The main purpose of this paper is to take stock of some of the most significant results emanating from The International Development Research Centre (IDRC)‐supported programmes, in recent years in the area of organizational capacity development, and feeding into the consultation process for the formulation of IDRC`s next Corporate Strategy Program Framework (CSPF) for the 2010‐2015 period.
Many capacity development (CD) programs and processes aim at long‐term sustainable change, which depends on seeing many smaller changes in at times almost invisible fields (rules, incentives, behaviours, power, coordination etc.). Yet, most evaluation processes of CD tend to focus on short‐term outputs focused on clearly visible changes.
In this article is presented an emergent capacity development approach that the authors have developed through participatory action research in Peru and Ecuador, which they call ‘systemic theories of change’ (STOC), for organisational capacity development. They argue that capacity development should be understood as systemic learning. The STOC approach promotes reflection about how we as individuals, organisations, and broader social groups and societal configurations, understand how change occurs.
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.
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).
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.
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.
Agricultural innovation is an essential component in achieving the SDG and accelerating the transition to more sustainable and resilient farming systems across the world. Innovations generally emerge from collective intelligence and action, which requires effective agricultural innovation systems (AIS). An AIS perspective has been widely adopted, but the analysis of AIS, especially at country level, remains a challenge. The need for and potential of a diagnostic tool for AIS analysis is currently receiving attention in the global agricultural policy debate.