Diffusion of agricultural knowledge in Southern Ethiopia: finding the real opinion leaders through network analysis. Issue 1 (1st January 2023) - de Roo, Nina; Amede, Tewodros; Elias, Eyasu; Almekinders, Conny; Leeuwis, Cees
ABSTRACT: Purpose: Agricultural extension services in poor countries often identify opinion leaders based on criteria such as wealth and social status. We explore the effectiveness of this top-down approach by analysing the role of so-called model and nodal farmers in the diffusion of malt barley in a highland community in Ethiopia. Research approach: We use a retrospective case study design where we combine quantitative network analysis with qualitative data. Findings: Nodal farmers played a more central role in knowledge diffusion of the technology than model farmers. While model farmers were wealthier and better connected to the local authorities, nodal farmers were socio-economically more similar to their fellow farmers. Nodal and model farmers, as well as farmers closely connected to them, had a significantly higher adoption index than the rest. Practical implications: The diffusion of knowledge is an important condition for the adoption of modern agricultural technologies, but it is not enough, particularly when access to external inputs is limited. Moreover, relying on assumed opinion leaders has its limitations and may even reinforce existing inequalities. Theoretical implications: This paper has shown the complementarity of network approaches. We propose network approaches such as social network analysis to identify community brokers who emerge from bottom-up or clan-based, political, knowledge networks that mediate access to agricultural technologies. Originality: Our combined research approach differs from the mainstream of studies in this field that employ either ethnographic fieldwork or (spatial-)econometric methods. We aim to create a bridge between the often separated worlds of (technical) agronomic research, (qualitative) rural sociology, and (quantitative) econometric analysis.