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Multiattribute Value Elicitation

In: Elicitation

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  • Alec Morton

    (University of Strathclyde)

Abstract

Multiattribute Value Theory (MAVT) methods are perhaps the most intuitive multicriteria methods, and have the most theoretically well-understood basis. They are employ a divide-and-conquer modelling strategy in which the value of an option is conceptualised as a function (typically the sum) of the scores associated with the performance of the option on different attributes. This chapter outlines the concept of preferential independence, which has a critical underpinning role of elicitation within the MAVT paradigm. I also present MAVT elicitation in the context of the overall Decision Analysis process, comprising three broad stages: Designing and Planning; Structuring the Model; and Analysing the Model. I outline some of the main practical methods for arriving at the partial values and weighting them to arrive at an overall value score, including both traditional methods relying on cardinal assessment, and the MACBETH approach which uses qualitative difference judgements. A running example of a house choice problem is used to illustrate the different elicitation approaches.

Suggested Citation

  • Alec Morton, 2018. "Multiattribute Value Elicitation," International Series in Operations Research & Management Science, in: Luis C. Dias & Alec Morton & John Quigley (ed.), Elicitation, chapter 0, pages 287-311, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-65052-4_12
    DOI: 10.1007/978-3-319-65052-4_12
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    Cited by:

    1. Cinelli, Marco & Kadziński, Miłosz & Miebs, Grzegorz & Gonzalez, Michael & Słowiński, Roman, 2022. "Recommending multiple criteria decision analysis methods with a new taxonomy-based decision support system," European Journal of Operational Research, Elsevier, vol. 302(2), pages 633-651.
    2. Gabriela D. Oliveira & Luis C. Dias, 2020. "The potential learning effect of a MCDA approach on consumer preferences for alternative fuel vehicles," Annals of Operations Research, Springer, vol. 293(2), pages 767-787, October.

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