Resilience Assessment of Global Manufacturing Value Chains Under the Influence of the Carbon Border Adjustment Mechanism Using Machine Learning and Knowledge Management

Resilience Assessment of Global Manufacturing Value Chains Under the Influence of the Carbon Border Adjustment Mechanism Using Machine Learning and Knowledge Management | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Resilience Assessment of Global Manufacturing Value Chains Under the Influence of the Carbon Border Adjustment Mechanism Using Machine Learning and Knowledge Management Danqing Chen Lecturer This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8313772/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract The introduction of the Carbon Border Adjustment Mechanism (CBAM) that balances the requirements of sustainability, competitiveness, and compliance in the international manufacturing value chain creates a new level of complexity. The present paper will be a proposal of a new Knowledge Resilience Assessment Framework (ML-KRAF) based on Machine Learning, which can be utilized to determine and improve the resilience of manufacturing global value chains under the effects of CBAM. The model integrates the approach of knowledge management theory and machine learning intelligence to gather, examine, and utilize the organization and cross-organization knowledge in the field of carbon management, supply chain flexibility, and production efficiency. It explains the Hybrid Random Forest-Graph Neural Network (HRF-GNN) as a new hybrid analysis model that is purportedly employed to simulate complex relationships between global value networks and offer ways of potential disruption and support strategic planning of resilience. Along with that, a Knowledge-Based Reinforcement Module (KBRM) refers to a continuous decision-maker optimizer by bringing real-time information and professional insights into dynamic knowledge bases. The model emphasizes active learning, carbon intelligence exchange, and dynamism of sustainability strategies in response to changes in regulations. The paper can be used to complete a new paradigm on how resilience is understood and managed in manufacturing systems within carbon-regulated global contexts by relating machine learning analytics and knowledge management systems, which provides a new theoretical and practical guidance to the leaders of policy, industry and sustainability strategies. Machine Learning Knowledge Management Global Value Chain Resilience Carbon Border Adjustment Mechanism (CBAM) Hybrid Random Forest–Graph Neural Network Sustainable Manufacturing Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 04 Mar, 2026 Reviews received at journal 18 Feb, 2026 Reviewers agreed at journal 18 Feb, 2026 Reviews received at journal 15 Feb, 2026 Reviewers agreed at journal 01 Feb, 2026 Reviewers agreed at journal 31 Jan, 2026 Reviewers invited by journal 23 Jan, 2026 Editor assigned by journal 19 Jan, 2026 Submission checks completed at journal 17 Jan, 2026 First submitted to journal 17 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8313772","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":579185378,"identity":"0cdadef2-e3c8-4743-aaf5-39f1d8651104","order_by":0,"name":"Danqing Chen Lecturer","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAyklEQVRIiWNgGAWjYFCCBMYHCRU1PPzsjY0PPxCphdngw5ljcpI9h5uNJYjUwiY5s43Z2OBGepsADzEa+NuTN0jzsLElzpz5sI1BgsFOTreBgBaJM88KjHl4ZBL7pRPbHhQwJBubHSCgxUAixyCZRwJoy+zEdgMJhgOJ24jRcpjHgDlxw82DbRI8RGoxbJyRAPI+I5FagH4pZvhwABTIicBANiDCL8AQ2/4j8R8oKo8/fPihwk6OoBaQ23CwidQyCkbBKBgFowALAABy70SVvWE8mwAAAABJRU5ErkJggg==","orcid":"","institution":"Zhengzhou University of Economics and Business","correspondingAuthor":true,"prefix":"","firstName":"Danqing","middleName":"Chen","lastName":"Lecturer","suffix":""}],"badges":[],"createdAt":"2025-12-09 06:23:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8313772/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8313772/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101397733,"identity":"79b78b7e-ddb5-4cf7-a901-806fc22e7044","added_by":"auto","created_at":"2026-01-29 09:36:12","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":801800,"visible":true,"origin":"","legend":"","description":"","filename":"RevisedPaper.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8313772/v1_covered_542001fa-5cae-4427-b562-f179872a44fe.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eResilience Assessment of Global Manufacturing Value Chains Under the Influence of the Carbon Border Adjustment Mechanism Using Machine Learning and Knowledge Management\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-artificial-intelligence","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"diai","sideBox":"Learn more about [Discover Artificial Intelligence](https://www.springer.com/44163)","snPcode":"","submissionUrl":"","title":"Discover Artificial Intelligence","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Machine Learning Knowledge Management, Global Value Chain Resilience, Carbon Border Adjustment Mechanism (CBAM), Hybrid Random Forest–Graph Neural Network, Sustainable Manufacturing","lastPublishedDoi":"10.21203/rs.3.rs-8313772/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8313772/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe introduction of the Carbon Border Adjustment Mechanism (CBAM) that balances the requirements of sustainability, competitiveness, and compliance in the international manufacturing value chain creates a new level of complexity. 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