This paper examines the design and implementation of a package of capacity strengthening interventions undertaken between March 2007 and March 2011, which aimed to enhance the performance of the national agricultural research system (NARS) in Lesotho. It also identifies some initial outcomes from these interventions and makes recommendations to sustain the process of organisational and institutional change and build on the results that have been achieved.
Early applications of the innovation systems framework to developing-country agriculture suggest opportunities for more intensive and extensive analysis. There is ample scope for empirical studies to make greater use of the theoretical content available in the literature, and to employ more diverse methodologies, both qualitative and quantitative. Further, there is room to improve the relevance of empirical studies to the analysis of public policies that support science, technology, and innovation, as well as to policies that promote poverty reduction and economic growth.
This guide is organized into six chapters with a summary of key steps at the end of each chapter which can be considered as main highlights. Chapter one gives an introduction and an overview of the sequence of the main agricultural research and extension approaches and their shortcomings and hence the reason for the new innovation systems approaches. Chapter two deals with an overview of the InP process covering underlying values and principles, design and processes.
Paper presented to the European Initiative for Agricultural Research and Development (EIARD), 12 January 2015.
This book is about the challenges and practical realities of building the capacity to innovate. It describes the experiences of the Research Into Use (RIU) programme, a five-year, multi-country investment by DFID that aimed to extract development impact from past investments in agricultural research. Specifically, it explores different approaches through which innovation capacities were built.
This report elaborates on how to use the agricultural knowledge and innovation systems framework to promote innovation at different levels with special focus on European issues related to the implementation of Horizon 2020. It is of value as a conceptual and methodological reference regarding the Agricultural Knowledge and Innovation Systems (AKIS).
The State of Food and Agriculture 2014: Innovation in family farming analyses family farms and the role of innovation in ensuring global food security, poverty reduction and environmental sustainability. It argues that family farms must be supported to innovate in ways that promote sustainable intensification of production and improvements in rural livelihoods. Innovation is a process through which farmers improve their production and farm management practices.
Innovation is an important challenge for European agriculture, but little is known about the performance of the Agricultural Knowledge and Innovation Systems (AKIS). This report contributes towards this knowledge, as it reports on experiences from different countries and regions. The systems are very different between countries, regions and sectors.
This book examines how agricultural innovation arises in four African countries – Ghana, Kenya, Tanzania, and Uganda – through the lens of agribusiness, public policies, and specific value chains for food staples, high value products, and livestock. Determinants of innovation are not viewed individually but within the context of a complex agricultural innovation system involving many actors and interactions.
This paper discusses a range of approaches and benchmarks that can guide future design of value chain impact evaluations. Twenty studies were reviewed to understand the status and direction of value chain impact evaluations. A majority of the studies focus on evaluating the impact of only a few interventions, at several levels within the value chains. Few impact evaluations are based on well-constructed, well-conceived comparison groups. Most of them rely on use of propensity score matching to construct counterfactual groups and estimate treatment effects.