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A comparative study on precision of pairwise comparison matrices

Author

Listed:
  • Bice Cavallo

    (University of Naples Federico II)

  • Jir̆í Mazurek

    (Silesian University in Opava)

  • Jaroslav Ramík

    (Silesian University in Opava)

Abstract

Pairwise comparisons have been a long-standing technique for comparing alternatives/criteria and their role has been pivotal in the development of modern decision-making methods such as the Analytic Hierarchy/Network Process (AHP/ANP), the Best-Worst method (BWM), PROMETHEE and many others. Pairwise comparisons can be performed within several frameworks such as multiplicative, additive and fuzzy representations of preferences, which are particular instances of a more general framework based on Abelian linearly ordered groups. Though multiplicative, additive and fuzzy representations of preferences are widely used in practice, it is unknown whether decision makers are equally precise in the three aforementioned representations when they measure objective data. Therefore, the aim of this paper is to design, carry out and analyse an experiment with over 200 respondents (undergraduate university students) from two countries, Czechia and Italy, to compare precision of the respondents in all three representations. In the experiment, respondents pairwise compared (by approximation) the areas of four geometric figures and then, the imprecision of their assessments was measured by computing the distance with the exact pairwise comparisons. We grouped the respondents in such a way that each participant was allowed to deal with a unique type of representation. The outcomes of the experiment indicate that the multiplicative approach is the most precise.

Suggested Citation

  • Bice Cavallo & Jir̆í Mazurek & Jaroslav Ramík, 2024. "A comparative study on precision of pairwise comparison matrices," Fuzzy Optimization and Decision Making, Springer, vol. 23(2), pages 179-198, June.
    • Handle: RePEc:spr:fuzodm:v:23:y:2024:i:2:d:10.1007_s10700-023-09416-4
    DOI: 10.1007/s10700-023-09416-4
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