Bioeconomic model of decision support system for farm management. Part I: Systemic conceptual modeling
Information systems used in farming systems are characterized by high complexity. They should be composed of inter-related economic and biological components capable of working in a dynamic and continuous manner, receiving data and producing results within an organized production process. Taking this complexity into account, in this study we propose a novel conceptual macromodel with a system approach of the agricultural and livestock production environment to be adopted as information system in order to support the decision making process. This model is capable of representing the innumerable aspects of a farm production system aiming to help farm producers understand and manage their production system. To better understand the general model and its nuances, several submodels (input models) were built based on adaptation of pre-existing research, among which we mention: meteorological, pasture, animal, crop–livestock integration, crop, soil, pasture-animal, and pasture-soil submodels. The combination of these submodels originates and configures the farm production system structure. Among the main outputs of the proposed model are the economic results, based on agricultural and livestock productivity, the environmental impact assessment, and the analysis of operational risk. A qualitative approach was used with an exploratory descriptive design to carry out this research, based on literature review, interviews, and meetings with experts to refine and validate the proposed model. The refinement of the conceptual model was based on the Delphi method, which allowed the collection of data and peculiarities of the object under study, guided its development to achieve the goals of this research, and allowed the register of several issues for further studies. The validation of the model, also using a qualitative approach, was performed employing conceptual, face, and subsystem validation procedures, also applying the Delphi method. This way, we aimed to identify the weak and strong points of our conceptual model, its main shortcomings and limitations, and the variables that should be optimized, in theoretical and practical perspectives, so that this model can be improved.
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- Senge, Peter M. & Sterman, John D., 1992. "Systems thinking and organizational learning: Acting locally and thinking globally in the organization of the future," European Journal of Operational Research, Elsevier, vol. 59(1), pages 137-150, May.
- Fisher, Donna K. & Norvell, Jonathan & Sonka, Steven T. & Nelson, Mark J., 2000. "Understanding Technology Adoption Through System Dynamics Modeling: Implications For Agribusiness Management," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association (IFAMA), vol. 3(03).
- Dueri, S. & Calanca, P.L. & Fuhrer, J., 2007. "Climate change affects farm nitrogen loss - A Swiss case study with a dynamic farm model," Agricultural Systems, Elsevier, vol. 93(1-3), pages 191-214, March.
- Beauchemin, Karen A. & Henry Janzen, H. & Little, Shannan M. & McAllister, Tim A. & McGinn, Sean M., 2010. "Life cycle assessment of greenhouse gas emissions from beef production in western Canada: A case study," Agricultural Systems, Elsevier, vol. 103(6), pages 371-379, July.
- Robert P. King & Michael Boehlje & Michael L. Cook & Steven T. Sonka, 2010. "Agribusiness Economics and Management," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 92(2), pages 554-570.
- Musshoff, Oliver & Hirschauer, Norbert, 2007. "What benefits are to be derived from improved farm program planning approaches? - The role of time series models and stochastic optimization," Agricultural Systems, Elsevier, vol. 95(1-3), pages 11-27, December.
- Jakku, E. & Thorburn, P.J., 2010. "A conceptual framework for guiding the participatory development of agricultural decision support systems," Agricultural Systems, Elsevier, vol. 103(9), pages 675-682, November.
- Nousiainen, J. & Tuori, M. & Turtola, E. & Huhtanen, P., 2011. "Dairy farm nutrient management model. 1. Model description and validation," Agricultural Systems, Elsevier, vol. 104(5), pages 371-382, June.
- Austin, E.J. & Willock, J. & Deary, I.J. & Gibson, G.J. & Dent, J.B. & Edwards-Jones, G. & Morgan, O. & Grieve, R. & Sutherland, A., 1998. "Empirical models of farmer behaviour using psychological, social and economic variables. Part II: nonlinear and expert modelling," Agricultural Systems, Elsevier, vol. 58(2), pages 225-241, October.
- Austin, E.J & Willock, J & Deary, I.J & Gibson, G.J & Dent, J.B & Edwards-Jones, G & Morgan, O & Grieve, R & Sutherland, A, 1998. "Empirical models of farmer behaviour using psychological, social and economic variables. Part I: linear modelling," Agricultural Systems, Elsevier, vol. 58(2), pages 203-224, October.
- Michael Boehlje, 1999. "Structural Changes in the Agricultural Industries: How Do We Measure, Analyze and Understand Them?," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(5), pages 1028-1041.
- Herbert A. Simon, 1955. "A Behavioral Model of Rational Choice," The Quarterly Journal of Economics, Oxford University Press, vol. 69(1), pages 99-118.
- Finger, Robert & Lazzarotto, Patrick & Calanca, Pierluigi, 2010. "Bio-economic assessment of climate change impacts on managed grassland production," Agricultural Systems, Elsevier, vol. 103(9), pages 666-674, November.
- Bryant, Jeremy & Lopez-Villalobos, Nicolas & Holmes, Colin & Pryce, Jennie & Rossi, Jose & Macdonald, Kevin, 2008. "Development and evaluation of a pastoral simulation model that predicts dairy cattle performance based on animal genotype and environmental sensitivity information," Agricultural Systems, Elsevier, vol. 97(1-2), pages 13-25, April.
- Moore, A.D. & Robertson, M.J. & Routley, R., 2011. "Evaluation of the water use efficiency of alternative farm practices at a range of spatial and temporal scales: A conceptual framework and a modelling approach," Agricultural Systems, Elsevier, vol. 104(2), pages 162-174, February.
- Hardaker, J. Brian & Lien, Gudbrand, 2010. "Probabilities for decision analysis in agriculture and rural resource economics: The need for a paradigm change," Agricultural Systems, Elsevier, vol. 103(6), pages 345-350, July.
- Thomson, Euan F. & Bahhady, Faik A., 1995. "A model-farm approach to research on crop-livestock integration -- I. Conceptual framework and methods," Agricultural Systems, Elsevier, vol. 49(1), pages 1-16.
- Janssen, Sander & van Ittersum, Martin K., 2007. "Assessing farm innovations and responses to policies: A review of bio-economic farm models," Agricultural Systems, Elsevier, vol. 94(3), pages 622-636, June.
- Douthwaite, Boru & Gummert, Martin, 2010. "Learning selection revisited: How can agricultural researchers make a difference?," Agricultural Systems, Elsevier, vol. 103(5), pages 245-255, June.
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