Optimized decision support for BIM maturity assessment

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dc.authoridDarko, Amos/0000-0002-7978-6039
dc.authoridChen, Zhen-Song/0000-0003-4360-5459
dc.authorwosidDarko, Amos/C-4721-2018
dc.authorwosidChen, Zhen-Song/K-3436-2019
dc.contributor.authorChen, Zhen-Song
dc.contributor.authorZhou, Meng-Die
dc.contributor.authorChin, Kwai-Sang
dc.contributor.authorDarko, Amos
dc.contributor.authorWang, Xian-Jia
dc.contributor.authorPedrycz, Witold
dc.date.accessioned2024-05-19T14:39:23Z
dc.date.available2024-05-19T14:39:23Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractBuilding information modeling (BIM) maturity models occupy a crucial role in guiding BIM-reliant stakeholders and enterprises to identify BIM capabilities and facilitate process improvements. Nevertheless, few quantitative BIM maturity models are available for the measurement and improvement of BIM utilization performance. This study designs a refined assessment system for the maturity measurement of BIM-based projects during the design and construction stages. The advocated BIM maturity model combines a probability distribution function aggregation paradigm and a large-scale group decision-making framework to provide an expert-based assessment system for evaluating project-based BIM performance. The case study of the Corning Gen 10.5 glass substrate production line workshop in Wuhan demonstrates the feasibility and effectiveness of the proposed model. This paper establishes a generalizable structural framework that can potentially facilitate BIM maturity analysis in a portfolio of projects or the industry as a whole and will generate fresh insight into designing quantitative BIM maturity models across various contexts.en_US
dc.description.sponsorshipNational Natural Science Foundation of China [72171182, 71801175, 71871171, 71971182, 72031009]; Chinese National Funding of Social Sciences [20ZD058]; Theme-based Research Projects of the Research Grants Council [T32-101/15-R]; City University of Hong Kong SRG [7004969]; Ger/HKJRS project [G-CityU103/17]en_US
dc.description.sponsorshipAcknowledgments This work was partly supported by the National Natural Science Foundation of China (Grant nos. 72171182, 71801175, 71871171, 71971182, and 72031009) , the Chinese National Funding of Social Sciences (Grant no. 20&ZD058) , the Theme-based Research Projects of the Research Grants Council (Grant no. T32-101/15-R) , the City University of Hong Kong SRG (Grant no. 7004969) , and the Ger/HKJRS project (Grant no. G-CityU103/17) .en_US
dc.identifier.doi10.1016/j.autcon.2023.104808
dc.identifier.issn0926-5805
dc.identifier.issn1872-7891
dc.identifier.scopus2-s2.0-85148694666en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org10.1016/j.autcon.2023.104808
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4768
dc.identifier.volume149en_US
dc.identifier.wosWOS:001012154400001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofAutomation In Constructionen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectBim Maturity Assessment Systemen_US
dc.subjectOptimized Aggregationen_US
dc.subjectProbability Distribution Functionen_US
dc.subjectLarge-Scale Group Decision-Makingen_US
dc.subjectProject-Based Assessmenten_US
dc.titleOptimized decision support for BIM maturity assessmenten_US
dc.typeArticleen_US

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