Based on farmer and value chain actor interviews, this comparative study of five emerging dairy clusters elaborates on the upgrading of farming systems, value chains, and context shapes transformations from semi-subsistent to market-oriented dairy farming. The main results show unequal cluster upgrading along two intensification dimensions: dairy feeding system and cash cropping. Intensive dairy is competing with other high-value cash crop options that resource-endowed farmers specialize in, given conducive support service arrangements and context conditions.
At present, agricultural policies in Kenya often ignore specific target groups because there is a lack of contextual information on farmers’ specific socio-economic conditions. The aim of this study was to fill this knowledge gap by answering the following research questions: 1. What determines the adaptive capacity of AIV farmers in Kenya? 2. How does access to capital assets differ by farming household characteristics and between the selected areas? 3. What are the AC levels of AIV farmers in the selected zones of Kenya? 4.
In this study, it is applies a participatory scenario modelling framework to assess potential societal responses to the impacts of climate change by the mid-21st century, and model consequent land use and land cover change scenarios under different livelihood futures as guided by communities’ members in the areas under investigation. The authors focused their analysis on two montane sites of the Eastern Afromontane Biodiversity Hotspot , the Taita Hills, Kenya, and a montane area north-west of Jimma, Ethiopia
The dynamic nature of climate and its impacts on agriculture is rendering most of the existing adaptation and coping strategies unsupportive in many regions.
Globalization, urbanization and new market demands - together with ever-increasing quality and safety requirements - are putting significantly greater pressures on agrifood stakeholders in the world. The ability to respond to new challenges and opportunities is important not just for producers but also for industries in developing countries. This paper aims to present what "innovation response capacity" entails, especially for natural resourcebased industries in a developing country context.
This article investigates determinants and impacts of cooperative organization, using the example of smallholder banana farmers in Kenya. Farmer groups are inclusive of the poor, although wealthier households are more likely to join. Employing propensity score matching, we find positive income effects for active group members. Yet price advantages of collective marketing are small, and high-value market potentials have not yet been tapped. Beyond prices, farmer groups function as important catalysts for innovation adoption through promoting efficient information flows.
Classical innovation adoption models implicitly assume homogenous information flow across farmers, which is often not realistic. As a result, selection bias in adoption parameters may occur. We focus on tissue culture (TC) banana technology that was introduced in Kenya more than 10 years ago. Up till now, adoption rates have remained relatively low.
With the commercialization of agriculture, women are increasingly disadvantaged because of persistent gender disparities in access to productive resources. Farmer collective action that intends to improve smallholder access to markets and technology could potentially accelerate this trend. Here, we use survey data of small-scale banana producers in Kenya to investigate the gender implications of recently established farmer groups. Traditionally, banana has been a women’s crop in Kenya. Our results confirm that the groups contribute to increasing male control over banana.
The recent proliferation of mobile phones in rural Africa has also led to increased interest in mobile financial services (MFS), such as mobile money and mobile banking. Such services are often portrayed as promising tools to improve agricultural finance, especially among smallholders who are typically underserved by traditional banks. However, empirical evidence on the actual use of MFS for agricultural activities is thin. Here, we use nationally representative data from Kenya to analyze the use of mobile payments, mobile savings, and mobile credit among the farming population.