A novel spherical fuzzy-based decision model for assessing Data management maturity in governmental institutions

A novel spherical fuzzy-based decision model for assessing Data management maturity in governmental institutions | 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 novel spherical fuzzy-based decision model for assessing Data management maturity in governmental institutions Muna Salem AlFadhli, Berk Ayvaz, Murat Kucukvar, Aya Hasan Alkhereibi, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4753989/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 23 Jan, 2025 Read the published version in International Journal of Data Science and Analytics → Version 1 posted 13 You are reading this latest preprint version Abstract The capability of government institutions to manage data effectively is fundamental to their operational efficiency and innovation potential. Governments face unique challenges, including rapid data generation, evolving regulations, and demands for quality services and transparency. This necessitates a tailored approach to data governance, given the complexities of balancing public interests with data privacy. This study aims to establish a robust framework for evaluating the data management maturity of Government Entities by developing an evaluative metric that reflects their data management maturity. Our approach involved gathering and synthesizing dispersed principles from existing literature into a set of definitive criteria. The criteria were subjectively weighted by an expert panel to reflect the significance of each criterion in a government setting. For methodology, the study pioneers the hybridization of Spherical Fuzzy Sets (SFSs) built on the Criteria Importance Through Intercriteria Correlation (CRITIC) and the Evaluation based on Distance from Average Solution (EDAS) model. The criteria weighting was methodically calculated using the CRITIC method, and the subsequent evaluation of the alternatives was ascertained through EDAS. This combination of methodologies effectively reduced subjective bias, yielding a more reliable foundation for the rankings. A sensitivity analysis was conducted to confirm the robustness of the presented methodology when subjected to variations. To verify the validity of the developed method, we compared the SF- CRITIC & SF-EDAS approach with the SF-AHP & SF-EDAS, SF-CRITIC & SF-TOPSIS, the SF-CRITIC & SF-WPM, the SF-CRITIC & SF-MARCOS. The results showcased a spectrum of maturity levels across the evaluated entities, pinpointing both commendable proficiencies and key areas for growth. This research presents a strategic asset for government bodies, aiding in the targeted enhancement of their data management systems. The broader implications of our findings serve as a strategic compass for governmental organizations, steering them toward achieving a higher echelon of data management sophistication. Data Management Decision Modeling Governmental Institutes Data Maturity Fuzzy Logic CRITIC EDAS Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 23 Jan, 2025 Read the published version in International Journal of Data Science and Analytics → Version 1 posted Editorial decision: Revision requested 12 Nov, 2024 Reviews received at journal 11 Nov, 2024 Reviewers agreed at journal 04 Nov, 2024 Reviewers agreed at journal 09 Oct, 2024 Reviewers agreed at journal 08 Oct, 2024 Reviews received at journal 02 Sep, 2024 Reviewers agreed at journal 16 Aug, 2024 Reviewers agreed at journal 07 Aug, 2024 Reviewers agreed at journal 05 Aug, 2024 Reviewers invited by journal 05 Aug, 2024 Editor assigned by journal 01 Aug, 2024 Submission checks completed at journal 17 Jul, 2024 First submitted to journal 17 Jul, 2024 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-4753989","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":343154597,"identity":"4acaf3f7-a416-437e-bca2-28a6981b0e53","order_by":0,"name":"Muna Salem AlFadhli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYBACfmbGhgMfeGzq+dkbQHxmwlok25sPPpwhk5Yg2XOASC0GZ44lG3PYHEowuJFApBaGGzlm0gw5B/IkZz7eJsFQYZ3YwJ78AK8OxhlALQVn7hTzS6eVSTCcSU9s4HlmgFcLswRQy8yeZ4wzZ+eYSTC2HU5skEjAr4UNpIX332HGDTfPALX8A2lJ/4BXCw8P0Ps8PIcTN9zgAWppAGnJwW+LBDsokHnSjCV70ootEo6lG7fxvCnAq8X+MCQq5fjZD2+88aHGWrafPX0DXi3IwIAhAeQ7MEm0FgggQcsoGAWjYBSMCAAA+UBLX8s4MGoAAAAASUVORK5CYII=","orcid":"","institution":"Qatar University","correspondingAuthor":true,"prefix":"","firstName":"Muna","middleName":"Salem","lastName":"AlFadhli","suffix":""},{"id":343154598,"identity":"0acf4dc9-9ac2-4e1b-aeb0-ab34bc693e9f","order_by":1,"name":"Berk Ayvaz","email":"","orcid":"","institution":"Istanbul Ticaret University","correspondingAuthor":false,"prefix":"","firstName":"Berk","middleName":"","lastName":"Ayvaz","suffix":""},{"id":343154602,"identity":"8c9a9b53-963f-4fec-8f08-ee55ba23c2a1","order_by":2,"name":"Murat Kucukvar","email":"","orcid":"","institution":"Daniels College of Business | University of Denver","correspondingAuthor":false,"prefix":"","firstName":"Murat","middleName":"","lastName":"Kucukvar","suffix":""},{"id":343154606,"identity":"7b2f8214-e67d-433a-8763-21f24fd0bf50","order_by":3,"name":"Aya Hasan Alkhereibi","email":"","orcid":"","institution":"Qatar University","correspondingAuthor":false,"prefix":"","firstName":"Aya","middleName":"Hasan","lastName":"Alkhereibi","suffix":""},{"id":343154607,"identity":"d071325f-e0d7-47c3-9d05-69f2a687b277","order_by":4,"name":"Nuri Onat","email":"","orcid":"","institution":"Qatar University","correspondingAuthor":false,"prefix":"","firstName":"Nuri","middleName":"","lastName":"Onat","suffix":""},{"id":343154610,"identity":"70210931-4a0d-45d8-a963-3925e55518f9","order_by":5,"name":"Somaya Al-Maadeed","email":"","orcid":"","institution":"Qatar University","correspondingAuthor":false,"prefix":"","firstName":"Somaya","middleName":"","lastName":"Al-Maadeed","suffix":""}],"badges":[],"createdAt":"2024-07-17 06:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4753989/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4753989/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s41060-024-00701-y","type":"published","date":"2025-01-23T15:58:11+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":74858509,"identity":"5004208d-15f9-4553-9416-f09efa80cf46","added_by":"auto","created_at":"2025-01-27 16:10:33","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1308091,"visible":true,"origin":"","legend":"","description":"","filename":"Anovelsphericalfuzzybaseddecisionmodelupdateon15724.