The privatization of agricultural research and extension establishments worldwide has led to the development of a market for services designed to support agricultural innovation. However, due to market and systemic failures, both supply side and demand side parties in this market have experienced constraints in effecting transactions and establishing the necessary relationships to engage in demand-driven innovation processes.

Most cocoa farmers in Ghana do not adopt research recommendations because they cannot afford the cost, therefore, yields are low. Integrated pest management (IPM) technologies that rely on low external inputs were tried with a group of farmers. The technologies included using aqueous neem seed extracts to control capsids; removing diseased pods to reduce blackpod incidence; controlling mistletoes, epiphytes, weeds; and managing shade. Although yields increased significantly, adoption was constrained by technical, social and economic factors.

The capacity of existing monitoring and decision making tools in generating evidence about the performance of R4D with multi-stakeholder processes, such as innovation platforms (IPs), public private partnerships (PPP), participatory value chain management (PVCM) is very limited. Results of these tools are either contextual and qualitative such as case studies that can not be used by other R4D interventions or quantitative i.e. impact assessments that do not inform what works in R4D.

According to the authors of this paper, actual methods of scaling are rather empirical and based on the premise of ‘find out what works in one place and do more of the same, in another place’. These methods thus would not sufficiently take into account complex realities beyond the concepts of innovation transfer, dissemination, diffusion and adoption. As a consequence, scaling initiatives often do not produce the desired effect.

Increasingly, value chain approaches are integrated with multi-stakeholder processes to facilitate inclusive innovation and value chain upgrading of smallholders. This pathway to smallholder integration into agri-food markets has received limited analysis. This article analyses this integration through a case study of an ongoing smallholder dairy development programme in Tanzania.

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.

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.