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Structural robustness of the international food supply network under external shocks and its determinants ( EI收录)
文献类型:期刊文献
英文题名:Structural robustness of the international food supply network under external shocks and its determinants
作者:Zhu, Han-Yu[1,2]; Zhang, Yin-Ting[3]; Xie, Wen-Jie[1,2]; Zhou, Wei-Xing[1,2,4]
机构:[1] School of Business, East China University of Science and Technology, Shanghai, 200237, China; [2] Research Center for Econophysics, East China University of Science and Technology, Shanghai, 200237, China; [3] School of Economics and Management, East China Normal University, Shanghai, 200062, China; [4] School of Mathematics, East China University of Science and Technology, Shanghai, 200237, China
年份:2025
外文期刊名:arXiv
收录:EI(收录号:20250176795)
语种:英文
摘要:The stability of the global food supply network is critical for ensuring food security. This study constructs an aggregated international food supply network based on the trade data of four staple crops and evaluates its structural robustness through network integrity under accumulating external shocks. Network integrity is typically quantified in network science by the relative size of the largest connected component, and we propose a new robustness metric that incorporates both the broadness p and severity q of external shocks. Our findings reveal that the robustness of the network has gradually increased over the past decades, punctuated by temporary declines that can be explained by major historical events. While the aggregated network remains robust under moderate disruptions, extreme shocks targeting key suppliers such as the United States and India can trigger systemic collapse. When the shock broadness p is less than about 0.3 and the shock severity q is close to 1, the structural robustness curves S(p, q) decrease linearly with respect to the shock broadness p, suggesting that the most critical economies have relatively even influence on network integrity. Comparing the robustness curves of the four individual staple foods, we find that the soybean supply network is the least robust. Furthermore, regression and machine learning analyses show that increaseing food (particularly rice and soybean) production enhances network robustness, while rising food prices significantly weaken it. Copyright ? 2025, The Authors. All rights reserved.
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