The analysis used both primary and secondary data. Primary data were collected by use of structured questionnaires, key informant interviews and focus group discussions. Based on the research plan, a total of 250 individual households were randomly selected and interviewed.
The stepwise multiple linear regression model ran using SPSS revealed nine variables significantly determining the adaptation of climate change strategies. The variables found significant were: agricultural labor force, level of education of the household head, land tenure arrangements, gender of the household head, extension service availability, out-migration of labor, years of farming experience, household size and availability of farmer to farmer extension. The predicted R value of 0.87, R2 of 0.63, and adjusted R2 of 0.60 indicate high explanatory power of the model as a whole.
The acceptance of the variables included in the model helps very useful policy conclusions for climate change adaptations to be drawn. All these variables, except gender and out-migration, have a positive influence on climate change adaptation strategies. The influence of agricultural labor force appeared to be strongest, indicating the very important role of this factor in adaptation and the need for promotion of less labour-intensive, but more remunerative adaptation strategies that would enable smallholder farmers to manage all of their farm plots in an effective way.
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