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The value of additional information in multicriteria decision making choice problems with information imperfections

Author

Listed:
  • Sarah Ben Amor

    (University of Ottawa)

  • Kazimierz Zaras

    (UQAT)

  • Ernesto A. Aguayo

    (Technical University of Madrid (UPM))

Abstract

Processing information is a key ingredient for decision making. In most decision-making cases, information is distributed across various sources that may differ in reliability and accuracy. Various sources and kinds of uncertainty are encountered in the same decision situation. “Information imperfections” is a general term that encompasses all kinds of “deficiencies” (such as uncertainty, imprecision, ambiguity, incompleteness) that may affect the quality of information at hand. In discrete multicriteria decision making, where several alternatives are assessed according to heterogeneous and conflicting criteria, information used to assess such alternatives can also be imperfect. It is rather natural, in such a context, to seek additional information to reduce these imperfections. This paper aims at extending the Bayesian model for assessing the value of additional information to multicriteria decision analysis in a context of imperfect information. A unified procedure for processing additional information has been proposed in a previous work. It leads to prior and posterior global preference relational systems. It will be extended here to include pre-posterior analysis where concepts such as the expected value of perfect information and the expected value of imperfect information are adapted to multicriteria decision making choice problems.

Suggested Citation

  • Sarah Ben Amor & Kazimierz Zaras & Ernesto A. Aguayo, 2017. "The value of additional information in multicriteria decision making choice problems with information imperfections," Annals of Operations Research, Springer, vol. 253(1), pages 61-76, June.
    • Handle: RePEc:spr:annopr:v:253:y:2017:i:1:d:10.1007_s10479-016-2318-x
    DOI: 10.1007/s10479-016-2318-x
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    References listed on IDEAS

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    1. James S. Dyer & Rakesh K. Sarin, 1979. "Measurable Multiattribute Value Functions," Operations Research, INFORMS, vol. 27(4), pages 810-822, August.
    2. Amor, Sarah Ben & Jabeur, Khaled & Martel, Jean-Marc, 2007. "Multiple criteria aggregation procedure for mixed evaluations," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1506-1515, September.
    3. David M. Pennock & Michael P. Wellman, 2005. "Graphical Models for Groups: Belief Aggregation and Risk Sharing," Decision Analysis, INFORMS, vol. 2(3), pages 148-164, September.
    4. Munda, G. & Nijkamp, P. & Rietveld, P., 1995. "Qualitative multicriteria methods for fuzzy evaluation problems: An illustration of economic-ecological evaluation," European Journal of Operational Research, Elsevier, vol. 82(1), pages 79-97, April.
    5. Durbach, Ian N. & Stewart, Theodor J., 2012. "Modeling uncertainty in multi-criteria decision analysis," European Journal of Operational Research, Elsevier, vol. 223(1), pages 1-14.
    6. Samson, D. & Wirth, A. & Rickard, J., 1989. "The value of information from multiple sources of uncertainty in decision analysis," European Journal of Operational Research, Elsevier, vol. 39(3), pages 254-260, April.
    7. Dennis V. Lindley, 1986. "The Reconciliation of Decision Analyses," Operations Research, INFORMS, vol. 34(2), pages 289-295, April.
    8. Zaras, Kazimierz, 2004. "Rough approximation of a preference relation by a multi-attribute dominance for deterministic, stochastic and fuzzy decision problems," European Journal of Operational Research, Elsevier, vol. 159(1), pages 196-206, November.
    9. Azondekon, Sebastien H. & Martel, Jean-Marc, 1999. ""Value" of additional information in multicriterion analysis under uncertainty," European Journal of Operational Research, Elsevier, vol. 117(1), pages 45-62, August.
    10. Clemon, Robert T & Winkler, Robert L, 1986. "Combining Economic Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 4(1), pages 39-46, January.
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