Abstract:
In most of the research studies, which involve participatory techniques, much of the
information gathered is of qualitative nature. Some of these will address specific
research questions and some provides a general understanding of peoples’ perceptions.
This study was focused on the former. Researchers have emphasized that causal maps
may be used as decision making tools in problem solving within the context of
organizational intervention. BNNs are a one step ahead than analysis of causal maps in
PRA. This can be used as a graphical decision support tool, which allows interactive
investigation of different causes affecting a decision and their relative impact on the
system as a whole. Participatory studies were carried out in 3 sites representing major
rubber growing areas, namely; Kegalle, Kalutara and Ratnapura districts. The objective
was to identify causes of low productivity in rubber lands and to identify effective
responses through institutional interventions. The study employed BBN as a tool to
make inferences on causal maps produced in farmer participatory studies. The software,
Netica 1.2 was employed in developing the model and subsequent analyses. According
to this BBN model, a considerable improvement in productivity can be obtained by
awareness and skill development in all villages. Introducing rain guards will have a
greater benefit in Kegalle area where the interference of rains is high, when compared to
other sites. However, when both the responses are considered, the highest improvement
can be gained in Batugampola in the Kalutara district, followed by Welihelatenna and
Pohorabawa in Kegalle and Ratnapura districts, respectively.
