Analysis of Global Trade Competition Pattern of New Energy Vehicles and Fuel Vehicles based on Multi-Layer Network
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| Format: | Recurso digital |
| Language: | English |
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Zenodo
2025
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| _version_ | 1866901591256203264 |
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| author | QiYu Hu |
| author_facet | QiYu Hu |
| contents | <p><strong><span>Abstract</span></strong><strong><span>—</span></strong><span> </span><span>Use the 2023 global trade export data of new energy vehicles and fuel vehicles to build a multi-layer network of global new energy vehicles and fuel vehicles (including inter-country trade relationship networks and competition relationships networks), and use this network model to analyze new energy vehicles and fuel vehicles The market competition landscape at the trade level is analyzed, and the application of multi-level exponential random graph model (ERGM) in this field is discussed. The results show that the global trade network of new energy vehicles and fuel vehicles shows an obvious center-periphery structure. Some countries have significantly maintained import relationships with multiple countries in the auto trade, and some countries have shown that they are interested in multiple countries. The propensity of a country to engage in export trade. Further ternary structure analysis revealed the existence of stratification in the trade patterns between new energy vehicles and fuel vehicles. In addition, the network structure analysis of competitive relationships shows that there are direct trade competition relationships between only a few countries, which means that only a few countries play the role of key industrial countries in the automotive trade field</span><span><span>.</span></span></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_17227251 |
| institution | Zenodo |
| language | eng |
| publishDate | 2025 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | Analysis of Global Trade Competition Pattern of New Energy Vehicles and Fuel Vehicles based on Multi-Layer Network QiYu Hu Multilayered Network Automobile Trade Network Competition Network Exponential Random Graph Model <p><strong><span>Abstract</span></strong><strong><span>—</span></strong><span> </span><span>Use the 2023 global trade export data of new energy vehicles and fuel vehicles to build a multi-layer network of global new energy vehicles and fuel vehicles (including inter-country trade relationship networks and competition relationships networks), and use this network model to analyze new energy vehicles and fuel vehicles The market competition landscape at the trade level is analyzed, and the application of multi-level exponential random graph model (ERGM) in this field is discussed. The results show that the global trade network of new energy vehicles and fuel vehicles shows an obvious center-periphery structure. Some countries have significantly maintained import relationships with multiple countries in the auto trade, and some countries have shown that they are interested in multiple countries. The propensity of a country to engage in export trade. Further ternary structure analysis revealed the existence of stratification in the trade patterns between new energy vehicles and fuel vehicles. In addition, the network structure analysis of competitive relationships shows that there are direct trade competition relationships between only a few countries, which means that only a few countries play the role of key industrial countries in the automotive trade field</span><span><span>.</span></span></p> |
| title | Analysis of Global Trade Competition Pattern of New Energy Vehicles and Fuel Vehicles based on Multi-Layer Network |
| topic | Multilayered Network Automobile Trade Network Competition Network Exponential Random Graph Model |
| url | https://doi.org/10.5281/zenodo.17227251 |