Linguistic group decision-making: opinion aggregation and measures of consensus

Authors:
D. Ben-Arieh;Z. Chen
Affiliations:
Dept. of Industrial and Manufacturing Systems Eng., Kansas State University, Manhattan, USA 66503;Dept. of Industrial and Manufacturing Systems Eng., Kansas State University, Manhattan, USA 66503
Venue:
Fuzzy Optimization and Decision Making
Year:
2006

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Abstract

Group decision-making is a crucial activity, necessary in many aspects of our civilization. In many cases, due to inherent complexity, experts cannot express their opinion or preferences using exact numbers, thus resorting to a qualitative preference such as linguistic labels. Another complicating factor is the fact that very seldom all individuals in a group share the same opinion about the alternatives. This creates the need to aggregate all the differing individual opinions into a group opinion. Moreover, it is desirable to be able to assess the level of agreement among the experts; termed consensus. This paper presents a methodology for aggregating experts' judgements, presented as linguistic labels, into a group opinion with a measure of the group consensus. The aggregation model allows weighted experts to express a degree of optimism or upward bias in their opinions. Then the paper presents two models of calculating the consensus based on the individual expert opinions and the group aggregated opinion.