My research investigating the appropriateness of agricultural biotechnology for African farmers combines qualitative and quantitative methodologies to catalogue the multiplicity of factors that influence agricultural decision-making. It aims to bridge the gap between the models and surveys favoured by economists and the ethnographies and participant observation favoured by anthropologists to offer an innovative methodological approach for evaluating farmer attitudes and behavioural intentions to adopt new agricultural technologies.
This methodological program emerges out of the theoretical framework of participatory plant breeding, which is guided by a desire to integrate farmers directly into the agricultural innovation process. This progression of exercises relies heavily on visual aids and side-by-side comparisons, which help to bridge the gap between hypothetical exercises and farm-level realities. Some examples include:
Each farmer is presented with a side-by-side comparison of two varieties of the crop, differing only in their yield stability, source of planting materials, and cost. One variety represents the traditional farmer variety; the other represents the Genetically Modified variety [these identities are not disclosed to farmers]. Farmers are asked to rate the likelihood that they would plant each variety based on these key differences.
Ranking of varietal types
Four types of planting materials are physically placed in front of the farmer: a traditional farmer variety, a modern variety improved through conventional breeding techniques, and genetically modified versions of these same varieties. Farmers are asked to rank these four varieties in terms of what they would sow, and then again in terms of what they would eat.
After using ranking exercises to determine farmer attitudes and intentions, focus groups are used to understand why farmers feel the way they do. Each focus group begins by undertaking the same series of exercises described above as a collective, prompting members to question, listen, and disagree as they try to achieve consensus. Follow-up questions explore differences among farmer responses based on geography, market and credit access, as well as demographic characteristics.
Taken together, this mixed methods approach constitutes a new methodological program designed to offer rigorous and representative data on farmer attitudes and intentions to adopt GM crops. The combined output of this research will be to develop the first predictive model that can forecast farmer demand for GM traits and varieties prior to their commercial release. These techniques should have wide applicability for future research into the potential adoption rates of new agricultural biotechnologies across Africa.