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Modeling the Conflict Within Group Decision Making: A Comparison Between Methods that Require and Do Not Require the Use of Preference Aggregation Techniques

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Group Decision and Negotiation: Behavior, Models, and Support (GDN 2019)

Abstract

This paper compares MCDM methods that require and do not require the use of aggregation techniques for their application within group decision making process and study the associated concern regarding the possibility of underestimation of conflicts. An experiment was adapted from previous research and three MCDM methods (TOPSIS, TOPSIS for group, a method based on game theory) were empirically compared based on the performance of these methods to predict correctly the agreement reached by the group. A criterion was established to be used as a performance indicator, which was the counting of the matches between the agreements of the group (if reached) with the solution of the MCDM method. It was very strong the difference in matches between the methods that require and do not require the use of preference aggregation techniques, which seems to corroborate the affirmation that modeling the conflict by using a more adequate methodology for dealing with conflictive scenarios provides best efficiency in predicting group decision making outcomes.

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Acknowledgments

The authors thank the São Paulo Research Foundation (FAPESP) for Regular Research Grant (2016/03722-5).

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Correspondence to Alexandre Bevilacqua Leoneti .

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Leoneti, A.B., Ziotti, V.C. (2019). Modeling the Conflict Within Group Decision Making: A Comparison Between Methods that Require and Do Not Require the Use of Preference Aggregation Techniques. In: Morais, D., Carreras, A., de Almeida, A., Vetschera, R. (eds) Group Decision and Negotiation: Behavior, Models, and Support. GDN 2019. Lecture Notes in Business Information Processing, vol 351. Springer, Cham. https://doi.org/10.1007/978-3-030-21711-2_5

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  • DOI: https://doi.org/10.1007/978-3-030-21711-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-21710-5

  • Online ISBN: 978-3-030-21711-2

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