZengWileyComplexity1099-05262022-01-01202210.1155/2022/9557722Influential Nodes in the OBOR Fossil Energy Trade Network Based on D-S Theory: Detection and Evolution AnalysisCuixia Gao0Simin Tao1Kehu Li2Yuyang He3School of Environmental Science and EngineeringSchool of Mathematical SciencesSchool of Mathematical SciencesSchool of Mechanical EngineeringThe structure formed by fossil energy trade among countries can be divided into multiple subcommodity networks. However, the difference of coupling mode and transmission mechanism between layers of the multirelationship network will affect the measurement of node importance. In this paper, a framework of multisource information fusion by considering data uncertainty and the classical network centrality measures is build. Then, the evidential centrality (EVC) indicator is proposed, by integrating Dempster–Shafer evidence theory and network theory, to empirically identify influential nodes of fossil energy trade along the Belt and Road Initiative. The initial result of the heterogeneity characteristics of the constructed network drives us to explore the core node issue further. The main detected evidential nodes include Russia, Kazakhstan, Czechia, Slovakia, Egypt, Romania, China, Saudi Arabia, and Singapore, which also have higher impact on network efficiency. In addition, cluster analysis discovered that resource endowment is an essential factor influencing country’s position, followed by geographical distance, economic level, and economic growth potential. Therefore, the above aspects should be considered when ensuring national trade security. At last, the rationality and comprehensiveness of EVC are verified by comparing with some benchmark centralities.http://dx.doi.org/10.1155/2022/9557722 |
| spellingShingle | Cuixia Gao Simin Tao Kehu Li Yuyang He Influential Nodes in the OBOR Fossil Energy Trade Network Based on D-S Theory: Detection and Evolution Analysis Complexity |
| title | Influential Nodes in the OBOR Fossil Energy Trade Network Based on D-S Theory: Detection and Evolution Analysis |
| title_full | Influential Nodes in the OBOR Fossil Energy Trade Network Based on D-S Theory: Detection and Evolution Analysis |
| title_fullStr | Influential Nodes in the OBOR Fossil Energy Trade Network Based on D-S Theory: Detection and Evolution Analysis |
| title_full_unstemmed | Influential Nodes in the OBOR Fossil Energy Trade Network Based on D-S Theory: Detection and Evolution Analysis |
| title_short | Influential Nodes in the OBOR Fossil Energy Trade Network Based on D-S Theory: Detection and Evolution Analysis |
| title_sort | influential nodes in the obor fossil energy trade network based on d s theory detection and evolution analysis |
| url | http://dx.doi.org/10.1155/2022/9557722 |
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