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Optimization of the international nickel ore trade network

Author

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  • Dong, Xiaojuan
  • An, Feng
  • Dong, Zhiliang
  • Wang, Ze
  • Jiang, Meihui
  • Yang, Ping
  • An, Haigang

Abstract

Optimizing the structure of the international nickel ore trade is of great significance for ensuring the supply of nickel ore. In this paper, we select data on the international nickel ore trade over ten years from 2009 to 2018 and identify major nickel ore net exporters and importers. Then, we construct nickel ore trade networks from the supply perspective and the demand perspective. Next, we design an improved dynamic programming model. Finally, we obtain the optimal trade network by solving the model based on an iterative algorithm. We find that the trade costs are reduced through the optimization of the nickel ore trade network, but the degree of reduction is not uniform. In addition, we find that the overall optimization proportion of the network in 2016–2018 is the lowest, and the nickel ore trade network during this period undergoes spontaneous optimization. Some countries in the trade network, such as Japan, need to be compensated for the increased costs after optimization through policy. We obtain the possible direction of trade optimization for importing and exporting countries for each year. The optimization direction of the nickel ore trade is then partly applied to real trade. Nickel ore importing countries should expand the scope of their supply sources, and exporting countries should adjust the allocation structure of their resources as soon as possible. The optimization of international nickel ore trade networks can help reduce energy consumption, promote the rational distribution of mineral resources and realize the sustainable development of resources.

Suggested Citation

  • Dong, Xiaojuan & An, Feng & Dong, Zhiliang & Wang, Ze & Jiang, Meihui & Yang, Ping & An, Haigang, 2021. "Optimization of the international nickel ore trade network," Resources Policy, Elsevier, vol. 70(C).
    • Handle: RePEc:eee:jrpoli:v:70:y:2021:i:c:s0301420720310060
    DOI: 10.1016/j.resourpol.2020.101978
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