A Knowledge Graph-Driven Risk Management Framework

Chen Peng (), Hongfeng Wang (), Yi Yang () and Yong Zhang ()
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Chen Peng: Shanghai University, School of Mechatronic Engineering and Automation
Hongfeng Wang: Northeastern University
Yi Yang: Shanghai University
Yong Zhang: China University of Mining and Technology, School of Information and Control Engineering

Chapter Chapter 2 in Modeling and Resilience Recovery for Disrupted Supply Chain, 2026, pp 23-33 from Springer

Abstract: Abstract Knowledge graph (KG) is widely applied in various industries, yet its practical application in supply chain risk management (SCRM) remains insufficient. This chapter develops a KG-based risk management framework to boost supply chain (SC) resilience, elaborating the construction steps of the SC-KG for knowledge retrieval, data visualization, risk monitoring, early warning and decision support. A scenario-based SCRM framework is built via SC-KG by considering disruption severity, and for long-term disruptions, product change strategy and dynamically adaptive network design are adopted to maintain SC continuity. A practical SC-KG with over 2.5 million entities and 11 relationship types is developed, whose functional implementation provides guidance for digital SCRM and improves SC management quality.

Keywords: knowledge graph; disruption risk; product change; data visualization; decision support (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-981-95-4901-6_2

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