Simulation models in farming systems research : potential and challengesFeola, G., Sattler, C. and Saysel, A. K. (2012) Simulation models in farming systems research : potential and challenges. In: Farming systems research into the 21st century : the new dynamic. Springer, pp. 281-306. ISBN 9789400745025 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1007/978-94-007-4503-2_13 Abstract/SummaryIntegrated simulation models can be useful tools in farming system research. This chapter reviews three commonly used approaches, i.e. linear programming, system dynamics and agent-based models. Applications of each approach are presented and strengths and drawbacks discussed. We argue that, despite some challenges, mainly related to the integration of different approaches, model validation and the representation of human agents, integrated simulation models contribute important insights to the analysis of farming systems. They help unravelling the complex and dynamic interactions and feedbacks among bio-physical, socio-economic, and institutional components across scales and levels in farming systems. In addition, they can provide a platform for integrative research, and can support transdisciplinary research by functioning as learning platforms in participatory processes.
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