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Augmenting Ordinal Methods of Attribute Weight Approximation

Mats Danielson (), Love Ekenberg () and Ying He ()
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Mats Danielson: Department of Computer and Systems Sciences, Stockholm University, SE-164 40 Kista, Sweden
Love Ekenberg: Department of Computer and Systems Sciences, Stockholm University, SE-164 40 Kista, Sweden
Ying He: Department of Management Sciences, City University of Hong Kong, Kowloon, G7722 Hong Kong

Decision Analysis, 2014, vol. 11, issue 1, 21-26

Abstract: Multicriteria decision aid (MCDA) methods have been around for quite some time. However, the elicitation of preference information in MCDA processes and the lack of supporting practical means are problematic in real-life applications. Various proposals have been made for how to eliminate some of the obstacles and methods for introducing so-called surrogate weights have proliferated in the form of ordinal ranking methods for criteria weights. Considering the decision quality, one main problem is that the input information allowed in ordinal methods is sometimes too restricted. At the same time, decision makers often possess more background information, for example, regarding the relative strengths of the criteria, and might want to use that. We propose combined methods for facilitating the elicitation process and show how this provides a way to use partial information from the strength of preference judgment over weights in assessing weights for multiattribute utility functions.

Keywords: multicriteria decision analysis; criteria weights; criteria ranking; rank order (search for similar items in EconPapers)
Date: 2014
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