Over the last 10 years much has been written about the role of the private sector as part of a more widely-conceived notion of agricultural sector capacity for innovation and development. This paper discusses the emergence of a new class of private enterprise in East Africa that would seem to have an important role in efforts to tackle poverty reduction and food security. These organisations appear to occupy a niche that sits between mainstream for-profit enterprises and the developmental activities of government programmes, NGOs and development projects.
This paper investigates Innovation Systems Concepts and Principles starting with an historical perspective. Then it analyzes their application to Integrated Agricultural Research for Development (IAR4D) and makes a comparison between the traditional Research and Development Systems Approaches and the Innovation Systems Approach.
This study was undertaken to assess the utility of remotely sensed net primary productivity (NPP) data to measure agricultural sustainability by applying a new methodology that captures spatial variability and trends in total NPP and in NPP removed at harvest. The sustainable intensification of agriculture is widely promoted as a means for achieving the Sustainable Development Goals (SDGs) and transitioning toward a more productive, sustainable, and inclusive agriculture, particularity in fragile environments.
Participation is connected to technology through the notion of innovation systems. To make the connection work, it is argued, the focus has to shift from a framing of participation in terms of democratic entitlement to a framing in terms of the settlement of issues (i.e. politics from below), The innovation system is an appropriate notion to see where issues are likely to lock on to processes of technological change.
Research and analysis of agricultural innovation processes and policies over the last 20 years has made a major contribution to scholarship on and the understanding of the nature of innovation. To an important, but much lesser degree this has also led to re-framing practice at the research-innovation interface. Innovation studies (for want of a better word), like many branches of science, finds that it needs to deliver solutions across the full spectrum of discovery (concepts and theories) to application in both policy and practice domains.
Mobile phone based money services have spread rapidly in many developing countries. We analyze micro level impacts using panel data from smallholder farmers in Kenya. Mobile money use has a large positive net impact on household income. One important pathway is through remittances, which contribute to income directly but also help to reduce risk and liquidity constraints, thus promoting agricultural commercialization. Mobile money users apply more purchased inputs, market a larger proportion of their output, and have higher farm profits.
Supermarkets and high-value exports are currently gaining ground in the agri-food systems of many developing countries. While recent research has analyzed income effects in the small farm sector, impacts on farming efficiency have hardly been studied. Using a survey of Kenyan vegetable growers and a stochastic frontier approach, we show that participation in supermarket channels increases mean technical efficiency by 19%. This gain is bigger at lower levels of efficiency, suggesting the potential for positive income distribution effects.
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.
Most micro-level studies on the impact of agricultural technologies build on cross-section data, which can lead to unreliable impact estimates. Here, we use panel data covering two time periods to estimate the impact of tissue culture (TC) banana technology in the Kenyan small farm sector. TC banana is an interesting case, because previous impact studies showed mixed results. We combine propensity score matching with a difference-in-difference estimator to control for selection bias and account for temporal impact variability.