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Using Satisfaction Analysis to Predict Decision Quality
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.
Decision Satisfaction, Group Decision Support Systems, Outcomes, Affective Computing.
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