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Multiattribute Value Elicitation

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Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 261))

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.

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Acknowledgements

I would particularly like to acknowledge the many helpful comments of Luis Dias, many of which have been directly incorporated in the text.

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Authors and Affiliations

  1. University of Strathclyde, 16 Richmond St, Glasgow, G1 1XQ, UK

    Alec Morton

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  1. Alec Morton
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Correspondence to Alec Morton .

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Editors and Affiliations

  1. Faculty of Economics, CeBER and INESC Coimbra, University of Coimbra, Coimbra, Portugal

    Luis C. Dias

  2. Department of Management Science, University of Strathclyde, Scotland, United Kingdom

    Alec Morton

  3. Department of Management Science, University of Strathclyde, Scotland, United Kingdom

    John Quigley

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Morton, A. (2018). Multiattribute Value Elicitation. In: Dias, L., Morton, A., Quigley, J. (eds) Elicitation. International Series in Operations Research & Management Science, vol 261. Springer, Cham. https://doi.org/10.1007/978-3-319-65052-4_12

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