Cascading Credit Risk Assessment in Multiplex Supply Chain Networks

Cascading Credit Risk Assessment in Multiplex Supply Chain Networks | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 26 February 2026 V6 Latest version Share on Cascading Credit Risk Assessment in Multiplex Supply Chain Networks Authors : Lizi Chen , Yue Zou , Pengfei Pan , and Chia Hong Chang 0009-0004-2689-1806 Authors Info & Affiliations https://doi.org/10.22541/au.176858311.10362606/v6 324 views 129 downloads Contents Abstract Supplementary Material Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Credit risk identification in financial markets is critically important as global economies become more linked. This is particularly evident in multiplex networked supply-chain platforms. In these systems, risks can damage market stability. They also create information gaps and resource misallocations across different parts of the supply chain. Additionally, they may trigger cascading failures at key nodes. Most current methods treat these complex multiplex structures as single-layer networks. This simplification fails to capture their true dynamic behavior. Another issue is that nodes often operate across multiple chains, which makes risk mitigation harder. To solve these problems, we propose CIRAM, a cascading risk assessment method that uses neural networks. CIRAM includes contagion strength coefficients and a multi-transfer probability framework. These support a new multi-label propagation mechanism. Tests on supply chains of different scales show that CIRAM beats four baseline methods in precision, recall, and F1 score. CCS CONCEPTS Mathematics of computing ~Probability and statistics ~Probabilistic inference problems Supplementary Material File (cascading risk assessment method for credit risk identification in multiplex networked supply chains1.pdf) Download 1.49 MB Information & Authors Information Version history V1 Version 1 16 January 2026 V2 Version 2 23 January 2026 V3 Version 3 05 February 2026 V4 Version 4 19 February 2026 V5 Version 5 25 February 2026 V6 Version 6 26 February 2026 Copyright This work is licensed under a Creative Commons Attribution 4.0 International License Keywords cascading risk credit risk identification multi-label propagation multiplex supply chains Authors Affiliations Lizi Chen View all articles by this author Yue Zou View all articles by this author Pengfei Pan View all articles by this author Chia Hong Chang 0009-0004-2689-1806 View all articles by this author Metrics & Citations Metrics Article Usage 324 views 129 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Lizi Chen, Yue Zou, Pengfei Pan, et al. Cascading Credit Risk Assessment in Multiplex Supply Chain Networks. Authorea . 26 February 2026. DOI: https://doi.org/10.22541/au.176858311.10362606/v6 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu . 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