Student - December 13, 2007

Fuzzy logic models motives

Policy makers and scientists may be helped by fuzzy logic models when it comes to studying and predicting farmers' decisions. Roel Bosma applied a fuzzy logic model in his study of 144 farming families in the Mekong Delta in Vietnam, to see whether this was a feasible way of simulating farming systems.

Bosma concludes in his thesis that this approach does work. There are many factors at play in Vietnamese farmers’ decisions on whether to combine fish, fruit or livestock raising with their rice growing. The decision often involves personal motives more than considerations such as labour savings or a potential increase in income.

According to Bosma, social circumstances and the family situation play an important role, and these conditions can be encapsulated in a fuzzy logic model. For example, if a young woman from a farming household is currently working off farm but becomes pregnant, this may be a reason to make on-farm adjustments so that she can earn an income from on-farm activities.

Fuzzy logic models are a way of making subjective statements (in this case made by farmers) manageable. On the basis of a number of statements, you can predict what decisions farmers are likely to make. Farmers do not generally behave in ways that fit simpler linear models. Fuzzy logic models are better for simulating farmers’ motives, says Bosma. / Jan Braakman

Roel Bosma receives his PhD on 18 December. His promotor is Professor Johan Verreth, chair of Aquaculture and Fisheries.