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Selecting numerical scales for pairwise comparisons

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  • Elliott, Michael A.

Abstract

It is often desirable in decision analysis problems to elicit from an individual the rankings of a population of attributes according to the individual's preference and to understand the degree to which each attribute is preferred to the others. A common method for obtaining this information involves the use of pairwise comparisons, which allows an analyst to convert subjective expressions of preference between two attributes into numerical values indicating preferences across the entire population of attributes. Key to the use of pairwise comparisons is the underlying numerical scale that is used to convert subjective linguistic expressions of preference into numerical values. This scale represents the psychological manner in which individuals perceive increments of preference among abstract attributes and it has important implications about the distribution and consistency of an individual's preferences. Three popular scale types, the traditional integer scales, balanced scales and power scales are examined. Results of a study of 64 individuals responding to a hypothetical decision problem show that none of these scales can accurately capture the preferences of all individuals. A study of three individuals working on an actual engineering decision problem involving the design of a decay heat removal system for a nuclear fission reactor show that the choice of scale can affect the preferred decision. It is concluded that applications of pairwise comparisons would benefit from permitting participants to choose the scale that best models their own particular way of thinking about the relative preference of attributes.

Suggested Citation

  • Elliott, Michael A., 2010. "Selecting numerical scales for pairwise comparisons," Reliability Engineering and System Safety, Elsevier, vol. 95(7), pages 750-763.
  • Handle: RePEc:eee:reensy:v:95:y:2010:i:7:p:750-763
    DOI: 10.1016/j.ress.2010.02.013
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    Cited by:

    1. Corrente, Salvatore & Greco, Salvatore & Ishizaka, Alessio, 2016. "Combining analytical hierarchy process and Choquet integral within non-additive robust ordinal regression," Omega, Elsevier, vol. 61(C), pages 2-18.
    2. Bice Cavallo & Alessio Ishizaka, 2023. "Evaluating scales for pairwise comparisons," Annals of Operations Research, Springer, vol. 325(2), pages 951-965, June.
    3. Turan Arslan, 2017. "A Weighted Euclidean Distance based TOPSIS Method for Modeling Public Subjective Judgments," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(03), pages 1-18, June.

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