Utilize este identificador para referenciar este registo: https://hdl.handle.net/1822/68812

TítuloPredicting satisfaction: perceived decision quality by decision-makers in Web-based group decision support systems
Autor(es)Carneiro, João
Saraiva, Pedro
Conceicao, Luis
Santos, Ricardo
Marreiros, Goreti
Novais, Paulo
Palavras-chaveGroup decision support systems
Decision satisfaction
Decision quality
Outcomes
Affective computing
Data2019
EditoraElsevier Science BV
RevistaNeurocomputing
Resumo(s)In future, the organizations' likelihood to endure and succeed will depend greatly on the quality of every decision made. It is known that most decisions in organizations are made in group. With the purpose of supporting decision-makers anytime and anywhere, Web-based Group Decision Support Systems (GDSS) have been studied. The amount of Web-based GDSS incorporating automatic negotiation mechanisms such as argumentation has been steadily increasing. Usually, these systems/models are evaluated through mathematical proofs, number of rounds or seconds to propose (reach) a solution. However, those techniques are not very informative in terms of the decision quality. Here, we propose a model that intends to predict the decision-makers' satisfaction (perception of the decision quality), specifically designed to deal with multi-criteria problems. Our model considers aspects such as: meeting's outcomes, decision-maker's intentions, expectations and emotional cost. To validate the proposed model in terms of its ability to predict decision-makers' satisfaction, we developed a prototype of a Web-based GDSS to be used in a case study where the participant had to make a joint decision. The decision process consisted in a set of 5 rounds, where the participant could (re) configure his/her preferences along the process. The satisfaction model ascertained its ability to predict the participants' satisfaction and allowed to understand that (as is stated in the literature) the inclusion of cognitive and emotional variables is essential to evaluate satisfaction more accurately.
TipoArtigo
URIhttps://hdl.handle.net/1822/68812
DOI10.1016/j.neucom.2018.05.126
ISSN0925-2312
Versão da editorahttps://www.sciencedirect.com/science/article/abs/pii/S0925231219300104
Arbitragem científicayes
AcessoAcesso aberto
Aparece nas coleções:CAlg - Artigos em revistas internacionais / Papers in international journals


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