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Peláez, J. I., Martínez, E. A., & Vargas, L. G. (2018). Consistency in positive reciprocal matrices: an improvement in measurement methods. IEEE Access, 6, 25600–25609. 
Added by: Klaus D. Goepel (06 Jun 2019 06:27:43 Asia/Singapore)   Last edited by: Klaus D. Goepel (10 Jun 2019 04:47:35 Asia/Singapore)
Resource type: Journal Article
DOI: 10.1109/ACCESS.2018.2829024
BibTeX citation key: 2018a
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Categories: AHP/ANP
Keywords: consistency, consistency index, eigenvalue, positiv reciprocal matrix, preference
Creators: Martínez, Peláez, Vargas
Collection: IEEE Access
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Consistency estimation of decision makers’ judgments in decision-making processes is fundamental to generating agreements and making decisions. AHP is a widely used method to solve this type of problem, enabling to evaluate the consistency of judgments emitted by the decision makers through the maximum eigenvalue of the matrix of judgments. In addition to the consistency index originally proposed in AHP, different indexes have been proposed in the literature, which use the minimum element of consistency. These indices that solve some of the original consistency index problems, present others that may question their usefulness. The purpose of this work is to propose a new index, as an improvement of the previous indexes. Among other characteristics, this new index is intuitive and easy to use, is bounded in the interval [0,1], proposes a critical value to accept or reject matrices, that depends on the size of the pairwise-comparison matrix, and can be extended to another type of pairwise-comparison scales. In addition, the probability distribution for the new index is defined, which enables to calculate the probability of a matrix being consistent, as a function of the critical acceptance value.
Added by: Klaus-admin  Last edited by: Klaus D. Goepel
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