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dc.contributor.authorBidel, Mohammad Javad
dc.contributor.authorSafari, Hossein
dc.contributor.authorAmoozad Mahdiraji, Hannan
dc.contributor.authorZavadskas, Edmundas Kazimieras
dc.contributor.authorAntuchevičienė, Jurgita
dc.date.accessioned2023-09-18T16:24:59Z
dc.date.available2023-09-18T16:24:59Z
dc.date.issued2022
dc.identifier.urihttps://etalpykla.vilniustech.lt/handle/123456789/113576
dc.description.abstractOne of the essential factors of project success is selecting the proper delivery method. This study aimed to provide a new hybrid decision-making framework to assist project stakeholders in evaluating and selecting the most appropriate Project Delivery System (PDS) and documenting the decision process. For this purpose, the selection factors of PDSs were obtained from a literature review, and critical selection factors were screened based on the fuzzy Delphi method, whereby expert feedback was on Information and Communication Technology (ICT) projects was obtained. Subsequently, the ICT project risks were identified and categorized into six competitive constraints, including time, cost, quality, reputation, value, and scope, and the risk factors were prioritized in each area. Then, the effect of project risks on the decision criteria was investigated using a fuzzy cognitive map (FCM). Finally, the PDSs were ranked through Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). This article researched a novel multi-layer decision system combining the FCM and FTOPSIS techniques. The decision criteria received their weights from the evaluation of the causal relationships between PDS selection factors and project risks. Thus, PDSs were ranked based on different project characteristics, the opinions of stakeholders, and the effect of project risks on the decision-making process; this increased the likelihood of project success. The results showed that the impact of the most critical project risks on the selection factors was so severe that they changed the weight of the criteria in the decision matrix and, subsequently, changed the ranking of decision options.eng
dc.formatPDF
dc.format.extentp. 1-22
dc.format.mediumtekstas / txt
dc.language.isoeng
dc.relation.isreferencedbyScience Citation Index Expanded (Web of Science)
dc.relation.isreferencedbyDOAJ
dc.relation.isreferencedbyRePec
dc.relation.isreferencedbyScopus
dc.rightsLaisvai prieinamas internete
dc.source.urihttps://www.mdpi.com/2227-7390/10/17/3185
dc.source.urihttps://talpykla.elaba.lt/elaba-fedora/objects/elaba:139512212/datastreams/MAIN/content
dc.titleA framework for project delivery systems via hybrid fuzzy risk analysis: Application and extension in ICT
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 (https:// creativecommons.org/licenses/by/ 4.0/).
dcterms.licenseCreative Commons – Attribution – 4.0 International
dcterms.references75
dc.type.pubtypeS1 - Straipsnis Web of Science DB / Web of Science DB article
dc.contributor.institutionUniversity of Tehran
dc.contributor.institutionUniversity of Leicester
dc.contributor.institutionVilniaus Gedimino technikos universitetas
dc.contributor.facultyStatybos fakultetas / Faculty of Civil Engineering
dc.subject.researchfieldT 002 - Statybos inžinerija / Construction and engineering
dc.subject.researchfieldT 007 - Informatikos inžinerija / Informatics engineering
dc.subject.vgtuprioritizedfieldsFM0101 - Fizinių, technologinių ir ekonominių procesų matematiniai modeliai / Mathematical models of physical, technological and economic processes
dc.subject.ltspecializationsL106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies
dc.subject.enProject Delivery Systems (PDSs)
dc.subject.enrisk analysis
dc.subject.enfuzzy cognitive maps (FCMs)
dc.subject.enICT projects
dc.subject.enFCM-FTOPSIS
dcterms.sourcetitleMathematics: Special issue: Data driven decision-making under uncertainty (D3U)
dc.description.issueiss. 17
dc.description.volumevol. 10
dc.publisher.nameMDPI
dc.publisher.cityBasel
dc.identifier.doi000851837900001
dc.identifier.doi10.3390/math10173185
dc.identifier.elaba139512212


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