计算机科学
风险管理
可扩展性
风险分析(工程)
供应链
弹性(材料科学)
过程管理
可视化
供应链风险管理
图形
预警系统
知识管理
供应链管理
业务
数据挖掘
服务管理
数据库
电信
物理
财务
理论计算机科学
营销
热力学
作者
Yi Yang,Chen Peng,En-Zhi Cao,Weibiao Zou
标识
DOI:10.1109/tcss.2023.3334768
摘要
As an emerging technology, the knowledge graph (KG) has been successfully applied in various industries. Though some potential benefits of the KG have been identified, there is still little work on implementing the KG in supply chain risk management (SCRM). This study develops a KG-based risk management framework to improve the resilience of Supply Chains (SCs). Specifically, the construction of the SC knowledge graph (SC-KG) framework, including the implementation steps, is presented in detail for the purpose of SC knowledge retrieval, data visualization analysis, risk monitoring, early warning, and decision support. Furthermore, the SC-KG is well constructed to build a scenario-based SCRM framework under consideration of the severity of disruptions. Especially during long-term disruptions, the continuity of SCs is maintained through the employment of a product change strategy and a structurally scalable and dynamically adapted network design method. The findings of the study are instructive for SC managers in adopting digital technologies for SC mitigation and recovery under disruptions. Finally, a practical SC-KG containing over 2.5 million entities and 11 types of relationships has been developed and its basic functions have been implemented, which contributes to improving the quality of SC management.
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