Multicriteria Methodology for Selection of a Personal Electric Vehicle

Detalhes bibliográficos
Autor(a) principal: Gomes, Carlos Francisco Simões
Data de Publicação: 2023
Outros Autores: Sousa, Francisco, Pereira, Teresa, Oliveira, Marisa, Torres, Luís Norberto Miranda
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Brazilian Journal of Operations & Production Management (Online)
Texto Completo: https://bjopm.org.br/bjopm/article/view/1415
Resumo: A methodology that can support the decision process for selecting an Electric Vehicle (EV) is crucial. Considering the quantity, diversity, and complexity of existing EV models, their advantages and disadvantages, and people's increasing concern for sustainability, selecting and buying a personal EV appropriate to one's needs and requirements is not a simple task. Currently, criteria such as price, consumption per 100 km, range, comfort, brand, safety, and technology can be used to analyse available EV models. In this context, the decision-making process can be supported by the Multicriteria Decision Analysis (MCDA), “a method that clearly structures and evaluates complex problems with several alternatives, conflicting criteria, and complex scenarios. The novelty of this paper is to present a hybrid MCDA approach, combining two powerful methods (AHP and PROMETHEE) into a single framework to assist EV selection by any given person who has no multicriteria knowledge. A survey was conducted to define relevant criteria for a private person selecting an EV. The approach was validated for EV selection, considering the available offer within a target value, based solely on available public data, and excluding qualitative criteria. The paper discusses a case study whereby the proposed approach, using both quantitative and qualitative criteria, assists a decision-maker in selecting an EV from a set of alternatives, validated by the decision-maker, proving the importance and relevance of supporting the decision-making process.
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spelling Multicriteria Methodology for Selection of a Personal Electric VehicleMulticriteriaPROMETHEE AHP Electric vehiclesA methodology that can support the decision process for selecting an Electric Vehicle (EV) is crucial. Considering the quantity, diversity, and complexity of existing EV models, their advantages and disadvantages, and people's increasing concern for sustainability, selecting and buying a personal EV appropriate to one's needs and requirements is not a simple task. Currently, criteria such as price, consumption per 100 km, range, comfort, brand, safety, and technology can be used to analyse available EV models. In this context, the decision-making process can be supported by the Multicriteria Decision Analysis (MCDA), “a method that clearly structures and evaluates complex problems with several alternatives, conflicting criteria, and complex scenarios. The novelty of this paper is to present a hybrid MCDA approach, combining two powerful methods (AHP and PROMETHEE) into a single framework to assist EV selection by any given person who has no multicriteria knowledge. A survey was conducted to define relevant criteria for a private person selecting an EV. The approach was validated for EV selection, considering the available offer within a target value, based solely on available public data, and excluding qualitative criteria. The paper discusses a case study whereby the proposed approach, using both quantitative and qualitative criteria, assists a decision-maker in selecting an EV from a set of alternatives, validated by the decision-maker, proving the importance and relevance of supporting the decision-making process.Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)2023-04-04info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionResearch paperapplication/pdfhttps://bjopm.org.br/bjopm/article/view/141510.14488/BJOPM.1415.2023Brazilian Journal of Operations & Production Management; Vol. 20 No. 2 (2023); 1415 2237-8960reponame:Brazilian Journal of Operations & Production Management (Online)instname:Associação Brasileira de Engenharia de Produção (ABEPRO)instacron:ABEPROenghttps://bjopm.org.br/bjopm/article/view/1415/1042Copyright (c) 2023 Carlos Francisco Simões Gomes, Francisco Sousa, Teresa Pereira, Marisa Oliveira, Luís Norberto Miranda Torreshttp://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessGomes, Carlos Francisco SimõesSousa, FranciscoPereira, TeresaOliveira, MarisaTorres, Luís Norberto Miranda2023-04-04T13:19:52Zoai:ojs.bjopm.org.br:article/1415Revistahttps://bjopm.org.br/bjopmONGhttps://bjopm.org.br/bjopm/oaibjopm.journal@gmail.com2237-89601679-8171opendoar:2023-04-04T13:19:52Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO)false
