SYNOPTIC ABSTRACT
The analytic hierarchy process is a popular and effective tool for multi-criteria decision making. It can be applied by a lone decision maker or by a group or team of decision makers. When a group of decision makers (DMs) is involved in an evaluation of alternatives with respect to criteria and sub-criteria, each DM produces a rating for each alternative. Of course, there may exist one or more DMs whose ratings deviate substantially from the other ratings. These outlier or extreme DMs can exert considerable influence on the overall ratings (and hence the ranking) of the alternatives, since the overall ratings are typically based on the arithmetic or geometric mean of the individual ratings. Two recent papers propose using a confidence-interval procedure for identifying extreme DMs. In this paper, we present two alternative procedures, one based on a multivariate test and the other based on visualization of the ratings. We discuss and illustrate how these new procedures improve upon the earlier procedure.
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