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.
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.
The capacity-focused problem tree pinpoints a core capacity issue, along with its causes and effects. It helps clarify the precise capacity-development objectives that the intervention aims to achieve. The focus should be on functional capacity, but room should be left to acknowledge technical capacity issues too.
The Action Planning is a tool that formalizes commitments and plots the route to their implementation. An action plan is intended for the use of the core actors, who will have been identified beforehand in the visioning phase. It determines who does what and when, and is therefore essential to ensuring that things get done and that the goals and visions set out in the capacity development strategy are achieved.
En la región centro-norte de Nicaragua, las organizaciones locales que trabajan con sistemas productivos de café, cacao y mixtos han unido esfuerzos bajo las Alianzas Territoriales de Aprendizaje impulsadas por CIAT, a través del Programa de Investigación de CGIAR sobre Sistemas Integrados del Trópico Húmedo (Humidtropics).
Extension and advisory services (EAS) perform an important role in agricultural development and help reduce hunger and poverty. Development efforts are increasingly complicated because of challenges such as natural resource depletion and climate change. Agricultural development frameworks have moved from a linear to a more complex systems perspective. Many scholars today use the agricultural innovation systems (AIS) framework as a conceptual model.
Though research on communication and innovation during the last decade brought better understanding on the innovation process, this has not influenced the underlying paradigm and practice of Extension and Advisory Services (EAS) in most countries. At the same time there have been few initiatives that tried to experiment with new ways of developing capacities for extension and innovation.
This is the first chapter of the book "Innovation platforms for agricultural development: Evaluating the mature innovation platforms landscape". It introduces the background, case study competition process, case study characterization and readers’ guide, and book outline. Characterization of the case studies includes their geographical spread, age and life stage of the platforms, and specific information on the multi-stakeholder processes, the content matter, platform support functions, and outcomes and impacts.
There is increasing demand for institutional reform in the agricultural sciences. This paper presents lessons from the content and directions in soil science research in India, to make a case for institutional reform in the agricultural sciences. It demonstrates how existing institutional and organizational contexts shape the research content of the soil sciences and its sub-disciplines. These contexts also shape the capacity of the soil sciences to understand and partner with other components of the wider natural resource management (NRM) innovation systems.
This paper reportson the implementation of a conceptual framework to carry out an impact evaluation of multi-stakeholder innovation systems using the NLA as the object of study. The assessment focused on the business relationship constructs of trust and capacity development. Survey interviews, in-depth interviews and focus group discussions collected data from agribusiness stakeholders linked with the NLA and from a control group of stakeholders involved with other networks. The quantitative data were analysed through factor and regression analyses