{"paper_id":"275cfba6-df42-4b9e-b3f1-fb52e014d837","body_text":"Study on the Destruction Resistance of Collaborative Innovation Networks in City Clusters under Subject Failure Scenarios: Simulation Analysis Based on Network Cascade Failure Models | 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 Study on the Destruction Resistance of Collaborative Innovation Networks in City Clusters under Subject Failure Scenarios: Simulation Analysis Based on Network Cascade Failure Models Danli Du, Jiahe Wang, Kaixing Ding, Yufeng Jin, Xinyi Wang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5624867/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract As the interdependence within inter-city collaborative innovation networks intensifies, the threat posed by subject failures triggered by external shocks to the effective functioning of these networks becomes increasingly critical. This paper delves into the impact of various types of subject failures on the resilience of city cluster collaborative innovation networks. By categorizing subject failures into nine distinct modes, this study integrates two pivotal aspects of innovation network resilience—structure and function—into a unified research framework. Structural resilience is assessed through the maximum connectivity subgraph, while functional resilience is gauged using network efficiency. The findings reveal notable variations in the structure of collaborative innovation networks across different fields, alongside differing sensitivities to the network’s resistance to destruction due to subject failures. Moreover, it was observed that random subject failures associated with high city clustering coefficients exert minimal impact on the network's structural and functional destructiveness, whereas those linked to larger city degree centrality significantly disrupt both network structure and function. Furthermore, the V index is employed to compare the effects of subject failure indicators across nine modes, indicating that cities with higher degrees of centrality have the most profound impact on network resilience. Significantly, when subject failures reach a threshold of 10%, both the structural and functional aspects of the city cluster collaborative innovation network approach a collapse threshold. The outcomes of this research highlight the destructive characteristics of city cluster collaborative innovation networks and offer a theoretical foundation for developing targeted risk management strategies to ensure the network's sustainable development. city clusters collaborative innovation networks destruction resistance subject failure cascade failure Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-5624867\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":392524272,\"identity\":\"a271eb32-20ce-40b7-9cff-48e2a7181610\",\"order_by\":0,\"name\":\"Danli Du\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Harbin Engineering University\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Danli\",\"middleName\":\"\",\"lastName\":\"Du\",\"suffix\":\"\"},{\"id\":392524273,\"identity\":\"c2e56ec7-7afe-4e27-a111-52361bd6c660\",\"order_by\":1,\"name\":\"Jiahe 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This paper delves into the impact of various types of subject failures on the resilience of city cluster collaborative innovation networks. By categorizing subject failures into nine distinct modes, this study integrates two pivotal aspects of innovation network resilience\\u0026mdash;structure and function\\u0026mdash;into a unified research framework. Structural resilience is assessed through the maximum connectivity subgraph, while functional resilience is gauged using network efficiency. The findings reveal notable variations in the structure of collaborative innovation networks across different fields, alongside differing sensitivities to the network\\u0026rsquo;s resistance to destruction due to subject failures. Moreover, it was observed that random subject failures associated with high city clustering coefficients exert minimal impact on the network's structural and functional destructiveness, whereas those linked to larger city degree centrality significantly disrupt both network structure and function. Furthermore, the V index is employed to compare the effects of subject failure indicators across nine modes, indicating that cities with higher degrees of centrality have the most profound impact on network resilience. Significantly, when subject failures reach a threshold of 10%, both the structural and functional aspects of the city cluster collaborative innovation network approach a collapse threshold. The outcomes of this research highlight the destructive characteristics of city cluster collaborative innovation networks and offer a theoretical foundation for developing targeted risk management strategies to ensure the network's sustainable development.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Study on the Destruction Resistance of Collaborative Innovation Networks in City Clusters under Subject Failure Scenarios: Simulation Analysis Based on Network Cascade Failure Models\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2024-12-23 14:32:30\",\"doi\":\"10.21203/rs.3.rs-5624867/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"identity\":\"researchsquare\",\"isNatureJournal\":false,\"hasQc\":true,\"allowDirectSubmit\":true,\"externalIdentity\":\"\",\"sideBox\":\"\",\"snPcode\":\"\",\"submissionUrl\":\"/submission\",\"title\":\"Research Square\",\"twitterHandle\":\"researchsquare\",\"acdcEnabled\":true,\"dfaEnabled\":false,\"editorialSystem\":\"\",\"reportingPortfolio\":\"\",\"inReviewEnabled\":false,\"inReviewRevisionsEnabled\":true}}],\"origin\":\"\",\"ownerIdentity\":\"3526155b-ac7d-4e22-987d-43173c8273fb\",\"owner\":[],\"postedDate\":\"December 23rd, 2024\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[],\"tags\":[],\"updatedAt\":\"2025-03-20T07:54:04+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2024-12-23 14:32:30\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-5624867\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-5624867\",\"identity\":\"rs-5624867\",\"version\":[\"v1\"]},\"buildId\":\"qtupq5eGEP_6zYnWcrvyt\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}