文献类型：期刊文献

中文题名：国际大米贸易网络的智能建模与脆弱性分析

英文题名：Intelligent modeling and vulnerabilities of the international rice trade net-work

作者：谢文杰[1];张银婷[2];高兴禄[1];周炜星[1]

机构：[1]华东理工大学商学院,上海2002372.华东理工大学商学院,上海200237;[2]华东师范大学经济与管理学院,上海200062

年份：2025

卷号：28

期号：6

起止页码：1

中文期刊名：管理科学学报

外文期刊名：Journal of Management Sciences in China

收录：;北大核心:【北大核心2023】；

基金：国家自然科学基金资助项目(72171083);中央高校基本科研业务费资助项目。

语种：中文

中文关键词：国际大米贸易网络;机器学习;政策模拟;网络脆弱性;计算实验

外文关键词：international rice trade network;machine learning;policy simulation;network vulnerability;computational experiments

摘要：国以民为本,民以食为天.粮食安全是人类社会稳定发展的基石.面对新冠疫情、自然灾害、局部战争、贸易战等事件,全球粮食贸易网络的脆弱性直接影响国际粮食安全,如何度量贸易网络的脆弱性并提供风险防控策略,是亟需解决的重要问题.本研究基于效用函数理论,构建异质主体大米贸易决策模型,运用图神经网络(graph neural network)模型和优化算法学习决策模型参数,模拟国际大米贸易网络演化,探究经济体贸易行为的演化规律.在贸易战、新冠疫情冲击而导致的全球贸易关系变化的现实情景下,通过计算实验进行政策模拟和评估,探究经济体大米贸易在面对外部冲击时的脆弱性.研究发现,在大洲层面上,亚洲和欧洲、非洲和大洋洲、北美洲和南美洲分别具有相似的脆弱性;在经济体层面上,当贸易关系增加时,中国内地、意大利和泰国所受影响较大,而印度和巴基斯坦所受影响较小.本研究运用图神经网络和优化方法解构蕴藏于贸易网络结构中的诸多影响因素,重构经济体特征属性,充分考虑多主体计算实验模型中个体属性异质性,从而保证模型更加贴合现实贸易环境,使得计算实验结果具有更高的参考价值.本研究的主要创新点是融合数据驱动和机制建模两大研究范式,具有高度的可扩展性和迁移性,可应用于不同领域的复杂系统并分析其脆弱性或网络动力学特征.
The country is built on the people,and the people regard food as their heaven.Food security is the foundation for the healthy and stable development of human society.Natural disasters,local wars,climate change,and other events have affected China's food security and social life.Food security is one of the cor-nerstones of global economic and social development.The structural robustness of the international rice trade network plays an important role in the global economy.The graph neural network algorithm and utility function theory are integrated for learning a trade decision-making model which contains the benefit endowments and cost endowment of economies in international trades.How to address changes in the international rice environ-ment and the impact of international emergencies is a question of important research value.By integrating graph neural networks,utility theory,and other methods,heterogeneous individual characteristic representa-tions are learned from international rice trade network data,and the network formation and evolution mecha-nism are revealed in complex systems.Then,the evolution of complex networks is simulated at the macro and micro levels to study the international rice trade networks in depth.Precise and controllable trade strategies,considering the impact of the trade war and COVID-19,are proposed.In the international rice trade network,Asia and Europe,North America and South America,and Africa and Oceania are three groups with similar vulnerabilities.As trade relations increase,India and Pakistan are less affected.The rice trade of the main-land in China is more affected.The model framework in this paper is highly scalable and transferable.The main innovation of the model framework is to connect the two research paradigms of data-driven and mecha-nism modelling.It is a general model framework that can be applied to different complex systems and complex networks across different fields.