A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme

Interest in group decision-making (GDM) has been increasing prominently over the last decade. Access to global databases, sophisticated sensors which can obtain multiple inputs or complex problems requiring opinions from several experts have driven interest in data aggregation. Consequently, the fie...

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Autores: Boix Cots, David|||0000-0002-8462-8887, Pardo Bosch, Francesc|||0000-0001-9532-8508, Pujadas Álvarez, Pablo|||0000-0001-5634-7431
Tipo de recurso: artículo
Fecha de publicación:2023
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/385395
Acceso en línea:https://hdl.handle.net/2117/385395
https://dx.doi.org/10.1016/j.inffus.2023.03.004
Access Level:acceso abierto
Palabra clave:Decision making
Group decision-making
Multiple criteria group decision-making
Expert weights
MCGDM
MAGDM
Decisió, Presa de
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
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network_acronym_str ES
network_name_str España
repository_id_str
spelling A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification schemeBoix Cots, David|||0000-0002-8462-8887Pardo Bosch, Francesc|||0000-0001-9532-8508Pujadas Álvarez, Pablo|||0000-0001-5634-7431Decision makingGroup decision-makingMultiple criteria group decision-makingExpert weightsMCGDMMAGDMDecisió, Presa deÀrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàticaInterest in group decision-making (GDM) has been increasing prominently over the last decade. Access to global databases, sophisticated sensors which can obtain multiple inputs or complex problems requiring opinions from several experts have driven interest in data aggregation. Consequently, the field has been widely studied from several viewpoints and multiple approaches have been proposed. Nevertheless, there is a lack of general framework. Moreover, this problem is exacerbated in the case of experts’ weighting methods, one of the most widely-used techniques to deal with multiple source aggregation. This lack of general classification scheme, or a guide to assist expert knowledge, leads to ambiguity or misreading for readers, who may be overwhelmed by the large amount of unclassified information currently available. To invert this situation, a general GDM framework is presented which divides and classifies all data aggregation techniques, focusing on and expanding the classification of experts’ weighting methods in terms of analysis type by carrying out an in-depth literature review. Results are not only classified but analysed and discussed regarding multiple characteristics, such as MCDMs in which they are applied, type of data used, ideal solutions considered or when they are applied. Furthermore, general requirements supplement this analysis such as initial influence, or component division considerations. As a result, this paper provides not only a general classification scheme and a detailed analysis of experts’ weighting methods but also a road map for researchers working on GDM topics or a guide for experts who use these methods. Furthermore, six significant contributions for future research pathways are provided in the conclusions.The first author acknowledges support from the Spanish Ministry of Universities [grant number FPU18/01471]. The second and third author wish to recognize their support from the Serra Hunter program. Finally, this work was supported by the Catalan agency AGAUR through its research group support program (2017SGR00227). This research is part of the R&D project IAQ4EDU, reference no. PID2020-117366RB-I00, funded by MCIN/AEI/10.13039/ 501100011033.Peer ReviewedElsevier20232023-08-0120232023-03-23journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2117/385395https://dx.doi.org/10.1016/j.inffus.2023.03.004reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)InglésengAgencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-117366RB-I00 ESTRATEGIAS DE VENTILACION OPTIMIZADAS CONSIDERANDO LA CALIDAD DEL AIRE INTERIOR, EL CONFORT TERMICO Y EL CONSUMO DE ENERGIA EN EDIFICIOS EDUCATIVOSopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2117/3853952026-05-27T15:37:01Z
dc.title.none.fl_str_mv A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme
title A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme
spellingShingle A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme
Boix Cots, David|||0000-0002-8462-8887
Decision making
Group decision-making
Multiple criteria group decision-making
Expert weights
MCGDM
MAGDM
Decisió, Presa de
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
title_short A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme
title_full A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme
title_fullStr A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme
title_full_unstemmed A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme
title_sort A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme
dc.creator.none.fl_str_mv Boix Cots, David|||0000-0002-8462-8887
Pardo Bosch, Francesc|||0000-0001-9532-8508
Pujadas Álvarez, Pablo|||0000-0001-5634-7431
author Boix Cots, David|||0000-0002-8462-8887
author_facet Boix Cots, David|||0000-0002-8462-8887
Pardo Bosch, Francesc|||0000-0001-9532-8508
Pujadas Álvarez, Pablo|||0000-0001-5634-7431
author_role author
author2 Pardo Bosch, Francesc|||0000-0001-9532-8508
Pujadas Álvarez, Pablo|||0000-0001-5634-7431
author2_role author
author
dc.subject.none.fl_str_mv Decision making
Group decision-making
Multiple criteria group decision-making
Expert weights
MCGDM
MAGDM
Decisió, Presa de
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
topic Decision making
Group decision-making
Multiple criteria group decision-making
Expert weights
MCGDM
MAGDM
Decisió, Presa de
Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica
description Interest in group decision-making (GDM) has been increasing prominently over the last decade. Access to global databases, sophisticated sensors which can obtain multiple inputs or complex problems requiring opinions from several experts have driven interest in data aggregation. Consequently, the field has been widely studied from several viewpoints and multiple approaches have been proposed. Nevertheless, there is a lack of general framework. Moreover, this problem is exacerbated in the case of experts’ weighting methods, one of the most widely-used techniques to deal with multiple source aggregation. This lack of general classification scheme, or a guide to assist expert knowledge, leads to ambiguity or misreading for readers, who may be overwhelmed by the large amount of unclassified information currently available. To invert this situation, a general GDM framework is presented which divides and classifies all data aggregation techniques, focusing on and expanding the classification of experts’ weighting methods in terms of analysis type by carrying out an in-depth literature review. Results are not only classified but analysed and discussed regarding multiple characteristics, such as MCDMs in which they are applied, type of data used, ideal solutions considered or when they are applied. Furthermore, general requirements supplement this analysis such as initial influence, or component division considerations. As a result, this paper provides not only a general classification scheme and a detailed analysis of experts’ weighting methods but also a road map for researchers working on GDM topics or a guide for experts who use these methods. Furthermore, six significant contributions for future research pathways are provided in the conclusions.
publishDate 2023
dc.date.none.fl_str_mv 2023
2023-08-01
2023
2023-03-23
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2117/385395
https://dx.doi.org/10.1016/j.inffus.2023.03.004
url https://hdl.handle.net/2117/385395
https://dx.doi.org/10.1016/j.inffus.2023.03.004
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Agencia Estatal de Investigación http://doi.org/10.13039/501100011033 Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020 PID2020-117366RB-I00 ESTRATEGIAS DE VENTILACION OPTIMIZADAS CONSIDERANDO LA CALIDAD DEL AIRE INTERIOR, EL CONFORT TERMICO Y EL CONSUMO DE ENERGIA EN EDIFICIOS EDUCATIVOS
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivatives 4.0 International
http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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