Group Consensus Function Estimation When Preferences are Uncertain

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Abstract
Group decision making usually requires eliciting and then combining and reconciling the preferences of each member of a group. Based on the premise that preference responses are uncertain, this paper presents a weighting scheme for combining multicriteria individual preferences to obtain group preferences, called “consensus points.” The consensus points are “efficient” in that they have minimum variance associated with confidence intervals of assessment. An estimation technique uses the efficient consensus points (as values of the dependent variable) and attribute values of alternatives based on which the consensus is generated (as values of independent variables), to estimate the multicriteria consensus function. This approach is capable of testing both a generalized form of prospect theory and the hypothesis of correlation among group members' preferences. In an expository application of the method, we test these hypotheses and use a decision already made, as well as extreme points on which members unanimously agree, to check the plausibility of results obtained from estimated consensus functions.

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