Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment

Detalhes bibliográficos
Autor(a) principal: Meidute-Kavaliauskiene, Ieva
Data de Publicação: 2021
Outros Autores: Ghorbani, Shahryar
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Independent Journal of Management & Production
Texto Completo: http://www.ijmp.jor.br/index.php/ijmp/article/view/1356
Resumo: The aim of this research study is to address a critique of how and when a supply chain contract is selected based on critical success factors (CSFs) utilizing stepwise weight assessment ratio analysis (SWARA) and Evaluation by an Area-based Method of ranking (EAMR). This research study ranked supply chain contracts by the EAMR in uncertainty environments, such as when breaking down the health care industry. This is done by providing a theoretical framework for sustainable entrepreneurship in telecommunications industry, focusing on managerial and operational practices that should be modified, in accordance to a set of CSFs identified from experts in fertility hospital. As a novel strategy, in this research, the initial factors of selecting customized Supply Chain Management (SCM) were extracted via a Delphi method along with the EAMR to symbolize a decision matrix that needs primary weights acquired through the SWARA method by hesitant fuzzy number. CSFs for achieving SCM contract selection in fertility hospitals were found to rely on a tripod based on effectiveness, transparency, and accountability that are embedded within the ambit of managerial and operational practices, such as focusing and reducing cost and based on these factors the best SCM contract must be selected. Besides, the EAMR method has more reliability than other similar MCDM methods such as TOPSIS, MOORA, VIKOR, and so on main contribution of this paper is the combination of SWARA, EAMR, and using hesitant fuzzy set in the EAMR method. Finally, the result indicates that hospitals based on these CSFs must be selected contracts.
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spelling Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environmentCritical Successful Factors (CSFs)Delphi methodHesitant fuzzy setsSCM contractSupply Chain Management (SCM)The aim of this research study is to address a critique of how and when a supply chain contract is selected based on critical success factors (CSFs) utilizing stepwise weight assessment ratio analysis (SWARA) and Evaluation by an Area-based Method of ranking (EAMR). This research study ranked supply chain contracts by the EAMR in uncertainty environments, such as when breaking down the health care industry. This is done by providing a theoretical framework for sustainable entrepreneurship in telecommunications industry, focusing on managerial and operational practices that should be modified, in accordance to a set of CSFs identified from experts in fertility hospital. As a novel strategy, in this research, the initial factors of selecting customized Supply Chain Management (SCM) were extracted via a Delphi method along with the EAMR to symbolize a decision matrix that needs primary weights acquired through the SWARA method by hesitant fuzzy number. CSFs for achieving SCM contract selection in fertility hospitals were found to rely on a tripod based on effectiveness, transparency, and accountability that are embedded within the ambit of managerial and operational practices, such as focusing and reducing cost and based on these factors the best SCM contract must be selected. Besides, the EAMR method has more reliability than other similar MCDM methods such as TOPSIS, MOORA, VIKOR, and so on main contribution of this paper is the combination of SWARA, EAMR, and using hesitant fuzzy set in the EAMR method. Finally, the result indicates that hospitals based on these CSFs must be selected contracts.Independent2021-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdftext/htmlhttp://www.ijmp.jor.br/index.php/ijmp/article/view/135610.14807/ijmp.v12i4.1356Independent Journal of Management & Production; Vol. 12 No. 4 (2021): Independent Journal of Management & Production; 1160-11872236-269X2236-269Xreponame:Independent Journal of Management & Productioninstname:Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)instacron:IJM&Penghttp://www.ijmp.jor.br/index.php/ijmp/article/view/1356/1814http://www.ijmp.jor.br/index.php/ijmp/article/view/1356/1815Copyright (c) 2021 Ieva Meidute-Kavaliauskiene, Shahryar Ghorbanihttp://creativecommons.org/licenses/by-nc-sa/4.0info:eu-repo/semantics/openAccessMeidute-Kavaliauskiene, IevaGhorbani, Shahryar2021-06-01T18:02:39Zoai:www.ijmp.jor.br:article/1356Revistahttp://www.ijmp.jor.br/PUBhttp://www.ijmp.jor.br/index.php/ijmp/oaiijmp@ijmp.jor.br||paulo@paulorodrigues.pro.br||2236-269X2236-269Xopendoar:2021-06-01T18:02:39Independent Journal of Management & Production - Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)false
