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Robustness of the International Wheat Trade Network

Jinlong Ma,Meng Li,Huijing Li

Published 2024 in IEEE Transactions on Network Science and Engineering

ABSTRACT

Grain is the material basis for human survival and development, wheat is one of the three significant grains, and the robustness of the wheat trade has seriously affected world grain security. In the article, we analyze the robustness of the International Wheat Trade Network (IWTN) from three perspectives: global, regional, and national. We quantify the topological properties and evolution characteristics of IWTN from 1987 to 2020, and analyze the stability of IWTN using random attacks and target attacks. The import satisfaction of major wheat trading countries and trade communities is quantified through import stability indicators. Firstly, the results show that IWTN satisfies the scale-free property and that global wheat trade transactions continue to increase. Secondly, IWTN under random attack forms a “convex” curve regarding network efficiency. It shows that IWTN has better resistance to external shocks, and higher robustness. However, under the targeted attack, the network collapses when the node failure rate reaches 40%. Regardless of the attack mode, the decreasing trend of network efficiency and connectivity is the same in different years as the number of failed nodes gradually increases, and no year shows outstanding stability. Thirdly, different communities in the wheat trade are more satisfied with the wheat imports of their internal countries, and most of the wheat trade occurs within the same trading community. Fourthly, among the top five global wheat importers in 2020, Italy and Turkey have diversified sources of imports, but trade imports are relatively concentrated. In contrast, China, Egypt and Indonesia have relatively balanced wheat trade imports from their respective trading countries and are less at risk of being affected in the event of supply risks.

PUBLICATION RECORD

  • Publication year

    2024

  • Venue

    IEEE Transactions on Network Science and Engineering

  • Publication date

    2024-01-01

  • Fields of study

    Agricultural and Food Sciences, Computer Science, Economics

  • Identifiers
    DOI 10.1109/TNSE.2023.3283251
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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