Dynamic collective opinion generation framework for digital transformation barrier analysis in the construction industry

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dc.authoridChen, Zhen-Song/0000-0003-4360-5459
dc.authorwosidChen, Zhen-Song/K-3436-2019
dc.contributor.authorChen, Zhen-Song
dc.contributor.authorLiang, Chong-Ze
dc.contributor.authorXu, Ya-Qiang
dc.contributor.authorPedrycz, Witold
dc.contributor.authorSkibniewski, Miroslaw J.
dc.date.accessioned2024-05-19T14:40:52Z
dc.date.available2024-05-19T14:40:52Z
dc.date.issued2024
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThe absence of a reliable, dynamic evaluation system has impeded early-stage industrial research progress, particularly in the digital transformation of the construction industry. Moreover, existing research studies rarely explore the impact of digitalt transformation barriers considering the interplays among them. This paper aims to introduce an innovative framework to generate dynamic collective opinions for barrier analysis in such context. The proposed dynamic collective opinion generation framework comprises three key components: Collective Opinion Generation, Prediction with Expert Advice (PEA), and Social Network Analysis. Its goal is to provide dependable decision support when subjective evaluation data from experts is available. Initially, a bi-objective optimization model generates the initial barrier weight vector. The PEA incorporates a loss function to measure the deviation between aggregated probablity density function and actual observed data, updating the weight vector over time. Next, an influence network covering all barriers is established. Node significance is evaluated through metrics like degree centrality, closeness centrality, and eigenvector centrality. The gravity model based on three metrics is used to determine interrelationships among barriers, resulting in a weight vector capturing these interplays. The two weight vectors are combined with Nash equilibrium, yielding the ultimate weight vector for barriers. The effectiveness of the proposed dynamic collective opinion generation framework is showcased through a case study on China Construction Third Bureau. Results indicate that talent structure notably influences construction companies' digital transformation. Additionally, market structure and strategic position significantly impact digital transformation in this industry.en_US
dc.description.sponsorshipNational Natural Science Foundation of China [72171182, 72031009]en_US
dc.description.sponsorshipThis work was supported by the National Natural Science Foundation of China under Grants 72171182 and 72031009.en_US
dc.identifier.doi10.1016/j.inffus.2023.102096
dc.identifier.issn1566-2535
dc.identifier.issn1872-6305
dc.identifier.scopus2-s2.0-85175366809en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org10.1016/j.inffus.2023.102096
dc.identifier.urihttps://hdl.handle.net/20.500.12713/5029
dc.identifier.volume103en_US
dc.identifier.wosWOS:001106939800001en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.relation.ispartofInformation Fusionen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.subjectDigital Transformationen_US
dc.subjectConstruction Enterprisesen_US
dc.subjectCollective Opinion Generationen_US
dc.subjectPrediction With Expert Adviceen_US
dc.subjectSocial Network Analysisen_US
dc.titleDynamic collective opinion generation framework for digital transformation barrier analysis in the construction industryen_US
dc.typeArticleen_US

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