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Inconsistency thresholds for incomplete pairwise comparison matrices – Publication by Kolos Csaba Ágoston and László Csató

2022-05-16 14:28:43

The article co-authored by Kolos Csaba Ágoston and László Csató was published in the Omega – International Journal of Management Science.
Corvinus Épület

Pairwise comparison matrices are increasingly used in settings where some pairs are missing. However, there exist few inconsistency indices for similar incomplete data sets and no reasonable measure has an associated threshold. This paper generalises the famous rule of thumb for the acceptable level of inconsistency, proposed by Saaty, to incomplete pairwise comparison matrices. The extension is based on choosing the missing elements such that the maximal eigenvalue of the incomplete matrix is minimised. Consequently, the well-established values of the random index cannot be adopted: the inconsistency of random matrices is found to be the function of matrix size and the number of missing elements, with a nearly linear dependence in the case of the latter variable. Our results can be directly built into decision-making software and used by practitioners as a statistical criterion for accepting or rejecting an incomplete pairwise comparison matrix. 

Ágoston Kolos Csaba kolos.agoston@uni-corvinus.hu Rektori Szervezet / Operáció és Döntés Intézet / Operációkutatás és Aktuáriustudományok Tanszék
Tanszékvezető, Egyetemi docens / Head of Department, Associate Professor
E épület, 132
Dr. Csató László laszlo.csato@uni-corvinus.hu Rektori Szervezet / Operáció és Döntés Intézet / Operációkutatás és Aktuáriustudományok Tanszék
Egyetemi Docens / Associate Professor
E épület, 122
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