Abstract
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 and social network metrics are used alongside regressions to provide a novel insight into the 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 within them. 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 farmer 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 contributes to our knowledge of information flows in farmer networks. It offers insight into how farmer networks structures can differ dependent 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.
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 and social network metrics are used alongside regressions to provide a novel insight into the 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 within them. 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 farmer 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 contributes to our knowledge of information flows in farmer networks. It offers insight into how farmer networks structures can differ dependent 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.
Original language | English |
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Pages (from-to) | 1-25 |
Number of pages | 25 |
Journal | The Journal of Agricultural Education and Extension |
Early online date | 11 Feb 2025 |
DOIs | |
Publication status | E-pub ahead of print - 11 Feb 2025 |
Keywords / Materials (for Non-textual outputs)
- Farmer interactions
- Kenya
- extension
- social networks