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Valoración Agraria multicriterio en un entorno con escasa información/Multicriteria Agricultural Valuation in an Environment with scarce information

Listed author(s):


    (Grupo Valoración y Decisión Multicriterio Universidad Politécnica de Valencia. Camino de Vera s/n, (46022) Valencia (Spain). ( ))



    (Grupo Valoración y Decisión Multicriterio Universidad Politécnica de Valencia. Camino de Vera s/n, (46022) Valencia (Spain). ( ))



    (Grupo Decisión Multicriterio Zaragoza ( Facultad de Ciencias Económicas y Empresariales, Universidad de Zaragoza. Gran Vía 2, (50005) Zaragoza (Spain).)

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    El presente trabajo presenta un nuevo procedimiento de valoración agraria multicriterio (MAVAM), especialmente diseñado para situaciones en las que se dispone de escasa información, cuantificada o no, acerca de los elementos considerados. El procedimiento propuesto, válido para trabajar en decisiones individuales y colectivas, pretende capturar e incorporar en el proceso de valoración, tanto la información objetiva asociada a los aspectos tangibles del problema como el conocimiento subjetivo del mismo vinculado al factor humano. Para ello, se combinan en un modelo de regresión dos de las técnicas de decisión multicriterio más extendidas en la práctica: el proceso analítico jerárquico (AHP) y la programación por metas (GP). La primera permite capturar, mediante la utilización de comparaciones pareadas, la información tangible e intangible derivada de los elementos conocidos. La segunda, además de proporcionar una estimación bastante robusta del modelo de regresión posibilita la integración en el proceso de valoración de la escasa información existente y la actitud personal ante la valoración. La metodología propuesta se ilustra mediante su aplicación a un caso particular de valoración de un activo agrario ubicado en la comarca de la Ribera de Valencia (España). This paper presents a new multicriteria agricultural valuation method (MAVAM) designed specifi cally for situations in which there is only limited information, whether quantifi ed or not, with respect to the elements being considered. The proposed procedure, valid for working in both individual and collective decision-making processes, aims to capture and incorporate into the valuation process both the objective information associated with the tangible aspects of the problem, as well as the subjective knowledge of that valuation process linked to the human factor. To that end, it combines in one regression model two of the most popular multicriteria decision-making techniques applied in practice: the analytical hierarchy process (AHP) and goal programming (GP). The fi rst of these allows us to capture, by way of the use of paired comparisons, the tangible and intangible information derived from the known elements. The second, in addition to providing a fairly robust estimation of the regression model, makes it possible to integrate into the valuation process both the limited information that exists and the personal attitude adopted with respect to that valuation. The methodology is illustrated by way of its application to the particular case of valuing an agricultural asset located in the Ribera e Valencia rural district of Spain.

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    Article provided by Estudios de Economía Aplicada in its journal Estudios de Economía Aplicada.

    Volume (Year): 25 (2007)
    Issue (Month): (Abril)
    Pages: 549-572

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    Handle: RePEc:lrk:eeaart:25_2_9
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    Beatriz Rodríguez Prado. Facultad de CC.EE. y EE. Avda. Valle del Esgueva. Valladolid 47011 SPAIN

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    1. A. Charnes & W. W. Cooper & R. O. Ferguson, 1955. "Optimal Estimation of Executive Compensation by Linear Programming," Management Science, INFORMS, vol. 1(2), pages 138-151, January.
    2. Schniederjans, Marc J & Hoffman, James J & Sirmans, G Stacy, 1995. "Using Goal Programming and the Analytic Hierarchy Process in House Selection," The Journal of Real Estate Finance and Economics, Springer, vol. 11(2), pages 167-176, September.
    3. Rosen, Sherwin, 1974. "Hedonic Prices and Implicit Markets: Product Differentiation in Pure Competition," Journal of Political Economy, University of Chicago Press, vol. 82(1), pages 34-55, Jan.-Feb..
    4. Badri, Masood A., 2001. "A combined AHP-GP model for quality control systems," International Journal of Production Economics, Elsevier, vol. 72(1), pages 27-40, June.
    5. Keeney, Ralph L., 1996. "Value-focused thinking: Identifying decision opportunities and creating alternatives," European Journal of Operational Research, Elsevier, vol. 92(3), pages 537-549, August.
    6. Aznar, Jeronimo & Guijarro, Francisco, 2007. "Estimating regression parameters with imprecise input data in an appraisal context," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1896-1907, February.
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