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On a Consensus Measure in a Group Multi-Criteria Decision Making Problem

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  • Michele Fedrizzi

Abstract

A method for consensus measuring in a group decision problem is presented for the multiple criteria case. The decision process is supposed to be carried out according to Saaty's Analytic Hierarchy Process, and hence using pairwise comparison among the alternatives. Using a suitable distance between the experts' judgements, a scale transformation is proposed which allows a fuzzy interpretation of the problem and the definition of a consensus measure by means of fuzzy tools as linguistic quantifiers. Sufficient conditions on the expert's judgements are finally presented, which guarantee any a priori fixed consensus level to be reached.

Suggested Citation

  • Michele Fedrizzi, 2010. "On a Consensus Measure in a Group Multi-Criteria Decision Making Problem," DISA Working Papers 1009, Department of Computer and Management Sciences, University of Trento, Italy, revised 22 Dec 2010.
    • Handle: RePEc:trt:disawp:1009
    as

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    File URL: http://www.unitn.it/files/download/10528/9_2010.pdf
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    References listed on IDEAS

    as
    1. Thomas L. Saaty, 1986. "Axiomatic Foundation of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 32(7), pages 841-855, July.
    2. Patrick T. Harker & Luis G. Vargas, 1987. "The Theory of Ratio Scale Estimation: Saaty's Analytic Hierarchy Process," Management Science, INFORMS, vol. 33(11), pages 1383-1403, November.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    group decision making; multiple criteria; degree of consensus; fuzzy preferences;
    All these keywords.

    JEL classification:

    • D70 - Microeconomics - - Analysis of Collective Decision-Making - - - General
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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