This training manual was prepared under the EU-funded project Capacity Development for Agricultural Innovation Systems (CDAIS), a global partnership (Agrinatura, FAO and 8 pilot countries) that aims to strengthen the capacity of countries and key stakeholders to innovate in complex agricultural systems, thereby achieving improved rural livelihoods.
There is widespread need for gender-responsive agricultural research, yet the question of how this kind of research can be implemented and its success measured needs further interrogation. This paper presents a framework, developed on the basis of literature and validated by experts, for tracking the gender responsiveness of agricultural research throughout the research cycle, from the research plan to the dissemination of research findings. The framework was tested in Uganda and Rwanda on 14 research projects considered to be gender-responsive.
A growing variety of public and private rural advisory services are available today, leading to increasingly pluralistic service systems (PSS) – in which advisory services are provided by different actors and funded from different sources. PSS have emerged in many countries as a response to a decline in public sector extension and the increasing demand for tailored, diverse and market-oriented services. Private companies, non-governmental organizations and producer organizations, today play more active roles alongside traditional public sector providers.
These Proceedings report on the second International Conference of the Convergence of Sciences (CoS) programme in Elmina (2009). The first International Conference was four years earlier in the same location, where it was discussed how to follow up on the findings of the first CoS Programme phase (entitled CoS1 running from 2001 to 2006). The Conference was intended to introduce the focus on “innovation systems”, and how to enhance these systems for smallholder farmers’ development.
This paper discusses the challenges and determinants of agro-operations and innovation initiatives in developing countries. With particular reference to the Caribbean region, available country statistics and data are analysed. A generic model of collaborative innovation for agriculture that stresses collaboration among the stakeholders (government, knowledge institutions, public and private firms and others) is described.
In this paper, presented at the 8th European IFSA Symposium ( Workshop 6: "Change in knowledge systems and extension services: Role of the new actors") in 2008, the authors discuss a conceptual framework that understands innovation processes as the outcome of collaborative networks where information is exchanged and learning processes happen. They argue that technical and economic factors used to analyse drivers and barriers alone are not sufficient to understand innovation processes.
The timeline tool is generally put to use when stakeholders embark upon the self-assessment phase of their innovation partnership. Stakeholders are asked to recall moments they feel were significant for the partnership, from its beginning to the present and to reflect upon how the partnership has evolved since it began.
Social Network Analysis is a practical and useful tool that looks at the linkages present in an innovation network and monitors their development over time. It maps the relationships between the stakeholders in the network and highlights the changes between them.
This tool enables participants to become cognisant of the functional capacities discovered through the capacity scoring questionnaire, and test the limits of these capacities through simulations or role-playing (e.g. problem-solving, collaboration, information sharing, and engagement). The simulation game leads to an intuitive understanding of innovation capacities and of the importance of the enabling environment, helping participants to learn about the significance of these capacities.
This tool was designed to assess innovation capacities, identify strengths and weaknesses and monitor capacity changes over time. The scoring tool makes it clear which functional capacities are going to be needed to promote, lead or successfully participate in innovation processes. The tool evaluates capacities on the basis of 21 indicators (each of which is graded on a scale from 0 (low capacity) to 3 (high capacity), and build on the key innovation capacities identified in the capacity needs assessment.