A range based Multi-Actor Multicriteria Analysis to incorporate uncertainty in stakeholder based evaluation processes

Gino Baudry (), Cathy Macharis () and Thomas Vallee
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Gino Baudry: 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: BUTO - Business Technology and Operations - VUB - Vrije Universiteit Brussel [Bruxelles]

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Abstract: Increasing concerns about environmental and social impacts have made multicriteria analysis (MCA) increasingly popular in decision making processes. The present paper proposes a new methodology which allows taking into account multicriteria aspects, stakeholder's preferences and long time horizon uncertainty. Relying on the MAMCA methodology developed by Macharis in 2000, we develop a new decision making support tool, the range based MAMCA. Within MAMCA, the different possible solutions or alternatives are evaluated on the objectives of the stakeholders. These evaluations can be however uncertain as there might be a lack of knowledge, lack of experience or future predications might be uncertain. By means of Monte Carlo Simulation a range based MAMCA approach is developed to generate several possible states of the world. While a classical MCA would have provided a single final ranking, encouraging the support of an alternative, which can either be the best or the worst one depending on its performance uncertainty in the long run. The range based MAMCA provides a wide range of possible rankings depending on the many possible states of the world. Thus, it provides scorings, rankings of alternatives and the probability they will occur. The new approach is described and shown by means of an illustrative case: the stakeholder support for different biofuel options.

Keywords: Multi-criteria analysis; decision making; multi-actor multi criteria analysis; uncertainty; sustainable development; Monte Carlo Simulation.; Monte Carlo Simulation (search for similar items in EconPapers)
Date: 2014-06-19
New Economics Papers: this item is included in nep-cmp and nep-ppm
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