The objective of this paper is to show how Value Chain Analysis for Development (VCA4D) applied sustainable development concept for value chain analysis to establish a manageable set of criteria allowing to provide quantitative information, which is desperately lacking in many situations in developing economies, usable by decision makers and in line with policymakers concerns and strategies (the “international development agenda”).
This study analyzed the determinants of ICT usage in agricultural value chains among rural youth in Busia County, Kenya. A total of 213 young farmers were randomly selected and interviewed using semi-structured questionnaires. Descriptive statistics and Poisson regression model were applied in data analysis. Findings showed youth participation using ICTs was concentrated at the marketing level of the agricultural chain activities.
The Participatory Market Chain Approach (PMCA), which aims to stimulate gender-responsive innovations in commodity chains, was used to improve the performance of ALVs market chains in central Uganda. This paper presents the results of applying the PMCA in a phased manner on the Indigenous African Leafy Vegetables (ALVs) commodity chain in the context of a collaborative research project implemented in central Uganda
This paper comparatively analyzes the structure of agricultural policy development networks that connect organizations working on agricultural development, climate change and food security in fourteen smallholder farming communities across East Africa, West Africa and South Asia.
This paper examines the determinants of participation in an outsourced extension programs and its impact of smallholder farmers' net farm income in Msinga, KwaZulu-Natal, South Africa. A multi-stage sampling technique was used to obtain cross-sectional farm-level data from a sample of 300 farm households, using a structured questionnaire for the interview. The determinants and impacts of participation were estimated using the propensity score matching (PSM) to account for sample selection bias.
In this paper, is first described the design and development process of a modular ICT application system called GeoFarmer. Geofarmer was designed to provide a means by which farmers can communicate their experiences, both positive and negative, with each other and with experts and consequently better manage their crops and farms. We designed GeoFarmer in a collaborative, incremental and iterative process in which user needs and preferences were paramount.
In this paper, was analyzed farmers' preferences for high-input maize production supported by site-specific nutrient management recommendations provided by an ICT-based extension tool that is being developed for extension services in the maize belt of Nigeria. Was used a choice experiment to provide ex-ante insights on the adoption potentials of site-specific extension services from the perspective of farmers. We control for attribute non-attendance and account for class as well as scale heterogeneity in preferences using different models, and find robust results.
This study, evaluates the intervening influence of extension services on livelihood impacts of drought tolerant maize adoption and the potential mechanisms through which extension can enhance or reduce impact of drought tolerant maize using cross-sectional household level data from smallholder maize producers in Zimbabwe. Specifically, we examine whether access to agriculture extension services influences the relationship between livelihood outcomes and the adoption of drought-tolerant maize varieties in selected districts in the country
Globally, the role of extension agents in scaling up the utilization of Climate Smart Agricultural Initiatives (CSAI) by farmers remains very crucial. This study examined the determinants of the involvement of extension agents in the dissemination of CSAI to farmers. A two-staged random sampling technique was used to elicit information from 277 extension agents in South West Nigeria using a structured questionnaire. Data were analysed using frequency counts, percentage and linear regression analysis
This study aims to contribute to literature on climate smart agriculture (CSA) scaling by identifying institutional and policy strategies that can help effect scaling of CSA practices in developing regions particularly SSA region. Increased adoption rates are more likely to enhance the overall impact of CSA innovations on productivity, food security, livelihoods and overall sustainability of agriculture. Furthermore, the study seeks to highlight and suggest possible approaches/strategies that the research and development community can adopt in taking CSA to scale.