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Range-based Multi-Actor Multi-Criteria Analysis: A combined method of Multi-Actor Multi-Criteria Analysis and Monte Carlo simulation to support participatory decision making under uncertainty

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  • Gino Baudry

    (GEPEA - Laboratoire de génie des procédés - environnement - agroalimentaire - IUT Nantes - Institut Universitaire de Technologie - Nantes - UN - Université de Nantes - UN UFR ST - Université de Nantes - UFR des Sciences et des Techniques - UN - Université de Nantes - IUT Saint-Nazaire - Institut Universitaire de Technologie Saint-Nazaire - UN - Université de Nantes - EPUN - Ecole Polytechnique de l'Université de Nantes - UN - Université de Nantes - ONIRIS - École nationale vétérinaire, agroalimentaire et de l'alimentation Nantes-Atlantique - CNRS - Centre National de la Recherche Scientifique - UBL - Université Bretagne Loire - IMT Atlantique - IMT Atlantique - IMT - Institut Mines-Télécom [Paris] - IUT La Roche-sur-Yon - Institut Universitaire de Technologie - La Roche-sur-Yon - UN - Université de Nantes, LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - IEMN-IAE Nantes - Institut d'Économie et de Management de Nantes - Institut d'Administration des Entreprises - Nantes - UN - Université de Nantes)

  • Cathy Macharis

    (MOBI research group, ETEC Department, Vrije Universiteit Brussel - VUB - Vrije Universiteit Brussel)

  • Thomas Vallée

    (LEMNA - Laboratoire d'économie et de management de Nantes Atlantique - IEMN-IAE Nantes - Institut d'Économie et de Management de Nantes - Institut d'Administration des Entreprises - Nantes - UN - Université de Nantes)

Abstract

Concerns about environmental and social effects have made Multi-Criteria Decision Making (MCDM) increasingly popular. Decision making in complex contexts often – possibly always – requires addressing an aggregation of multiple issues to meet social, economic, legal, technical, and environmental objectives. These values at stake may affect different stakeholders through distributional effects characterized by a high and heterogeneous uncertainty that no social actors can completely control or understand. On this basis, we present a new process framework that aims to support participatory decision making under uncertainty: the range-based Multi-Actor Multi-Criteria Analysis (range-based MAMCA). On the one hand, the process framework explicitly considers stakeholders' objectives at an output level of aggregation. On the other hand, by means of a Monte Carlo analysis, the method also provides an exploratory scenario approach that enables the capture of the uncertainty, which stems from the complex context evolution. Range-based MAMCA offers a unique participatory process framework that enables us (1) to identify the alternatives pros and cons for each stakeholder group; (2) to provide probabilities about the risk of supporting mistaken, or at least ill-suited, decisions because of the uncertainty regarding to the decision-making context; (3) to take the decision-makers' limited control of the actual policy effects over the implementation of one or several options into account. The range-based MAMCA framework is illustrated by means of our first case study that aimed to assess French stakeholders' support for different biofuel options by 2030.

Suggested Citation

  • Gino Baudry & Cathy Macharis & Thomas Vallée, 2018. "Range-based Multi-Actor Multi-Criteria Analysis: A combined method of Multi-Actor Multi-Criteria Analysis and Monte Carlo simulation to support participatory decision making under uncertainty," Post-Print hal-03193653, HAL.
  • Handle: RePEc:hal:journl:hal-03193653
    DOI: 10.1016/j.ejor.2017.06.036
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