Integrating Cognitive Mapping Analysis into Multi-Criteria Decision Aiding

Amidou Kpoumié (), Sébastien Damart () and Alexis Tsoukiàs ()
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Amidou Kpoumié: LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique
Sébastien Damart: NIMEC - Normandie Innovation Marché Entreprise Consommation - UNICAEN - Université de Caen Normandie - NU - Normandie Université - ULH - Université Le Havre Normandie - NU - Normandie Université - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université - IRIHS - Institut de Recherche Interdisciplinaire Homme et Société - UNIROUEN - Université de Rouen Normandie - NU - Normandie Université
Alexis Tsoukiàs: LAMSADE - Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision - Université Paris Dauphine-PSL - PSL - Université Paris Sciences et Lettres - CNRS - Centre National de la Recherche Scientifique

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Abstract: Multi-criteria decision aiding (MCDA) is a process implying two distinctive actors (the client and the analyst) which aims at providing transparent and coherent support for complex decision situations, taking into account values of decision makers involved in a specific decision context. The theoretical framework of MCDA traditionally addresses problems involving a single decision maker. However, MCDA ought to investigate the case where the decision maker is made up of groups of individuals with conflicting interests. In contrast, cognitive mapping (CM) is frequently used in order to capture the values in a group of individuals and to reduce the antagonism between such values. Its ability to capture multiple values and reduce their conflicting aspects provides a rationale for decision problem analysis with multiple stakeholders. Nevertheless, capturing values by CM is not always intended for a subsequent multi-criteria analysis. This paper explores the integration of both techniques combining their respective strengths as well as their application in assessment of hydrogen technologies scenarios in terms of their perception and social acceptability by the general public.

Keywords: Multi-criteria decision aiding; Hydrogen technologies; Social acceptability; Problem structuring; Cognitive mapping; Value trees of objectives; Multi-criteria decision aiding. (search for similar items in EconPapers)
Date: 2012-05-08
Note: View the original document on HAL open archive server: https://hal.science/hal-00875480v1
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