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4753989/v1_covered_8dc7734b-268f-4a5c-a16d-689a22be2873.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A novel spherical fuzzy-based decision model for assessing Data management maturity in governmental institutions","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":"international-journal-of-data-science-and-analytics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jdsa","sideBox":"Learn more about [International Journal of Data Science and Analytics](http://link.springer.com/journal/41060)","snPcode":"41060","submissionUrl":"https://submission.nature.com/new-submission/41060/3","title":"International Journal of Data Science and Analytics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Data Management, Decision Modeling, Governmental Institutes, Data Maturity, Fuzzy Logic, CRITIC, EDAS","lastPublishedDoi":"10.21203/rs.3.rs-4753989/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4753989/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe capability of government institutions to manage data effectively is fundamental to their operational efficiency and innovation potential. Governments face unique challenges, including rapid data generation, evolving regulations, and demands for quality services and transparency. This necessitates a tailored approach to data governance, given the complexities of balancing public interests with data privacy. This study aims to establish a robust framework for evaluating the data management maturity of Government Entities by developing an evaluative metric that reflects their data management maturity. Our approach involved gathering and synthesizing dispersed principles from existing literature into a set of definitive criteria. The criteria were subjectively weighted by an expert panel to reflect the significance of each criterion in a government setting. For methodology, the study pioneers the hybridization of Spherical Fuzzy Sets (SFSs) built on the Criteria Importance Through Intercriteria Correlation (CRITIC) and the Evaluation based on Distance from Average Solution (EDAS) model. The criteria weighting was methodically calculated using the CRITIC method, and the subsequent evaluation of the alternatives was ascertained through EDAS. This combination of methodologies effectively reduced subjective bias, yielding a more reliable foundation for the rankings. A sensitivity analysis was conducted to confirm the robustness of the presented methodology when subjected to variations. To verify the validity of the developed method, we compared the SF- CRITIC \u0026amp; SF-EDAS approach with the SF-AHP \u0026amp; SF-EDAS, SF-CRITIC \u0026amp; SF-TOPSIS, the SF-CRITIC \u0026amp; SF-WPM, the SF-CRITIC \u0026amp; SF-MARCOS. The results showcased a spectrum of maturity levels across the evaluated entities, pinpointing both commendable proficiencies and key areas for growth. This research presents a strategic asset for government bodies, aiding in the targeted enhancement of their data management systems. The broader implications of our findings serve as a strategic compass for governmental organizations, steering them toward achieving a higher echelon of data management sophistication.\u003c/p\u003e","manuscriptTitle":"A novel spherical fuzzy-based decision model for assessing Data management maturity in governmental institutions","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-28 09:05:57","doi":"10.21203/rs.3.rs-4753989/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-11-12T07:53:40+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-11T06:58:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291554482743821339481684703436163627394","date":"2024-11-05T02:19:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"214946767894081981828622596295770878435","date":"2024-10-10T03:50:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"71636584562446045830335156510422520034","date":"2024-10-08T08:46:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-09-02T13:40:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"149536787930299453691439069059606847471","date":"2024-08-16T07:16:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"298108131069080332184610929998728637311","date":"2024-08-07T10:55:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"134949257683946825000653726325012915020","date":"2024-08-05T12:50:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-05T12:27:48+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-01T15:23:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-07-17T16:26:05+00:00","index":"","fulltext":""},{"type":"submitted","content":"International Journal of Data Science and Analytics","date":"2024-07-17T06:21:44+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"international-journal-of-data-science-and-analytics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jdsa","sideBox":"Learn more about [International Journal of Data Science and Analytics](http://link.springer.com/journal/41060)","snPcode":"41060","submissionUrl":"https://submission.nature.com/new-submission/41060/3","title":"International Journal of Data Science and Analytics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"efc9572c-9613-47e1-90e9-304fbfe12e6e","owner":[],"postedDate":"August 28th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-01-27T16:04:13+00:00","versionOfRecord":{"articleIdentity":"rs-4753989","link":"https://doi.org/10.1007/s41060-024-00701-y","journal":{"identity":"international-journal-of-data-science-and-analytics","isVorOnly":false,"title":"International Journal of Data Science and Analytics"},"publishedOn":"2025-01-23 15:58:11","publishedOnDateReadable":"January 23rd, 2025"},"versionCreatedAt":"2024-08-28 09:05:57","video":"","vorDoi":"10.1007/s41060-024-00701-y","vorDoiUrl":"https://doi.org/10.1007/s41060-024-00701-y","workflowStages":[]},"version":"v1","identity":"rs-4753989","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4753989","identity":"rs-4753989","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}