Preference Sensitivity Analyses for Multi-Attribute Decision Support

Contributing to transparency and traceability of decision making processes and taking into account the preferences of the decision makers, multi-criteria decision analysis (MCDA) is suitable to bring together knowledge from different disciplines and fields of expertise. The modelling of the decision makers’ preferences is a crucial part of any multi-criteria analysis. In multi-attribute value theory (MAVT), preferential information is modelled by weighting factors (i.e. inter-criteria comparisons) and value functions (i.e. intra-criteria preferences). However, the uncertainties associated with the determination of these preferential parameters are often underestimated. Thus, the focus of this paper is the description of an approach to explore the impact of simultaneous variations of these subjective parameters. Special attention is paid to the consideration of variations of the value functions’ shapes. The aim of the presented methods is to facilitate the process of preference modelling and to comprehensibly visualise and communicate the impact of the preferential uncertainties on the results of the decision analysis.