This paper examines how the different institutional innovations arising from various permutations of linkages and interactions of ARD organizations (national, international advanced agricultural research centres and universities) influenced the different outcomes in addressing identified ARD problems.
The process of knowledge brokering in the agricultural sector, where it is generally called agricultural extension, has been studied since the 1950s. While agricultural extension initially employed research push models, it gradually moved towards research pull and collaborative research models. The current agricultural innovation systems perspective goes beyond seeing research as the main input to change and innovation, and recognises that innovation emerges from the complex interactions among multiple actors and is about fostering combined technical, social and institutional change.
This paper traces the evolution of the innovation systems framework within the agricultural sector in Sub-Saharan Africa, and presents a conceptual framework for agricultural innovation systems. The difference between innovation ecology/ecosystems and intervention-based innovations systems is highlighted, given that these two concepts are used at different levels in promoting and sustaining agricultural innovations.
Net-Map is an interview-based mapping tool that helps people understand, visualize, discuss, and improve situations in which many different actors influence outcomes. By creating Influence Network Maps, individuals and groups can clarify their own view of a situation, foster discussion, and develop a strategic approach to their networking activities.
This paper presents the processes, general guidelines lessons and experiences pertaining to “good practices” for organizing and forming Agricultural Innovation Platforms in the Lake Kivu Pilot Learning Site, covering three countries (Uganda, Rwanda and Democratic Republic of Congo) with widely differing social political environments to address agricultural development challenges.
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.
This paper captures lessons from recent experiences on using ‘theories of change’ amongst organisations involved in the research–policy interface. The literature in this area highlights much of the complexity inherent in the policymaking process, as well as the challenges around finding meaningful ways to measure research uptake. As a tool, ‘theories of change’ offers much, but the paper argues that the very complexity and dynamism of the research-to-policy process means that any theory of change will be inadequate in this context.
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.