A network perspective filling a gap in assessment of agricultural advisory system performance. (February 2017) - Bourne, Mieke; Gassner, Anja; Makui, Parmutia; Muller, Alice; Muriuki, Jonathan
Abstract: Agricultural advisory systems aim to improve livelihoods and well-being of the rural community by enhancing information exchange and capacity for collective action. In East Africa, advisory systems are becoming more demand driven and are being provided by an increasingly complex range of actors using participatory approaches. Social network analysis (SNA) provides a tool to examine farmer networks for broad assessment of agricultural advisory systems. This paper proposes a framework linking social network measures to information flow and capacity for collective action and applies it to personal (egocentric) networks in 11 sites within East Africa. The results provide valuable insight into performance of existing advisory systems and areas for improvement. Limited capacity for collective action, based on information networks, anecdotal evidence and literature, within farmer groups and communities was found in the Rwanda and to some degree in the Kenyan sites. In Tanzania, few connections with external information sources were found, potentially limiting new innovations entering the communities. In applying the framework, consideration of external factors that can influence social network structures is required so that attribution is not overstated. Use of egocentric networks and recall error challenges exist but can be managed. The proposed SNA framework provides a new and useful assessment tool, particularly combined with broader frameworks, for government agriculture ministries, development practitioners and researchers to support the design and assessment of agricultural advisory systems. Highlights: Social Network Analysis measures can usefully assess agricultural advisory systems. SNA framework provides insights into advisory systems in East Africa. SNA provides a rapid and relationship based assessment tool.