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Incomparable: What Now, IV. Incomparabilities: A Modeling Challenge

  • Rainer Bruggemann
  • Lars Carlsen
  • Paola Annoni
Chapter

Abstract

When a mutual ranking of a selection of objects is wanted, an initial step is the development of a multi-indicator system (MIS). Many MCDA concepts, e.g., members of the ELECTRE-family or of the different PROMETHEE versions, are available for obtaining rankings from an MIS. On the one side, a major disadvantage applying these models is the need for additional parameters beyond the data matrix, whereas Partial Order Theory is a methodology that allows extracting ranking information from a data matrix without additional, often subjective and consequently questionable parameters. On the other side, additional parameters help decision-making by introducing knowledge for decision makers/stakeholders beyond the data matrix. The present study focuses on the question to what extent an MIS can be modeled within the framework of partial order theory to add knowledge similarly to the MCDA approaches. Of all the possible alternatives, applying weight intervals to the indicators system is here discussed.

Keywords

Monte Carlo Partial Order Composite Indicator Weight Combination Weak Order 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of EcohydrologyLeibniz—Institute of Freshwater Ecology and Inland FisheriesBerlinGermany
  2. 2.Awareness CenterRoskildeDenmark
  3. 3.Economic Analysis UnitEuropean Commission-Directorate General for Regional and Urban PolicyBrusselsBelgium

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