建立供应链的复原力:基于知识图谱的风险管理框架

IF 4.5 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS IEEE Transactions on Computational Social Systems Pub Date : 2023-12-22 DOI:10.1109/TCSS.2023.3334768
Yi Yang;Chen Peng;En-Zhi Cao;Wenxuan Zou
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引用次数: 0

摘要

作为一种新兴技术,知识图谱(KG)已成功应用于各行各业。虽然已经发现了知识图谱的一些潜在优势,但在供应链风险管理(SCRM)中实施知识图谱的工作仍然很少。本研究开发了一个基于 KG 的风险管理框架,以提高供应链(SC)的应变能力。具体而言,本研究详细介绍了供应链知识图谱(SC-KG)框架的构建,包括实施步骤,以实现供应链知识检索、数据可视化分析、风险监测、预警和决策支持等目的。此外,考虑到中断的严重性,SC-KG 还能很好地构建基于情景的 SCRM 框架。特别是在长期中断期间,通过采用产品变更策略和结构可扩展且动态调整的网络设计方法,可保持 SC 的连续性。研究结果对 SC 管理者在中断情况下采用数字技术缓解和恢复 SC 具有指导意义。最后,还开发了一个包含 250 多万个实体和 11 种关系的实用 SC-KG 并实现了其基本功能,这有助于提高 SC 管理的质量。
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Building Resilience in Supply Chains: A Knowledge Graph-Based Risk Management Framework
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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来源期刊
IEEE Transactions on Computational Social Systems
IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)
CiteScore
10.00
自引率
20.00%
发文量
316
期刊介绍: IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.
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