A non-interactive elicitation method for non-linear multiattribute utility functions: Theory and application to agricultural economics

André, Francisco J.; Riesgo, Laura

doi:10.1016/j.ejor.2006.06.020

Cited by 28 publications

(28 citation statements)

References 39 publications

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“…Despite the fact that additive utility function is associated with the assumption of somewhat restrictive conditions [33], this functional form may be considered as an approximation to the real utility function under certain conditions [45]. In any case, non-linear utility functions such as linear-multiplicative [37] or power functions [39,46] seem to be better approximations to the real utility function.…”

Section: Selecting the Mauf Functional Form And Eliciting Mauf Paramementioning

confidence: 99%

“…This implies that any linear combination of the points of the pay-off matrix was (incorrectly) considered to belong to the efficient set, and thus would be wrongly eligible to be the "optimum" solution for eliciting farmers' MAUF. André and Riesgo [37] developed a more accurate approximation of the efficient set by regressing a hyper-plane on the basis of a limited number of efficient points included in the compromise set, as a subset of the whole efficient set interpreted as the "landing area" for the utility curve [34,41]. However, as the authors themselves noted, this approach also results in approximation errors, since the points belonging to the regressed hyper-plane may not belong to the actual efficient set.…”

Section: Defining the Efficient Setmentioning

confidence: 99%

“…In this paper, we decided to follow this last approach, identifying the ideal and anti-ideal values in the pay-off matrix (see Section 3 for details on the pay-off matrix calculation). Due to this selection, and in order to bound attributes between 0 and 1, the anti-ideal value is also included in the numerator as a reference (see [37] for an application of this normalization process).…”

Section: Model Buildingmentioning

confidence: 99%

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Modeling at farm level: Positive Multi-Attribute Utility Programming

Gómez‐Limón

Gutiérrez‐Martín

Riesgo

2016

Omega

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This article proposes a new mathematical programming model for the simulation of farmers' decision-making. We have developed a model based on a multi-attribute utility approach that takes into consideration the most relevant attributes of farmers within a positive framework.This approach overcomes the limitations found in some mathematical models used in the literature to simulate farmers' behavior. A five-step procedure is presented in order to elicit the utility function that reproduces farmers' current decision-making. We illustrate this positive multi-attribute approach using a sample of farmers in an irrigated area in southern Spain, where our simulations demonstrate the accurateness of the model in reproducing actual farmers' decision-making. We also find evidence that the model is able to explain the heterogeneous behavior of farmers within a homogeneous agricultural system.

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Section: Selecting the Mauf Functional Form And Eliciting Mauf Paramementioning

confidence: 99%

Section: Defining the Efficient Setmentioning

confidence: 99%

Section: Model Buildingmentioning

confidence: 99%

See 1 more Smart Citation

Modeling at farm level: Positive Multi-Attribute Utility Programming

Gómez‐Limón

Gutiérrez‐Martín

Riesgo

2016

Omega

Self Cite

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“…The projection method reduces the approximation error as compared to other alternatives (André et al 2010;André and Riesgo 2007), but still yields an error that is measured by using calibration residuals (see next section).…”

Section: Efficient Frontier and Tangency Pointmentioning

confidence: 99%

Economic Impacts of Irrigation-Constrained Agriculture in the Lower Po Basin

Pérez-Blanco

Koks

Calliari

et al. 2018

Water Econs. Policy

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Climate change, increasing demand for water, higher environmental standards and inelastic water supply suggest that future drought response in Southern Europe would require more efficient management of water use. In this context, there is a pressing need for a better understanding of the economic impacts of irrigation restrictions, including their microeconomic and broad economic repercussions. This paper connects a multi-attribute Revealed Preference Model working at an agricultural district level with a regionally calibrated supply and use model that combines nonlinear programming and input-output modeling techniques to address water allocation issues. To the best of our knowledge, this is the first time these two modeling approaches are combined in this fashion. Methods are illustrated with an application to the Lower Po River Basin (LPRB) in the Emilia Romagna Region, Italy. Results show that irrigation restrictions generate rising incremental losses in the agricultural districts of the LPRB, which are amplified through negative inter-sectorial feedbacks at a regional level.

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“…For example, there is an analysis of how water policies impact agricultural practices [27], evaluation for irrigation system designs and evaluation [28] and a multi-attribute approach and linear programming for risk aversion investments in agriculture [29]. Recently, a non-interactive elicitation method for non-linear multi-attribute utility functions analyzing their application in agricultural economics was proposed [30]. Other recent multi-attribute research can be consulted in [31,32] for utility analysis for policy selection and financing the preservation of forests, as well as a sustainable optimization model for agricultural production.…”

Section: Introductionmentioning

confidence: 99%

Agricultural Tractor Selection: A Hybrid and Multi-Attribute Approach

et al. 2016

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Usually, agricultural tractor investments are assessed using traditional economic techniques that only involve financial attributes, resulting in reductionist evaluations. However, tractors have qualitative and quantitative attributes that must be simultaneously integrated into the evaluation process. This article reports a hybrid and multi-attribute approach to assessing a set of agricultural tractors based on AHP-TOPSIS. To identify the attributes in the model, a survey including eighteen attributes was given to agricultural machinery salesmen and farmers for determining their importance. The list of attributes was presented to a decision group for a case of study, and their importance was estimated using AHP and integrated into the TOPSIS technique. In this case, one tractor was selected from a set of six alternatives, integrating six attributes in the model: initial cost, annual maintenance cost, liters of diesel per hour, safety of the operator, maintainability and after-sale customer service offered by the supplier. Based on the results obtained, the model can be considered easy to apply and to have good acceptance among farmers and salesmen, as there are no special software requirements for the application.

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A non-interactive elicitation method for non-linear multiattribute utility functions: Theory and application to agricultural economics

Cited by 28 publications

References 39 publications

Modeling at farm level: Positive Multi-Attribute Utility Programming

Modeling at farm level: Positive Multi-Attribute Utility Programming

Economic Impacts of Irrigation-Constrained Agriculture in the Lower Po Basin

Agricultural Tractor Selection: A Hybrid and Multi-Attribute Approach

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