Improving the efficiency of agricultural development: Can farmer typologies be used to predict the adoption of agricultural innovations for the poorest farmers, and therefore, increase the impact of rural development programs on the rural poor?

This investigation, through a literature review, outlines how agricultural development is an effective tool for achieving the goals of human development theory, the participatory approach to development and the sustainable development approach. In this investigation, sustainable intensification is identified as an essential part of agricultural development. Through an examination of the literature, it is made clear that there is a low adoption rate for agricultural innovations, this inhibits sustainable intensification. Moreover, it is demonstrated that the distribution of agricultural innovations favours wealthier farmers, who are less deterred by the perceived risk associated with the adoption process. Antecedent research has tried to improve adoption rates by targeting particular groups of farmers, known as farmer typologies. Traditional typologies focus on the structural characteristics of farms, such as farm size, crop diversity and livestock diversity. Despite the use of these typologies, adoption rates remain low. An emerging method for creating typologies incorporates the personal motivations and attitudes of farmers, however, these have not been empirically tested in relation to the real-life adoption of innovations. This investigation used data from the Africa Research In Sustainable Intensification for the Next Generation (RISING) project based in the Ethiopian Highlands to investigate three types of typology. The ultimate aim of this investigation was to see whether a particular set of typologies can be used to identify high adopting farmers in the lowest wealth quartiles. The first set of typologies is based solely on the structural characteristics of the farms surveyed. The second set of typologies is solely based on motivational characteristics. The third set of typologies is based on both structural and motivational characteristics. Two variables are used to measure adoption: Adoption rate, which indicates the percentage of innovations which farmers continued to use after phase one of the Africa RISING program; Adoption strength, which measures how strongly farmers have adopted each innovation. The results of this investigation indicate that there is sufficient evidence to support the use of all three sets of typologies to predict high adoption rates and high adoption strength in farmers. However, there is insufficient evidence to support the use of structural clusters for predicting high adoption rates, or adoption strength, for farmers in the lowest wealth quartiles. There is also insufficient evidence to support the use of motivational typologies to predict high adoption rates for farmers in the lowest wealth quartiles. In contrast, the results indicate that motivational typologies could effectively predict high adoption strength for farmers in each individual wealth quartile. There was sufficient evidence to suggest that combined typologies could be used to predict high adoption rates and high adoption strength for farmers in the lowest wealth quartiles. This research shows the promise of using motivational characteristics to group farmers. This investigation should encourage further research which investigates how motivational typologies can be operationalised in order to catalyse sustainable intensification and make agricultural innovations more accessible to the rural poor