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Macbeth

Author

Listed:
  • CARLOS A. BANA E COSTA

    (Centre for Management Studies of Instituto Superior Técnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon, Portugal)

  • JEAN-MARIE DE CORTE

    (Centre de Recherche Warocqué, Université de Mons, Place du Parc, 20, 7000 Mons, Belgium)

  • JEAN-CLAUDE VANSNICK

    (Centre de Recherche Warocqué, Université de Mons, Place du Parc, 20, 7000 Mons, Belgium)

Abstract

This paper presents an up-to-date comprehensive overview of the MACBETH approach to multicriteria decision-aid. It requires only qualitative judgements about differences of attractiveness to help a decision maker, or a decision-advisory group, quantify the relative value of options. The approach, based on the additive value model, aims to support interactive learning about evaluation problems and the elaboration of recommendations to prioritize and select options in individual or group decision making processes. A case study based on a real-world application of MACBETH for multicriteria value measurement of IT solutions is presented. It shows how the M-MACBETH decision support system can be used in practice to construct an additive evaluation model. The paper addresses key issues related to structuring the model, building value scales, weighting criteria and sensitivity and robustness analyzes. Reference is also made to applications of MACBETH reported in the scientific literature.

Suggested Citation

  • Carlos A. Bana E Costa & Jean-Marie De Corte & Jean-Claude Vansnick, 2012. "Macbeth," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 11(02), pages 359-387.
  • Handle: RePEc:wsi:ijitdm:v:11:y:2012:i:02:n:s0219622012400068
    DOI: 10.1142/S0219622012400068
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    References listed on IDEAS

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    1. JosÉ Figueira & Salvatore Greco & Matthias Ehrogott, 2005. "Multiple Criteria Decision Analysis: State of the Art Surveys," International Series in Operations Research and Management Science, Springer, number 978-0-387-23081-8, April.
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