dc.title.none.fl_str_mv Multicriteria Methodology for Selection of a Personal Electric Vehicle
title Multicriteria Methodology for Selection of a Personal Electric Vehicle
spellingShingle Multicriteria Methodology for Selection of a Personal Electric Vehicle
Gomes, Carlos Francisco Simões
Multicriteria
PROMETHEE
AHP
Electric vehicles
title_short Multicriteria Methodology for Selection of a Personal Electric Vehicle
title_full Multicriteria Methodology for Selection of a Personal Electric Vehicle
title_fullStr Multicriteria Methodology for Selection of a Personal Electric Vehicle
title_full_unstemmed Multicriteria Methodology for Selection of a Personal Electric Vehicle
title_sort Multicriteria Methodology for Selection of a Personal Electric Vehicle
author Gomes, Carlos Francisco Simões
author_facet Gomes, Carlos Francisco Simões
Sousa, Francisco
Pereira, Teresa
Oliveira, Marisa
Torres, Luís Norberto Miranda
author_role author
author2 Sousa, Francisco
Pereira, Teresa
Oliveira, Marisa
Torres, Luís Norberto Miranda
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Gomes, Carlos Francisco Simões
Sousa, Francisco
Pereira, Teresa
Oliveira, Marisa
Torres, Luís Norberto Miranda
dc.subject.por.fl_str_mv Multicriteria
PROMETHEE
AHP
Electric vehicles
topic Multicriteria
PROMETHEE
AHP
Electric vehicles
description A methodology that can support the decision process for selecting an Electric Vehicle (EV) is crucial. Considering the quantity, diversity, and complexity of existing EV models, their advantages and disadvantages, and people's increasing concern for sustainability, selecting and buying a personal EV appropriate to one's needs and requirements is not a simple task. Currently, criteria such as price, consumption per 100 km, range, comfort, brand, safety, and technology can be used to analyse available EV models. In this context, the decision-making process can be supported by the Multicriteria Decision Analysis (MCDA), “a method that clearly structures and evaluates complex problems with several alternatives, conflicting criteria, and complex scenarios. The novelty of this paper is to present a hybrid MCDA approach, combining two powerful methods (AHP and PROMETHEE) into a single framework to assist EV selection by any given person who has no multicriteria knowledge. A survey was conducted to define relevant criteria for a private person selecting an EV. The approach was validated for EV selection, considering the available offer within a target value, based solely on available public data, and excluding qualitative criteria. The paper discusses a case study whereby the proposed approach, using both quantitative and qualitative criteria, assists a decision-maker in selecting an EV from a set of alternatives, validated by the decision-maker, proving the importance and relevance of supporting the decision-making process.
publishDate 2023
dc.date.none.fl_str_mv 2023-04-04
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Research paper
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://bjopm.org.br/bjopm/article/view/1415
10.14488/BJOPM.1415.2023
url https://bjopm.org.br/bjopm/article/view/1415
identifier_str_mv 10.14488/BJOPM.1415.2023
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://bjopm.org.br/bjopm/article/view/1415/1042
dc.rights.driver.fl_str_mv http://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)
publisher.none.fl_str_mv Brazilian Association for Industrial Engineering and Operations Management (ABEPRO)
dc.source.none.fl_str_mv Brazilian Journal of Operations & Production Management; Vol. 20 No. 2 (2023); 1415
2237-8960
reponame:Brazilian Journal of Operations & Production Management (Online)
instname:Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron:ABEPRO
instname_str Associação Brasileira de Engenharia de Produção (ABEPRO)
instacron_str ABEPRO
institution ABEPRO
reponame_str Brazilian Journal of Operations & Production Management (Online)
collection Brazilian Journal of Operations & Production Management (Online)
repository.name.fl_str_mv Brazilian Journal of Operations & Production Management (Online) - Associação Brasileira de Engenharia de Produção (ABEPRO)
repository.mail.fl_str_mv bjopm.journal@gmail.com
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