Concordance and consensus

C.H. Elzinga, H. Wang, Z. Lin, Y. Kumar

Research output: Contribution to JournalArticleAcademicpeer-review


This paper deals with the measurement of concordance and the construction of consensus in preference data, either in the form of preference rankings or in the form of response distributions with Likert-items. We propose a set of axioms of concordance in preference orderings and a new class of concordance measures. The measures outperform classic measures like Kendall's τ and W and Spearman's ρ in sensitivity and apply to large sets of orderings instead of just to pairs of orderings. For sets of N orderings of n items, we present very efficient and flexible algorithms that have a time complexity of only O(Nn
Original languageEnglish
Pages (from-to)2529-2549
Number of pages20
JournalInformation Sciences
Publication statusPublished - 2011


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