This paper offers a perspective on the Agricultural Knowledge and Innovation System. The first chapter gives an introduction to the subject and explains the role of SCAR and of the Strategic Working Group AKIS. The second chapter investigates the AKIS and their role in innovation, including the policy context of the European Innovation Partnership “Agricultural productivity and sustainability”. Chapter 3 discusses the relation in a globalised world between Agricultural Research (AR) and Agricultural Research for Development (ARD).
Traditional approaches to innovation systems policymaking and governance often focus exclusively on the central provision of services, regulations, fiscal measures, and subsidies.
A growing variety of public and private agricultural advisory services are available today, leading to increasingly ‘pluralistic service systems’ (PSS) where advisory services are provided by different actors and funded from different sources. This is generally regarded as an important step forward, as it steers away from relying on purely state-led or privatised service systems. PSS hold the potential to overcome constraints related to funding, staffing and expertise, and to make advisory services more demand-driven.
El presente documento se enmarca en el Proyecto “Estrategia de Extensionismo, red de instituciones nacionales e internacionales para proveer el sustento científico y tecnológico para el desarrollo de capacidades y extensionismo rural” y corresponde al entregable del Objetivo Específico 2.1, Documento con lineamientos a nivel político, estratégico y operativo que permitan avanzar en la incorporación de la perspectiva de género en las estrategias de extensionismo de la SAGARPA.
Agricultural knowledge and innovation systems (AKIS) are in transition in many countries from a linear, top-down approach towards more flexible and interactive arrangements. This transition to a system more responsive to changing demands seeks to improve the adoption of innovation in order to strengthen the competitiveness of the agri-food sector. This article focuses on the research and innovation components of the AKIS to analyse the main developments of recent years and their drivers.
In this paper the authors present the development of an analytical framework to study agricultural innovation systems. They divide the agricultural sector into four levels and expand the innovation system approach to study innovation processes.
Nouvel instrument communautaire mobilisant la politique de recherche et la PAC, le PEI entend susciter des partenariats entre les acteurs du développement, de l’enseignement agricole, les agriculteurs, les chercheurs et les entreprises. En cela, il reflète l’évolution récente du cadre de pensée des institutions internationales, qui voient dans l’innovation agricole moins le produit de la recherche et du transfert de connaissances que le résultat d’interactions entre acteurs au sein de réseaux plus ou moins formels.
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 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.