This paper argues that impact assessment research has not made more of a difference because the measurement of the economic impact has poor diagnostic power. In particular it fails to provide research managers with critical institutional lessons concerning ways of improving research and innovation as a process. Paper's contention is that the linear input-output assumptions of economic assessment need to be complemented by an analytical framework that recognizes systems of reflexive, learning interactions and their location in, and relationship with, their institutional context.
There are divergent views on what capacity development might mean in relation to agricultural biotechnology. The core of this debate is whether this should involve the development of human capital and research infrastructure, or whether it should encompass a wider range of activities which also include developing the capacity to use knowledge productively. This paper uses the innovation systems concept to shed light on this discussion, arguing that it is innovation capacity rather than science and technology capacity that has to be developed.
This paper reviews a recent donor-funded project concerning the introduction of post-harvest technology to poor hill farmers in India. Rather than conform to conventional development aid projects of either a “research” or an “interventionist” nature, it combines both approaches in a research-action program, which has more in common with a business development approach than a formal social science one. An important conclusion is that the work (and apparent success) of the project is consistent with an understanding of development that emphasizes the importance of innovation systems.
Innovation platforms (IPs) are a way of organizing multistakeholder interactions, marshalling ideas, people and resources to address challenges and opportunities embedded in complex settings. The approach has its roots in theories of complexity, the concept of innovation systems and practices of participatory action research. IPs have been widely adopted across Africa and beyond in recent years as a “must have” tool in a range of “for development” modes of agricultural research.
This paper describes the learning selection approach to enabling innovation that capitalizes on the complexity of social systems at different scales of analysis. The first part of the paper describes the approach and how it can be used to guide the early stages of setting up a “grassroots” innovation process. The second part of the paper looks at how the learn selection model can be used “top-down” to guide research investments to trigger large-scale systemic change.
This paper (Part I) present a case study of work conducted by the International Centre for Tropical Agriculture (CIAT) to adapt network mapping techniques to a rural and developing country context. It reports on work in Colombia to develop a prototype network diagnosis tool for use by service providers who work to strengthen small rural groups. It is complemented by a further paper in this issue by Louise Clark (Part II) which presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia.
There have been repeated calls for a ‘new professionalism’ for carrying out agricultural research for development since the 1990s. At the centre of these calls is a recognition that for agricultural research to support the capacities required to face global patterns of change and their implications on rural livelihoods, requires a more systemic, learning focused and reflexive practice that bridges epistemologies and methodologies.