Combining Different Stakeholders’ Opinions in Multi-Criteria Decision Analyses Applying Partial Order Methodology

Abstract

Multi-criteria decision analyses (MCDA) for prioritizations may be performed applying a variety of available software, e.g., methods such as Analytic Network Process (ANP) and Elimination Et Choice Translating Reality (ELECTRE III) as recently suggested by Kalifa et al. In addition to a data matrix, usually based on indicators and designed for describing the parts of the framework intended for the MCDA, these methods require input of a variety of other parameters that are not necessarily immediately obtainable. Often the indicators are simply combined by a weighted sum to obtain a ranking score, which is supposed to reflect the opinion of a multitude of stakeholders. A single ranking score facilitates the decision as a unique ordering is obtained; however, such a ranking score masks potential conflicts that are expressed by the values of the single indicators. Beyond hiding the inherent conflicts, the problem arises that the weights, needed for summing up the indicator values are difficult to obtain or are even controversially discussed. Here we show a procedure, which takes care of potential different weighting schemes but nevertheless does not mask any inherent conflicts. Two examples are given, one with a small (traffic) system and one with a pretty large data matrix (food sustainability). The results show how decisions can be facilitated even taking a multitude of stakeholder opinions into account although conflicts are not necessarily completely eliminated as demonstrated in the second case.

Keywords

• partial ordering
• Hasse diagram
• generalized linear aggregation
• multi-criteria decision analyses
• weighting schemes