The ongoing quest for a better understanding of adoption behaviour, and more specifically the search for relevant, and meaningful behaviour determinants that can be useful in the understanding, analysis and change of adoption behaviour, has prompted this study. It was specifically focused on the role of intervening variables and their influence relative to the commonly used independent variables. A pre-tested, structured questionnaire was used to collect data from 113 farmers randomly selected to represent five percent samples of four villages selected to represent the biggest variation in terms of climatic conditions within the Njombe district of Tanzania. Correlations, chi-square, and regressions were used to determine the relationship between the independent and the dependent variables. The results show that most of the farmers’ (97.3 percent) production efficiency falls well below the optimum maize yield of about 40 bags per acre. Various independent and intervening factors were found to influence adoption. In general, the intervening variables show, without exception, much stronger influence relationships with adoption behaviour than is the case with independent variables. Also, unlike what is a common phenomenon among independent variables, these relationships show great consistency, which further supports the research hypothesis. The most convincing evidence in support of the critical role of intervening variables in decision making and adoption behaviour are the regressions, which explain about 73.2 to 93.6 percent of the variation in adoption as compared to the mere 6.0 to 32.9 percent of the independent variables. The explanation for this highly significant difference is that the intervening variables are probably the immediate and direct determinants of adoption behaviour and that the influence of intervening variables only becomes manifested in adoption behaviour via the intervening variables. This explains why the influence of independent variables is much smaller and more inconsistent than that of the intervening variables. The practical implications of these findings are that the emphasis in the analysis and understanding of adoption behaviour should be on the intervening variables. They lend themselves as so-called “forces of change” and thus represent the focus of extension endeavours, but also as criteria for evaluation and monitoring. From the study arise various issues that call for further research like refinement of the measurements.
Thesis (PhD(Agrarian Extension))--University of Pretoria, 2008.