A hybrid network–fuzzy framework for modelling sustainable tourism development: latent structures from Delphi indicators

A hybrid network–fuzzy framework for modelling sustainable tourism development: latent structures from Delphi indicators | 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 A hybrid network–fuzzy framework for modelling sustainable tourism development: latent structures from Delphi indicators Yuri Calleo, Laura Antonucci, Simone Di Zio This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8490313/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 The elicitation of expert consensus in future studies often results in complex, high-dimensional datasets characterized by ordinal variables andnon-linear dependencies. Traditional hard clustering techniques frequentlyfail to capture the intrinsic ambiguity and the overlapping nature of futurescenarios derived from Delphi studies. This paper introduces a novel hybridmethodological framework that integrates correlation network analysis withfuzzy clustering to detect latent structures in ordinal Delphi data. We modelthe consensus space as a weighted graph where edge weights represent rankcorrelations between projections. A topological modularity maximization isfirst applied to identify the backbone of the community structure, followedby a Fuzzy C-Means algorithm on the topological feature space to assignmembership degrees to transitional variables. The methodology is appliedto a dataset of 57 items regarding the future of the tourism ecosystem in the Apulia region, evaluated by a panel of experts. Results reveal a tripartitelatent structure comprising structural assets, sustainability governance, andeconomic risks. The validity of the extracted partitions is confirmed via aMonte Carlo permutation test, demonstrating that the detected modularitysignificantly exceeds that of random networks. This approach offers a robustquantitative tool for policy planning, capable of distinguishing between coredrivers and ambiguous bridge factors in scenario building Fuzzy clustering Network analysis Tourism Delphi 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. 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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-8490313","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":571565084,"identity":"4ba175e2-ddd8-48dc-b783-2def27ae2ad5","order_by":0,"name":"Yuri Calleo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFUlEQVRIiWNgGAWjYJCCA0Asw8fAwPiAgUECWYKxAZ8WHjYGBmYDuJYDEC2NOPVAtbAhrDiAxxqDG7kPDzDU2PGwsTcfq+bdYRHNL3344ecPFfcS1zYwtz/AqiXd4ADDsWQeNp5jabd5z0jkzuxLM5Y4cKY4cdsB7A4zuJHGcICxgZmHTSLH7DZvm0TuhjM8DBIH2xIIaannYZN/Y1YM0rL/DA/zDyK0HAbawmPGDLaFB8jGp0XyzDOGAwnHjgP9kpYsOReoZcYZNjOLM2cSjLcdZmycgUUL3/E05g8faqrl+NkPH/zwtq0ut7+H+fGNiooE2W3H2x98wKJF4QCQSMAiAQTM2IXlsbl2FIyCUTAKRgEKAADuRmdP3ANg8gAAAABJRU5ErkJggg==","orcid":"","institution":"Mercatorum University","correspondingAuthor":true,"prefix":"","firstName":"Yuri","middleName":"","lastName":"Calleo","suffix":""},{"id":571565086,"identity":"2fe80539-90e8-411a-bcce-2ac2ab54e377","order_by":1,"name":"Laura Antonucci","email":"","orcid":"","institution":"University of Foggia","correspondingAuthor":false,"prefix":"","firstName":"Laura","middleName":"","lastName":"Antonucci","suffix":""},{"id":571565089,"identity":"643e2a41-90bc-40d4-862c-d5336a3ff474","order_by":2,"name":"Simone Di Zio","email":"","orcid":"","institution":"University of Chieti-Pescara","correspondingAuthor":false,"prefix":"","firstName":"Simone","middleName":"Di","lastName":"Zio","suffix":""}],"badges":[],"createdAt":"2025-12-31 14:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8490313/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8490313/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100357518,"identity":"a7b55b8c-0462-4a50-82ab-87ae7339a957","added_by":"auto","created_at":"2026-01-16 07:19:59","extension":"json","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5064,"visible":true,"origin":"","legend":"","description":"","filename":"94eb7d88f1814fee9fe30a252a77ea71.json","url":"https://assets-eu.researchsquare.com/files/rs-8490313/v1/f6e2ee1c07c351189b4c2663.json"},{"id":100377103,"identity":"32a5cfaf-a324-471a-be04-02c72fa6a061","added_by":"auto","created_at":"2026-01-16 08:47:05","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":755981,"visible":true,"origin":"","legend":"","description":"","filename":"SpecialIssuequq3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8490313/v1_covered_62552928-5551-40eb-a1e4-cbf938b47efb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA hybrid network–fuzzy framework for modelling sustainable tourism development: latent structures from Delphi indicators\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"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},"keywords":"Fuzzy clustering, Network analysis, Tourism, Delphi","lastPublishedDoi":"10.21203/rs.3.rs-8490313/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8490313/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"The elicitation of expert consensus in future studies often results in complex, high-dimensional datasets characterized by ordinal variables andnon-linear dependencies. 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