Optimal allocation of production resources under uncertainty: Application of the muliticriteria approach

https://doi.org/10.17221/238/2015-AGRICECONCitation:Zgajnar J., Kavcic S. (2016): Optimal allocation of production resources under uncertainty: Application of the muliticriteria approach. Agric. Econ. – Czech, 62: 556-565.
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Analysing economic efficiency of farm production always faces a problem of insufficient information. This is particularly true when the analysis is performed on the reference farm where estimates are based on the average aggregated data. The paper illustrates how the combination of different mathematical programming methods could be efficiently used to analyse the farm-production plan with the lack of the on-farm accounting data. The utilised approach shows how the holistic analysis of production planning as a multi-criteria problem could be conducted. The estimation of the missing information and the disaggregation of the endogenous farm data is enabled through different models that are based on the constrained optimisation. The developed models are linked into the spreadsheet modular tool enabling systematic analyses of the farm decision making under risky conditions. Illustration of the modular tool application is given via the analyses of three hypothetic dairy farms. The obtained results indicate that the developed approach enables holistic analyses of the production planning. The methodology applied provides also important information for the measures aimed to increase efficiency as well as to benchmarking the performance of different farm types. The results point to a discrepancy between the solutions obtained through different objective functions and shows the advantage of the multi-criteria approach.
Antle John M. (1987): Econometric Estimation of Producers' Risk Attitudes. American Journal of Agricultural Economics, 69, 509-  https://doi.org/10.2307/1241687
Biswas Animesh, Pal Bijay Baran (2005): Application of fuzzy goal programming technique to land use planning in agricultural system. Omega, 33, 391-398  https://doi.org/10.1016/j.omega.2004.07.003
Buysse J., Huylenbroeck G.V., Lauwers L. (2007): Normative, positive and econometric mathematical programming as tools for incorporation of multifunctionality in agricultural policy modelling. Agriculture, Ecosystems & Environment, 120: 70–81.
Čančer Vesna, Mulej Matjaž (2010): The dialectical systems theory's capacity for multi-criteria decision-making. Systems Research and Behavioral Science, 27, 285-300  https://doi.org/10.1002/sres.1016
Ferguson E.L., Darmon N., Fahmida U., Fitriyanti S., Harper T.B., Premachandra I.M. (2006): Design of optimal food-based complementary feeding recommendations and identification of key »problem nutrients« using goal programming. The Journal of Nutrition, 136: 2399–2404.
Gómez-Limón José A, Arriaza Manuel, Riesgo Laura (2003): An MCDM analysis of agricultural risk aversion. European Journal of Operational Research, 151, 569-585  https://doi.org/10.1016/S0377-2217(02)00625-2
Hardaker J.B., Huirne R.B.M., Anderson J.R., Lien G. (2007): Coping with Risk in Agriculture. 2nd ed. CABI Publishing, Oxfordshire.
Huirne R., Meuwissen M., Van Asseldonk M. (2007): Importance of whole-farm risk management in agriculture. In: Handbook of Operations Research in Natural Resources. Weintraub A., Romero C., Bjorndal T., Epstein R. (Eds.). New York, Springer Science & Business Media: 3–15.
Jones D., Tamiz M. (2010): Practical Goal Programming. International Series in Operations Research and Management Science. New York, Springer.
Kobzar O.A. (2006): Whole-farm risk management in arable farming: portfolio methods for farm-specific business analysis and planning. [PhD thesis.] Wageningen University Wageningen.
Lien Gudbrand (2002): Non-parametric estimation of decision makers' risk aversion. Agricultural Economics, 27, 75-83  https://doi.org/10.1111/j.1574-0862.2002.tb00106.x
Martel J.M., Aouni B. (1998): Diverse imprecise goal programming model formulations. Journal of Global Optimization, 12: 127–138. https://doi.org/10.1023/A:1008206226608
Meyer Donald J., Meyer Jack (): Measuring Risk Aversion. Foundations and Trends® in Microeconomics, 2, 107-203  https://doi.org/10.1561/0700000006
Ortuño M. T., Vitoriano B. (2011): A goal programming approach for farm planning with resources dimensionality. Annals of Operations Research, 190, 181-199  https://doi.org/10.1007/s10479-009-0524-5
Pavlovic M., Cerenak A., Pavlovic V., Rozman C., Pazek K., Bohanec M. (2011): Development of DEX-HOP multi-attribute decision model for preliminary hop hybrids assessment. Computers and Electronics in Agriculture, 75, 181-189  https://doi.org/10.1016/j.compag.2010.11.002
Pažek K., Rozman Č., Bavec F., Borec A., Bavec M. (2010): A Multi-Criteria Decision Analysis Framework Tool for the Selection of Farm Business Models on Organic Mountain Farms. Journal of Sustainable Agriculture, 34, 778-799  https://doi.org/10.1080/10440046.2010.507531
Rednak M., Erjavec E., Volk T., Zagorac B., Mojk B., Kavčič S., Kožar M., Turk J., Rozman Č., Vučko I. (2009): Analysis of the effects of agricultural policy with the model of typical agricultural holdings. Zaključno poročilo CRP projketa V4-0361. Kmetijski Inštitut Slovenije, Ljubljana, (in Slovene).
Rehman Tahir, Romero Carlos (1984): Multiple-criteria decision-making techniques and their role in livestock ration formulation. Agricultural Systems, 15, 23-49  https://doi.org/10.1016/0308-521X(84)90016-7
Rehman Tahir, Romero Carlos (1987): Goal programming with penalty functions and livestock ration formulation. Agricultural Systems, 23, 117-132  https://doi.org/10.1016/0308-521X(87)90090-4
Saaty T.L. (1980): The Analytic Hierarchy Process. Mc Graw, New York.
Sharma Dinesh K., Ghosh Debasis, Alade Julius A. (2006): A fuzzy goal programming approach for regional rural development planning. Applied Mathematics and Computation, 176, 141-149  https://doi.org/10.1016/j.amc.2005.09.080
Tamiz Mehrdad, Jones Dylan, Romero Carlos (1998): Goal programming for decision making: An overview of the current state-of-the-art. European Journal of Operational Research, 111, 569-581  https://doi.org/10.1016/S0377-2217(97)00317-2
Torkamani J., Abdolahi M. (2001): Empirical comparison of direct techniques for measuring attitudes toward risk. Journal of Agricultural Science and Technology, 3: 163–170.
Zgajnar J., Kavcic S. (2011): Indirect estimation of farm’s risk aversion; mathematical programming approach. Bulgarian Journal of Agricultural Science, 17: 218–231.
Žgajnar J., Kermauner A., Kavčič S. (2007): Model for assessing the nutritional needs of ruminants and optimization of feed rations. In: Kavčič S. (ed.): 4. konferenca DAES. Slovensko kmetijstvo in podeželje v Evropi, ki se širi in spreminja, Moravske Toplice, 8–9 Nov. 2007, Ljubljana: 279–288 (in Slovene).
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