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Sustainable Rangeland Management Using A Multi-Fuzzy Model: How To Deal With Heterogeneous Experts’ Knowledge


  • Azadi, H.
  • Shahvali, M.
  • van den Berg, J.H.
  • Faghih, N.


While fuzzy specialists usually use homogeneous experts’ knowledge to construct fuzzy models, it is much more difficult to deal with knowledge elicited from a heterogeneous group of experts. This issue especially holds in the area of the sustainable rangeland management. One way to deal with the diversity of opinions is to develop a fuzzy system for all experts and to combine all these so-called primary systems into one multi-fuzzy model. To derive each of the primary fuzzy systems using the knowledge of a group of administrative experts, several semi-structured interviews were held in three different areas of the Fars province in Southwest Iran. In order to find the final output of the multi-fuzzy model, we applied different ‘voting’ methods. The first method simply uses the arithmetic average of the primary outputs as the final output of the multifuzzy model. This final output represents an estimation of the Right Rate of Stocking. We also propose other (un)supervised voting methods. Most importantly, by harmonizing the primary outputs such that outliers get less emphasis, we introduce an unsupervised voting method calculating a weighted estimate of the Right Rate of Stocking. This harmonizing method is expected to provide a new useful tool for policymakers in order to deal with heterogenity in experts’ opinions: it is especially useful in cases where little field data is available and one is forced to rely on experts’ knowledge only. By constructing the three fuzzy models based on the elicitation of heterogeneous experts’ knowledge, our study shows the multidimensional vaguenesses that exist in sustainable rangeland management. Finally, by comparing the final Right Rate of Stocking with its medium range, this study proves the existence of overgrazing in pastures of the three regions of the Fars province in Southwest Iran.

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  • Azadi, H. & Shahvali, M. & van den Berg, J.H. & Faghih, N., 2005. "Sustainable Rangeland Management Using A Multi-Fuzzy Model: How To Deal With Heterogeneous Experts’ Knowledge," ERIM Report Series Research in Management ERS-2005-016-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
  • Handle: RePEc:ems:eureri:1934

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    References listed on IDEAS

    1. Sicat, Rodrigo S. & Carranza, Emmanuel John M. & Nidumolu, Uday Bhaskar, 2005. "Fuzzy modeling of farmers' knowledge for land suitability classification," Agricultural Systems, Elsevier, vol. 83(1), pages 49-75, January.
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    More about this item


    carrying capacity; heterogeneous; multi-fuzzy model; sustainable rangeland management;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G3 - Financial Economics - - Corporate Finance and Governance
    • M - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics
    • Q24 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation - - - Land

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