Rodyti trumpą aprašą

dc.contributor.authorLeščauskienė, Ingrida
dc.contributor.authorBaušys, Romualdas
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.contributor.authorJuodagalvienė, Birutė
dc.date.accessioned2023-09-18T20:33:55Z
dc.date.available2023-09-18T20:33:55Z
dc.date.issued2020
dc.identifier.issn2073-8994
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/150837
dc.description.abstractData symmetry and asymmetry might cause difficulties in various areas including criteria weighting approaches. Preference elicitation is an integral part of the multicriteria decision-making process. Weighting approaches differ in terms of accuracy, ease of use, complexity, and theoretical foundations. When the opinions of the wider audience are needed, electronic surveys with the matrix questions consisting of the visual analogue scales (VAS) might be employed as the easily understandable data collection tool. The novel criteria weighting technique VASMA weighting (VAS Matrix for the criteria weighting) is presented in this paper. It respects the psychometric features of the VAS scales and analyzes the uncertainties caused by the survey-based preference elicitation. VASMA weighting integrates WASPAS-SVNS for the determination of the subjective weights and Shannon entropy for the calculation of the objective weights. Numerical example analyzing the importance of the criteria that affect parents’ decisions regarding the choice of the kindergarten institution was performed as the practical application. Comparison of the VASMA weighting and the direct rating (DR) methodologies was done. It revealed that VASMA weighting is able to overcome the main disadvantages of the DR technique—the high biases of the collected data and the low variation of the criteria weights.eng
dc.formatPDF
dc.format.extentp. 1-20
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbySocial Sciences Citation Index (Web of Science)
dc.relation.isreferencedbyScopus
dc.relation.isreferencedbyINSPEC
dc.relation.isreferencedbyDOAJ
dc.relation.isreferencedbyGenamics Journal Seek
dc.relation.isreferencedbyChemical abstracts
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://www.mdpi.com/2073-8994/12/10/1641
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:71629210/datastreams/MAIN/content
dc.titleVASMA weighting: survey-based criteria weighting methodology that combines ENTROPY and WASPAS-SVNS to reflect the psychometric features of the VAS scales
dc.typeStraipsnis Web of Science DB / Article in Web of Science DB
dcterms.accessRightsThis article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references59
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyFundamentinių mokslų fakultetas / Faculty of Fundamental Sciences
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.studydirectionB04 - Informatikos inžinerija / Informatics engineering
dc.subject.vgtuprioritizedfieldsIK0303 - Dirbtinio intelekto ir sprendimų priėmimo sistemos / Artificial intelligence and decision support systems
dc.subject.ltspecializationsL103 - Įtrauki ir kūrybinga visuomenė / Inclusive and creative society
dc.subject.enVisual analogue scales (VAS)
dc.subject.encriteria weighting
dc.subject.enmatrix question
dc.subject.ensurvey
dc.subject.enWASPAS-SVNS
dc.subject.enentropy
dc.subject.endirect rating
dcterms.sourcetitleSymmetry: Special issue: Symmetric and asymmetric data in solution models
dc.description.issueiss. 10
dc.description.volumevol. 12
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi000586243200001
dc.identifier.doi10.3390/sym12101641
dc.identifier.elaba71629210


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