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Indirect elicitation of non-linear multi-attribute utility functions. A dual procedure combined with DEA

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  • André, Francisco J.

Abstract

This paper proposes a non-interactive method to elicit non-linear multi-attribute utility functions which is based on duality results. The idea is to obtain a utility function which is compatible with the observed behavior of decision makers. The paper builds on a previous work by André and Riesgo [A non-interactive method to elicit non-linear multi-attribute utility functions. Theory and application to agricultural economics. European Journal of Operational Research 2008;181:793-807] but it eliminates an important shortcoming: the necessity to have an analytical expression of the efficient set or an estimation of it. The alternative approach presented in this paper consists in using a method of projection onto the true efficient set, based on data envelopment analysis (DEA). In a simulation exercise we check the ability of the method to recover true preference parameters in the presence of errors made by decision makers.

Suggested Citation

  • André, Francisco J., 2009. "Indirect elicitation of non-linear multi-attribute utility functions. A dual procedure combined with DEA," Omega, Elsevier, vol. 37(4), pages 883-895, August.
  • Handle: RePEc:eee:jomega:v:37:y:2009:i:4:p:883-895
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    References listed on IDEAS

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    1. Johri, Pravin K., 1994. "Derivation of duality in mathematical programming and optimization theory," European Journal of Operational Research, Elsevier, vol. 73(3), pages 547-554, March.
    2. Jiménez, Antonio & Mateos, Alfonso & Ríos-Insua, Sixto, 2009. "Missing consequences in multiattribute utility theory," Omega, Elsevier, vol. 37(2), pages 395-410, April.
    3. Sumpsi, JoseMaria & Amador, Francisco & Romero, Carlos, 1997. "On farmers' objectives: A multi-criteria approach," European Journal of Operational Research, Elsevier, vol. 96(1), pages 64-71, January.
    4. Canbolat, Yavuz Burak & Chelst, Kenneth & Garg, Nitin, 2007. "Combining decision tree and MAUT for selecting a country for a global manufacturing facility," Omega, Elsevier, vol. 35(3), pages 312-325, June.
    5. Tiwari, D. N. & Loof, R. & Paudyal, G. N., 1999. "Environmental-economic decision-making in lowland irrigated agriculture using multi-criteria analysis techniques," Agricultural Systems, Elsevier, vol. 60(2), pages 99-112, May.
    6. Johri, Pravin K., 1993. "Implied constraints and a unified theory of duality in linear and nonlinear programming," European Journal of Operational Research, Elsevier, vol. 71(1), pages 61-69, November.
    7. P. L. Yu, 1973. "A Class of Solutions for Group Decision Problems," Management Science, INFORMS, vol. 19(8), pages 936-946, April.
    8. Brugha, Cathal M., 2004. "Phased multicriteria preference finding," European Journal of Operational Research, Elsevier, vol. 158(2), pages 308-316, October.
    9. Gomez-Limon, J. A. & Berbel, J., 2000. "Multicriteria analysis of derived water demand functions: a Spanish case study," Agricultural Systems, Elsevier, vol. 63(1), pages 49-72, January.
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    Cited by:

    1. Hatami-Marbini, Adel & Tavana, Madjid, 2011. "An extension of the Electre I method for group decision-making under a fuzzy environment," Omega, Elsevier, vol. 39(4), pages 373-386, August.
    2. André, Francisco J. & Herrero, Inés & Riesgo, Laura, 2010. "A modified DEA model to estimate the importance of objectives with an application to agricultural economics," Omega, Elsevier, vol. 38(5), pages 371-382, October.
    3. Odeck, James, 2009. "Statistical precision of DEA and Malmquist indices: A bootstrap application to Norwegian grain producers," Omega, Elsevier, vol. 37(5), pages 1007-1017, October.
    4. Kanellopoulos, A. & Gerdessen, J.C. & Claassen, G.D.H., 2015. "Compromise programming: Non-interactive calibration of utility-based metrics," European Journal of Operational Research, Elsevier, vol. 244(2), pages 519-524.
    5. Hinojosa, M.A. & Mármol, A.M., 2011. "Axial solutions for multiple objective linear problems. An application to target setting in DEA models with preferences," Omega, Elsevier, vol. 39(2), pages 159-167, April.

    More about this item

    Keywords

    Multi-criteria Decision making Data envelopment analysis (DEA);

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles

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