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Usability of concordance indices in FAST-GDM problems

Abstract:

A flexible attribute-set group decision-making (FAST-GDM) problem boils down to finding the most suitable option(s) with a general agreement among the participants in a decision-making process in which each option can be described by a flexible collection of attributes. The solution to such a problem can involve a consensus reaching process (CRP) in which the participants iteratively try to reach a general agreement on the best option(s) based on the attributes that are relevant for each participant. A challenging task in a CRP is the selection of an adequate method to determine the level of concordance between the evaluations given by each participant and the collective evaluations computed for the group. To gain insights in this regard, we performed a pilot test in which a group of persons were asked to estimate the level of concordance between individual and collective evaluations obtained while other participants tried to solve a FAST-GDM problem. The perceived concordance levels were compared with several theoretical concordance indices based on similarity measures designed to compare intuitionistic fuzzy sets. This paper presents our findings on how each of the chosen theoretical concordance indices reflected the perceived concordance levels.