Evaluating scales for pairwise comparisons

Abstract Pairwise comparisons have been a long-standing technique for comparing alternatives/criteria and their role has pivotal in the development of modern decision-making methods. The evaluation is very often done linguistically. Several scales proposed to translate linguistic into quantitative evaluation. In this paper, we perform an experiment investigate, under our methodological choices, which type scale provides best matching decision-maker’s verbal representation. aims evaluate suitability eight problems different sizes. We find that inverse linear representation whenever objective data are measured by means pairwise matrices suitable distance between applied computing error.