This concept note has been developed within the context of the EU-funded CDAIS project, which is jointly implemented by AGRINATURA-EEIG and the Food and Agriculture Organization of the United Nations (FAO) to support the TAP Action Plan in eight pilot countries in Africa (Angola, Burkina Faso, Ethiopia, Rwanda), Asia (Bangladesh, Laos) and Central America (Guatemala, Honduras) .
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.
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 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.
Galvanizing the commitment of agricultural innovation systems (AIS) actors through learning, participation and reflection is a prerequisite for capacity development (CD) initiatives. This phase ensures both a common understanding of the process of CD for AIS as well as to create ownership and high-level support by those that head and lead representative bodies of actors within the system.
This report highlights the great potential of the agribusiness sector in Africa by drawing on experience in Africa as well as other regions. The evidence demonstrates that good policies, a conducive business environment, and strategic support from governments can help agribusiness reach its potential. Africa is now at a crossroads, from which it can take concrete steps to realize its potential or continue to lose competitiveness, missing a major opportunity for increased growth, employment, and food security. The report pursues several lines of analysis.
The Feed the Future Asia Innovative Farmers Activity (AIFA) is a regional project transforming the lives of farmers by developing and supporting a regional technology ecosystem that fosters new technology, partnerships, and innovative practices in South and Southeast Asia with a focus on Bangladesh, Cambodia, and Nepal. The project aims to build a diverse regional agricultural innovation community that can test, adapt, and share the latest practices and technologies with smallholder farmers in the region.
The Feed the Future Asia Innovative Farmers Activity (AIFA) is a regional project working to facilitate the scaling of critical agricultural technologies through regional partnership and technology transfer. The project works with a range of agricultural technology stakeholders on a regional basis (private sector, research institutions, governments, networks, etc.) to increase food security, reduce poverty, and improve environmental sustainability by facilitating agricultural innovation and technology diffusion in the Asia region.
The study first identified fully efficient farmers and then estimated technical efficiency of inefficient farmers, identifying their determinants by applying a Zero Inefficiency Stochastic Frontier Model (ZISFM) on a sample of 300 rice farmers from central-northern Thailand. Next, the study developed scenarios of potential production increase and resource conservation if technical inefficiency was eliminated. Results revealed that 13% of the sampled farmers were fully efficient, thereby justifying the use of our approach.