Using satisfaction analysis to predict decision quality
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/50524 |
Resumo: | One of the most important factors to determine the success of an organization is the quality of decisions made. In order to improve the decisions taken and to strengthen the competitiveness of organizations, systems such as Group Decision Support Systems (GDSS) have been strongly developed and studied in recent decades. The amount of GDSS incorporating automatic negotiation mechanisms, such as argumentation, is increasing nowadays. The evaluation of these mechanisms and the understanding of their real benefits for the organizations is still a hard challenge. In this article, we propose a model that allows a GDSS to measure the participant’s satisfaction with the decision, considering aspects such as problem evaluation, personality, emotions and expectations. To create the model some assumptions are deducted from literature, as well as the premises needed to validate any decision satisfaction model. This model is intended to enable the understanding of the decision’s quality achieved with an argumentation system and to evaluate its capability to potentiate the decision’s quality. The proposed model validates all the assumptions found in the literature regarding the participant’s satisfaction. |
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Using satisfaction analysis to predict decision qualityDecision SatisfactionGroup Decision Support SystemsOutcomesAffective ComputingEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e InformáticaOne of the most important factors to determine the success of an organization is the quality of decisions made. In order to improve the decisions taken and to strengthen the competitiveness of organizations, systems such as Group Decision Support Systems (GDSS) have been strongly developed and studied in recent decades. The amount of GDSS incorporating automatic negotiation mechanisms, such as argumentation, is increasing nowadays. The evaluation of these mechanisms and the understanding of their real benefits for the organizations is still a hard challenge. In this article, we propose a model that allows a GDSS to measure the participant’s satisfaction with the decision, considering aspects such as problem evaluation, personality, emotions and expectations. To create the model some assumptions are deducted from literature, as well as the premises needed to validate any decision satisfaction model. This model is intended to enable the understanding of the decision’s quality achieved with an argumentation system and to evaluate its capability to potentiate the decision’s quality. The proposed model validates all the assumptions found in the literature regarding the participant’s satisfaction.This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundação para a Ciência e a Tecnologia (Portuguese Foundation for Science and Technology) within project FCOMP-01-0124-FEDER-028980 (PTDC/EEISII/1386/2012) and SFRH/BD/89697/2012.info:eu-repo/semantics/publishedVersionCESER PublicationsUniversidade do MinhoCarneiro, JoãoMarreiros, GoretiNovais, Paulo20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/50524engCarneiro J., Marreiros G., Novais P., Using Satisfaction Analysis to Predict Decision Quality, International Journal of Artificial Intelligence (IJAI), CESER Publications, ISSN 0974-0635, Volume 13, Nº 1, pp 45-57, 2015.0974-0635http://www.ceser.in/ceserp/index.php/ijai/article/view/3525info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:37:30Zoai:repositorium.sdum.uminho.pt:1822/50524Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:33:49.164875Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Using satisfaction analysis to predict decision quality |
title |
Using satisfaction analysis to predict decision quality |
spellingShingle |
Using satisfaction analysis to predict decision quality Carneiro, João Decision Satisfaction Group Decision Support Systems Outcomes Affective Computing Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
title_short |
Using satisfaction analysis to predict decision quality |
title_full |
Using satisfaction analysis to predict decision quality |
title_fullStr |
Using satisfaction analysis to predict decision quality |
title_full_unstemmed |
Using satisfaction analysis to predict decision quality |
title_sort |
Using satisfaction analysis to predict decision quality |
author |
Carneiro, João |
author_facet |
Carneiro, João Marreiros, Goreti Novais, Paulo |
author_role |
author |
author2 |
Marreiros, Goreti Novais, Paulo |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Carneiro, João Marreiros, Goreti Novais, Paulo |
dc.subject.por.fl_str_mv |
Decision Satisfaction Group Decision Support Systems Outcomes Affective Computing Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
topic |
Decision Satisfaction Group Decision Support Systems Outcomes Affective Computing Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática |
description |
One of the most important factors to determine the success of an organization is the quality of decisions made. In order to improve the decisions taken and to strengthen the competitiveness of organizations, systems such as Group Decision Support Systems (GDSS) have been strongly developed and studied in recent decades. The amount of GDSS incorporating automatic negotiation mechanisms, such as argumentation, is increasing nowadays. The evaluation of these mechanisms and the understanding of their real benefits for the organizations is still a hard challenge. In this article, we propose a model that allows a GDSS to measure the participant’s satisfaction with the decision, considering aspects such as problem evaluation, personality, emotions and expectations. To create the model some assumptions are deducted from literature, as well as the premises needed to validate any decision satisfaction model. This model is intended to enable the understanding of the decision’s quality achieved with an argumentation system and to evaluate its capability to potentiate the decision’s quality. The proposed model validates all the assumptions found in the literature regarding the participant’s satisfaction. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015 2015-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/50524 |
url |
http://hdl.handle.net/1822/50524 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Carneiro J., Marreiros G., Novais P., Using Satisfaction Analysis to Predict Decision Quality, International Journal of Artificial Intelligence (IJAI), CESER Publications, ISSN 0974-0635, Volume 13, Nº 1, pp 45-57, 2015. 0974-0635 http://www.ceser.in/ceserp/index.php/ijai/article/view/3525 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
CESER Publications |
publisher.none.fl_str_mv |
CESER Publications |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799132857443024896 |