Information flows within farmer networks and the implications for farmer-to-farmer extension: evidence from the Kenyan dairy sector

Morrison, R., Cassar, X., Duncan, A.J., Rao, E.J.O. and Barnes, A.P. 2025. Information flows within farmer networks and the implications for farmer-to-farmer extension: evidence from the Kenyan dairy sector. The Journal of Agricultural Education and Extension

Purpose This article analyses the information flows within farmer networks to understand how farmer-to-farmer extension strategies can be made more effective.

Design/methodology/approach Sociograms are used alongside regressions to provide a novel insight into information flows and power dynamics within dairy farmer networks. Primary survey data from four farmer networks (n = 255) collected through a method of snowball sampling in western Kenya in 2022 is analysed.

Findings The findings show that farmer networks are heterogenous and have varying levels and types of social capital which impacts how information is shared. Certain individuals within the networks are well positioned to transfer information to other network members and therefore may make effective lead farmers. These individuals tend to be market-orientated and male.

Practical implications The results of this study highlight that training a lead farmer to spread information and awareness of agricultural technologies may not always be effective due to low social capital. Therefore, whilst farmer-to-farmer extension may be a low-cost alternative to traditional extension services, policy makers should also consider implementing interventions that focus on increasing the social capital base of farmers.

Theoretical implications This study increases our knowledge of how agricultural innovations diffuse through networks. This contributes to our wider understanding of how innovation systems work providing greater insight in the role of farmers as agents of change.

Originality/value This study offers insight into how farmer network structures can differ depending on context and how this influences knowledge diffusion. It also offers a unique insight into the characteristics of farmers who may make ideal ‘lead farmers’ for knowledge exchange due to the position they occupy within their networks.

KEYWORDS: Farmer interactions extension social networks Kenya