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Koczkodaj, W. W. (2016). Pairwise comparisons rating scale paradox. In N. T. Nguyen & R. Kowalczyk (Eds), Transactions on Computational Collective Intelligence Vol. 9655, (pp. 1–9).Springer. Added by: Klaus-admin (08 Jun 2019 02:13:23 Asia/Singapore) Last edited by: Klaus-admin (08 Jun 2019 02:18:52 Asia/Singapore) |
| Resource type: Book Chapter Number DOI: 10.1007/978-3-662-49619-0_1 BibTeX citation key: Koczkodaj2016 Email resource to friend View all bibliographic details  |
Categories: AHP/ANP, Decision Making Keywords: Analytic Hierarchy Process (AHP), inconsistency, pairwise comparison matrix, pairwise comparisons, scale, scale functions Creators: Koczkodaj, Kowalczyk, Nguyen Publisher: Springer Collection: Transactions on Computational Collective Intelligence |
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| Abstract |
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This study demonstrates that incorrect data are entered into a pairwise comparisons matrix for processing into weights for the data collected by a rating scale. Unprocessed rating scale data lead to a paradox. A solution to it, based on normalization, is proposed. This is an essential correction for virtually all pairwise comparisons methods using rating scales. The illustration of the relative error, currently taking place in numerous publications, is discussed.
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| Notes |
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Lecture Notes in Computer Science
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