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Dynamic changes in the bauxite trade competition network structure and its influencing factors: Based on temporal exponential random graph model
被引:0
|作者:
Li Y.
[1
]
Liu Y.
[2
]
Pu Y.
[3
,4
]
机构:
[1] Institute of International Economy, University of International Business and Economics, Beijing
[2] International Business Strategy Institute, University of International Business and Economics, Beijing
[3] School of International Business, Southwestern University of Finance and Economics, Sichuan, Chengdu
[4] Center for Bay of Bengal Studies, Southwestern University of Finance and Economics, Sichuan, Chengdu
来源:
基金:
中国国家自然科学基金;
关键词:
Bauxite;
Competition network;
Complex network;
TERGM;
D O I:
10.1016/j.resourpol.2024.105176
中图分类号:
学科分类号:
摘要:
Global bauxite resource mismatch, limited resources and rising demand have led to intense import competition and export competition. Based on the bauxite trade data from 2005 to 2020, this study uses the complex network method to construct the bauxite import and export competition network, analyzes the evolution of the global bauxite competition pattern and influencing factors. The results show that: First, the density of global bauxite competition network as a whole is on the rise, and competition networks are somewhat resistant to destruction. Second, the import competition network shows a clear trend towards eastward migration, with China's competition strength standing out. Most of the competing economies in the export competition network are large bauxite resource economies. Third, both import and export competition networks show a tendency to spread from core and semi-periphery regions to periphery region. Finally, it can be seen from the influencing factors analysis, the competition network of bauxite has stability. GDP, population, and FTA significantly promote the formation of competition networks, while CO2 and geographic distance play the opposite role. In addition, the effects of industrial structure, common language and common colony on the import and export competition networks are not uniform. © 2024 Elsevier Ltd
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