A framework of incorporating confidence levels to deal with uncertainty in pairwise comparisons

Georgia Dede (), Thomas Kamalakis () and Dimosthenis Anagnostopoulos ()
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Georgia Dede: Harokopio University
Thomas Kamalakis: Harokopio University
Dimosthenis Anagnostopoulos: Harokopio University

Central European Journal of Operations Research, 2022, vol. 30, issue 3, No 9, 1069 pages

Abstract: Abstract Pairwise comparison is a key ingredient in multi-criteria decision analysis. The method is based on a set of comparisons conducted by a group of experts, comparing all possible pairs of alternatives involved in the decision process. The outcome is the estimation of weights determining the ranking of alternatives. In this paper, we introduce a new framework for the incorporation of confidence levels in pairwise comparisons, in order to deal with uncertainty issues related to the individual expert judgments. We discuss how the confidence levels can be related to the probability of rank reversal by introducing a theoretical model based on the multivariate normal cumulative distribution function. A comparison between theoretical and numerical results (Monte Carlo simulations), reveals a very good agreement. The proposed framework may provide a very good basis for pairwise comparison extensions aiming to provide further information regarding the accuracy for the evaluation of the final outcome.

Keywords: Multiple criteria analysis; Decision analysis; Pairwise comparisons; Confidence levels (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10100-020-00735-0

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