dc.title.none.fl_str_mv Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment
title Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment
spellingShingle Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment
Meidute-Kavaliauskiene, Ieva
Critical Successful Factors (CSFs)
Delphi method
Hesitant fuzzy sets
SCM contract
Supply Chain Management (SCM)
title_short Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment
title_full Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment
title_fullStr Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment
title_full_unstemmed Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment
title_sort Supply chain contract selection in the healthcare industry: a hybrid mcdm method in uncertainty environment
author Meidute-Kavaliauskiene, Ieva
author_facet Meidute-Kavaliauskiene, Ieva
Ghorbani, Shahryar
author_role author
author2 Ghorbani, Shahryar
author2_role author
dc.contributor.author.fl_str_mv Meidute-Kavaliauskiene, Ieva
Ghorbani, Shahryar
dc.subject.por.fl_str_mv Critical Successful Factors (CSFs)
Delphi method
Hesitant fuzzy sets
SCM contract
Supply Chain Management (SCM)
topic Critical Successful Factors (CSFs)
Delphi method
Hesitant fuzzy sets
SCM contract
Supply Chain Management (SCM)
description The aim of this research study is to address a critique of how and when a supply chain contract is selected based on critical success factors (CSFs) utilizing stepwise weight assessment ratio analysis (SWARA) and Evaluation by an Area-based Method of ranking (EAMR). This research study ranked supply chain contracts by the EAMR in uncertainty environments, such as when breaking down the health care industry. This is done by providing a theoretical framework for sustainable entrepreneurship in telecommunications industry, focusing on managerial and operational practices that should be modified, in accordance to a set of CSFs identified from experts in fertility hospital. As a novel strategy, in this research, the initial factors of selecting customized Supply Chain Management (SCM) were extracted via a Delphi method along with the EAMR to symbolize a decision matrix that needs primary weights acquired through the SWARA method by hesitant fuzzy number. CSFs for achieving SCM contract selection in fertility hospitals were found to rely on a tripod based on effectiveness, transparency, and accountability that are embedded within the ambit of managerial and operational practices, such as focusing and reducing cost and based on these factors the best SCM contract must be selected. Besides, the EAMR method has more reliability than other similar MCDM methods such as TOPSIS, MOORA, VIKOR, and so on main contribution of this paper is the combination of SWARA, EAMR, and using hesitant fuzzy set in the EAMR method. Finally, the result indicates that hospitals based on these CSFs must be selected contracts.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.ijmp.jor.br/index.php/ijmp/article/view/1356
10.14807/ijmp.v12i4.1356
url http://www.ijmp.jor.br/index.php/ijmp/article/view/1356
identifier_str_mv 10.14807/ijmp.v12i4.1356
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv http://www.ijmp.jor.br/index.php/ijmp/article/view/1356/1814
http://www.ijmp.jor.br/index.php/ijmp/article/view/1356/1815
dc.rights.driver.fl_str_mv Copyright (c) 2021 Ieva Meidute-Kavaliauskiene, Shahryar Ghorbani
http://creativecommons.org/licenses/by-nc-sa/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Ieva Meidute-Kavaliauskiene, Shahryar Ghorbani
http://creativecommons.org/licenses/by-nc-sa/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
text/html
dc.publisher.none.fl_str_mv Independent
publisher.none.fl_str_mv Independent
dc.source.none.fl_str_mv Independent Journal of Management & Production; Vol. 12 No. 4 (2021): Independent Journal of Management & Production; 1160-1187
2236-269X
2236-269X
reponame:Independent Journal of Management & Production
instname:Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
instacron:IJM&P
instname_str Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
instacron_str IJM&P
institution IJM&P
reponame_str Independent Journal of Management & Production
collection Independent Journal of Management & Production
repository.name.fl_str_mv Independent Journal of Management & Production - Instituto Federal de Educação, Ciência e Tecnologia de São Paulo (IFSP)
repository.mail.fl_str_mv ijmp@ijmp.jor.br||paulo@paulorodrigues.pro.br||
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