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Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry
The assessment of sustainable supplier is very significant for supply chain management (SCM). The procedure of sustainable supplier selection (SSS) is a complex process for decision experts (DEs) due to the association of diverse qualitative and quantitative attributes. As the uncertainty is usually...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164192/ https://www.ncbi.nlm.nih.gov/pubmed/35677555 http://dx.doi.org/10.1007/s00500-022-07192-8 |
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author | Mishra, Arunodaya Raj Saha, Abhijit Rani, Pratibha Pamucar, Dragan Dutta, Debjit Hezam, Ibrahim M. |
author_facet | Mishra, Arunodaya Raj Saha, Abhijit Rani, Pratibha Pamucar, Dragan Dutta, Debjit Hezam, Ibrahim M. |
author_sort | Mishra, Arunodaya Raj |
collection | PubMed |
description | The assessment of sustainable supplier is very significant for supply chain management (SCM). The procedure of sustainable supplier selection (SSS) is a complex process for decision experts (DEs) due to the association of diverse qualitative and quantitative attributes. As the uncertainty is usually ensued in the SSS and hesitant fuzzy set (HFS), an extension of fuzzy set (FS) has been demonstrated as one of the effective ways to treat the uncertain information in realistic problems. The objective of this paper is to propose an integrated hesitant fuzzy–data envelopment analysis (DEA)–full consistency method (FOCUM)–multi attribute border approximation area comparison (MABAC) method called HF-DEA-FUCOM-MABAC framework to assess the multi-attribute decision-making (MADM) problems on HFSs settings. In this line, first, the efficient alternatives are chosen using the DEA method. Second, The FUCOM is used to compute the subjective weight of attributes. Third, The HF-MABAC method is presented to prioritize the alternatives in an MADM problem. In the following, a case study of SSS problem for an Auto-making company is taken to show the practicality and utility of the presented approach. Next, we present a sensitivity investigation with different attribute weights set to observe the steadiness of the presented approach. Finally, we draw attention toward a comparison between presented approach with the extant HF-FOCUM-TOPSIS model to show its advantage and potency as well. |
format | Online Article Text |
id | pubmed-9164192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-91641922022-06-04 Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry Mishra, Arunodaya Raj Saha, Abhijit Rani, Pratibha Pamucar, Dragan Dutta, Debjit Hezam, Ibrahim M. Soft comput Soft Computing in Decision Making and in Modeling in Economics The assessment of sustainable supplier is very significant for supply chain management (SCM). The procedure of sustainable supplier selection (SSS) is a complex process for decision experts (DEs) due to the association of diverse qualitative and quantitative attributes. As the uncertainty is usually ensued in the SSS and hesitant fuzzy set (HFS), an extension of fuzzy set (FS) has been demonstrated as one of the effective ways to treat the uncertain information in realistic problems. The objective of this paper is to propose an integrated hesitant fuzzy–data envelopment analysis (DEA)–full consistency method (FOCUM)–multi attribute border approximation area comparison (MABAC) method called HF-DEA-FUCOM-MABAC framework to assess the multi-attribute decision-making (MADM) problems on HFSs settings. In this line, first, the efficient alternatives are chosen using the DEA method. Second, The FUCOM is used to compute the subjective weight of attributes. Third, The HF-MABAC method is presented to prioritize the alternatives in an MADM problem. In the following, a case study of SSS problem for an Auto-making company is taken to show the practicality and utility of the presented approach. Next, we present a sensitivity investigation with different attribute weights set to observe the steadiness of the presented approach. Finally, we draw attention toward a comparison between presented approach with the extant HF-FOCUM-TOPSIS model to show its advantage and potency as well. Springer Berlin Heidelberg 2022-06-03 2022 /pmc/articles/PMC9164192/ /pubmed/35677555 http://dx.doi.org/10.1007/s00500-022-07192-8 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Soft Computing in Decision Making and in Modeling in Economics Mishra, Arunodaya Raj Saha, Abhijit Rani, Pratibha Pamucar, Dragan Dutta, Debjit Hezam, Ibrahim M. Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry |
title | Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry |
title_full | Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry |
title_fullStr | Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry |
title_full_unstemmed | Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry |
title_short | Sustainable supplier selection using HF-DEA-FOCUM-MABAC technique: a case study in the Auto-making industry |
title_sort | sustainable supplier selection using hf-dea-focum-mabac technique: a case study in the auto-making industry |
topic | Soft Computing in Decision Making and in Modeling in Economics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9164192/ https://www.ncbi.nlm.nih.gov/pubmed/35677555 http://dx.doi.org/10.1007/s00500-022-07192-8 |
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