Social structure, especially in the form of social networks, affects the adoption of agricultural technologies. In light of an increasing focus on new demand-driven agricultural extension approaches that leverage social networks as an opportunity, too little is known about (a) which network characteristics matter? and (b) how do specific network characteristics matter? This paper investigates the impact of social networks in relation to smallholder dairy production technology adoption in Ethiopia.
Graduate programs in agriculture and allied disciplines in Ethiopia are expected to make concrete contribution to market-oriented development of smallholder agriculture. This, among others, calls for realignment and engagement of the programs with smallholder farmers and, value chain, R&D and policy actors. No panacea exists, however, as to how to ensure effective linkages, and thereby responsiveness. Lessons from initiatives on the ground in the country and beyond is thus crucial to inform the development of appropriate policy and innovative strategy.
This conference paper presentet at the "International conference on livestock value chain finance and access to credit" reviews the different financial mechanisms available to promote value chain, analysing wheter such forms address the capital constraints faced by value chain actors. It also looks at the challenges faced by specific sectors, such as the livestock sector, in securing appropriate forms of capital
This paper published in the 56th Annual Conference of The Agriculture Economics Association of South Africa, describes the opportunities of innovation bringed by the new global cannabis marketing, especially in Lesotho and aims to fill the gap of focused social scientific research on the potential of cannabis cultivation to promote inclusive growth creating conditions of improved social justice and economic emancipation
This paper has been prepared from a transcript of a presentation at the Crawford Fund 2017. This talk is a synthesis of some of the emerging issues we are seeing in the digital revolution, and how we can overcome the barriers to digitalised agricultural systems in the developing world
The aim of the paper is to evaluate the impact of value-webs as an innovation in agricultural production on welfare of cassava smallholders in Nigeria. The estimation procedure involved the alternative process of multivalued treatment models when treatment units have multiple values. The study thus extends previous impact studies which focused on estimating causal effects from binary treatment units. The treatment units were determined from the extent of utilization of cassava which informed the classification of households into value-web groups.
There is a lack of quantitative information about farmers preferences of those activities, which are crucial to refine capacity development activities in the future. This study employs a discrete choice experiment analysing the willingness to pay to determine the preferences of small-scale farmers for agricultural training with respect to the training method, trainer, duration, location and additional offers
Changes in the structure of value chains have opened up lucrative opportunities for smallholder producers to increase income as a means to improve their livelihoods. Yet, recent literature argues that smallholder producers are better off in their current markets than when integrated in high value chains on disadvantageous terms. This article studies the terms of integration of smallholder producers in high value chains from a marketing systems perspective
Based on three rounds of panel data (2007, 2009, and 2012) on indigenous households, this study assessed the impacts of Integrated Aquaculture-agriculture value chain participation on the welfare of marginalized poor indigenous rural households in Bangladesh. We also examined the distributional impacts of IAA value chain
This paper examined cowpea value chain mapping and marketing efficiency among cowpea farmers in Ga-Molepo of Capricorn district and Bela-Bela of Waterberg district. Primary data was collected through face to face interviews from 80 smallholder cowpea farmers using structured questionnaire. Value chain map, descriptive statistics and binary logistic regression model were used to analyse the data