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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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    Cited by:

    1. Pérez-Blanco, C. D & Standardi, G., 2019. "Farm waters run deep: a coupled positive multi-attribute utility programming and computable general equilibrium model to assess the economy-wide impacts of water buyback," Agricultural Water Management, Elsevier, vol. 213(C), pages 336-351.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Kourtesi, Sofia & De Witte, Kristof & Polymeros, Apostolos, 2016. "Technical Efficiency in the Agricultural Sector - Evidence from a Conditional Quantile-Based Approach," Agricultural Economics Review, Greek Association of Agricultural Economists, vol. 17(2), June.
    8. Gómez-Limón, José A. & Gutiérrez-Martín, Carlos & Riesgo, Laura, 2016. "Modeling at farm level: Positive Multi-Attribute Utility Programming," Omega, Elsevier, vol. 65(C), pages 17-27.

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    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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