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Successes and failures to embed socioeconomic dimensions in integrated natural resource management modeling: Lessons from Thailand

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  • Ekasingh, B.
  • Letcher, R.A.

Abstract

This paper discusses the necessity, successes, and failures of attempts to embed socioeconomic aspects into integrated natural resource modeling. It examines experiences in Thailand over the past 20–30 years to illustrate advances and difficulties experienced in these attempts. The paper explores different approaches which are used to incorporate socioeconomic dynamic processes and impacts into integrated assessments. Lessons learnt from Thai experiences starting from systems approaches and modeling agricultural and watershed management are reviewed. It is found that greater success has been experienced with the inclusion of agricultural and natural resource economists, who have experience dealing with quantitative methods and “hard” systems dynamics. The need for the “soft” side of assessment is recognized but is not easily realized. Failures to include other social science disciplines in integrated assessment have been caused by factors such as administrative boundaries, inadequate linkages between social theories and differences in agendas. Some modeling approaches, such as agent-based systems or multi-agent systems are well tuned to socioeconomic variables but their use by policy makers is still in experiment. Balancing “hard” and “soft” systems approaches will improve the relevance and validity of the models to solve agricultural and natural resource problems but this is still an art which requires patience and perseverance on the part of both the biophysical and social scientists involved.

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  • Ekasingh, B. & Letcher, R.A., 2008. "Successes and failures to embed socioeconomic dimensions in integrated natural resource management modeling: Lessons from Thailand," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 137-145.
  • Handle: RePEc:eee:matcom:v:78:y:2008:i:2:p:137-145
    DOI: 10.1016/j.matcom.2008.01.006
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