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Elicitation of multiattribute value functions through high dimensional model representations: Monotonicity and interactions

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  • Beccacece, Francesca
  • Borgonovo, Emanuele
  • Buzzard, Greg
  • Cillo, Alessandra
  • Zionts, Stanley

Abstract

This work addresses the early phases of the elicitation of multiattribute value functions proposing a practical method for assessing interactions and monotonicity. We exploit the link between multiattribute value functions and the theory of high dimensional model representations. The resulting elicitation method does not state any a-priori assumption on an individual’s preference structure. We test the approach via an experiment in a riskless context in which subjects are asked to evaluate mobile phone packages that differ on three attributes.

Suggested Citation

  • Beccacece, Francesca & Borgonovo, Emanuele & Buzzard, Greg & Cillo, Alessandra & Zionts, Stanley, 2015. "Elicitation of multiattribute value functions through high dimensional model representations: Monotonicity and interactions," European Journal of Operational Research, Elsevier, vol. 246(2), pages 517-527.
  • Handle: RePEc:eee:ejores:v:246:y:2015:i:2:p:517-527
    DOI: 10.1016/j.ejor.2015.04.042
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    References listed on IDEAS

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    Cited by:

    1. Ben Abdallah, N. & Destercke, S. & Sallak, M., 2017. "Easy and optimal queries to reduce set uncertainty," European Journal of Operational Research, Elsevier, vol. 256(2), pages 592-604.
    2. Ghaderi, Mohammad & Ruiz, Francisco & Agell, Núria, 2017. "A linear programming approach for learning non-monotonic additive value functions in multiple criteria decision aiding," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1073-1084.

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