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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
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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
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.
  
Notes
Lecture Notes in Computer Science
  
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