dc.contributor.author | Fallahpour, Alireza | |
dc.contributor.author | Wong, Kuan Yew | |
dc.contributor.author | Rajoo, Srithar | |
dc.contributor.author | Fathollahi-Fard, Amir M. | |
dc.contributor.author | Antuchevičienė, Jurgita | |
dc.contributor.author | Nayeri, Sina | |
dc.date.accessioned | 2023-09-18T20:45:23Z | |
dc.date.available | 2023-09-18T20:45:23Z | |
dc.date.issued | 2021 | |
dc.identifier.issn | 0944-1344 | |
dc.identifier.other | (SCOPUS_ID)85119296252 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/152362 | |
dc.description.abstract | The recent advances in sustainable supply chain management are integrated with Industry 4.0 concepts. This study develops a new integrated model to consider the sustainability and Industry 4.0 criteria for the supplier selection management. The proposed approach consists of the fuzzy best worst method (FBWM) and the two-stage fuzzy inference system (FIS) to assess the selection of suppliers. Firstly, this study determines a comprehensive list of Industry 4.0 and sustainability criteria along with their definitions. Then, the importance weight of each criterion is computed by the FBWM. Subsequently, a two-stage FIS is devoted to nominate the suppliers’ performance with regard to the sustainability and Industry 4.0 criteria. To show the applicability of our integrated model, a case study for a textile company in Iran is provided. Finally, some sensitivity analyses are done to assess the efficiency of the proposed integrated approach. One finding is to establish a decision-making framework to evaluate suppliers separately, rather than relatively in a fuzzy environment using Industry 4.0 and sustainability criteria. | eng |
dc.format | PDF | |
dc.format.extent | p. 1-19 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Science Citation Index Expanded (Web of Science) | |
dc.relation.isreferencedby | Scopus | |
dc.rights | Laisvai prieinamas internete | |
dc.source.uri | https://link.springer.com/article/10.1007%2Fs11356-021-17445-y | |
dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:112548734/datastreams/MAIN/content | |
dc.title | An integrated approach for a sustainable supplier selection based on Industry 4.0 concept | |
dc.type | Straipsnis Web of Science DB / Article in Web of Science DB | |
dcterms.references | 95 | |
dc.type.pubtype | S1 - Straipsnis Web of Science DB / Web of Science DB article | |
dc.contributor.institution | Universiti Teknologi Malaysia | |
dc.contributor.institution | University of Québec | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.institution | University of Tehran | |
dc.contributor.faculty | Statybos fakultetas / Faculty of Civil Engineering | |
dc.subject.researchfield | T 002 - Statybos inžinerija / Construction and engineering | |
dc.subject.researchfield | T 007 - Informatikos inžinerija / Informatics engineering | |
dc.subject.researchfield | S 004 - Ekonomika / Economics | |
dc.subject.vgtuprioritizedfields | EV02 - Aukštos pridėtinės vertės ekonomika / High Value-Added Economy | |
dc.subject.ltspecializations | L104 - Nauji gamybos procesai, medžiagos ir technologijos / New production processes, materials and technologies | |
dc.subject.en | industry 4.0 | |
dc.subject.en | sustainable supply chain management | |
dc.subject.en | sustainable supplier selection | |
dc.subject.en | fuzzy best worst method | |
dc.subject.en | fuzzy inference system | |
dcterms.sourcetitle | Environmental science and pollution research | |
dc.description.issue | iss. 00 | |
dc.description.volume | vol. 00 | |
dc.publisher.name | Springer | |
dc.publisher.city | Heidelberg | |
dc.identifier.doi | 2-s2.0-85119296252 | |
dc.identifier.doi | 85119296252 | |
dc.identifier.doi | 0 | |
dc.identifier.doi | 000720254100009 | |
dc.identifier.doi | 132230776 | |
dc.identifier.doi | 10.1007/s11356-021-17445-y | |
dc.identifier.elaba | 112548734 | |