While the Agricultural Science and Technology Indicators (ASTI) initiative provides data and analysis of domestic public and private spending on agricultural research and development for a wide range of developing countries, the literature pays little attention, if any, to foreign assistance to agricultural, fishing and forestry research and agricultural extension. The objective of the present study is to fill this gap.
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.
Agricultural innovation in low-income tropical countries contributes to a more effective and sustainable use of natural resources and reduces hunger and poverty through economic development in rural areas. Yet, despite numerous recent public and private initiatives to develop capacities for agricultural innovation, such initiatives are often not well aligned with national efforts to revive existing Agricultural Innovation Systems (AIS).
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.
Research, extension, and advisory services are some of the most knowledge-intensive elements of agricultural innovation systems. They are also among the heaviest users of information communication technologies (ICTs). This module introduces ICT developments in the wider innovation and knowledge systems as well as explores drivers of ICT use in research and extension.
This study explores the properties of innovation systems and their contribution to increased eco-efficiency in agriculture. Using aggregate data and econometric methods, the eco-efficiency of 79 countries was computed and a range of factors relating to research, extension, business and policy was examined. Despite data limitations, the analysis produced significant results.
This paper presents the common framework on CD for AIS developed by TAP and points to the relevance of meta-learning and the importance of “functional capacities”, if higher education institutions and their graduates are to become active players in the agricultural innovation system. The Framework was developed through an inclusive, participatory and multi-stakeholders approach with contributions by TAP Partners, including FARA and the Global Conference on Higher Education and Research in Agriculture.
En los últimos años, han surgido nuevas oportunidades que permiten que las organizaciones de investigación adopten prácticas innovadoras que fomentan la gestión y el intercambio del conocimiento, tanto a nivel interno como entre sus respectivas redes.
This study explores the properties of innovation systems and their contribution to increased eco-efficiency in agriculture. Using aggregate data and econometric methods, the eco-efficiency of 79 countries was computed and a range of factors relating to research, extension, business and policy was examined. Despite data limitations, the analysis produced some interesting insights. For instance public research spending has a positive significant effect for emerging economies, while no statistically significant effect was found for foreign aid for research.
Participatory Impact Pathways Analysis (PIPA) is a practical approach to planning, monitoring and evaluation, developed for use with complex research-for-development projects. PIPA begins with a participatory workshop where stakeholders make explicit their assumptions about how their project will make an impact, and produce an ‘Outcomes logic model’ and an ‘Impact logic model’. These two logic models provide an ex-ante framework of predictions of impact that can also be used in priority setting and ex-post impact assessment.