The aim of this document is to produce a state-of-the-art of the academic literature in order to identify theories and concepts available for: a) describing the structure, the dynamics and the functioning of agricultural advisory services; b) understanding how these services are embedded into national Agricultural Knowledge and Innovation Systems (AKIS), and into various agricultural and rural policies across the European Union (EU) countries; c) providing some conceptual elements to support the methodology for an inventory of agricultural advisory services in EU 27 countries (WP3 of the PR
Recently, Agricultural Knowledge and Innovation Systems (AKISs) have gained considerable attention in scientific and political forums in the European Union (EU). AKIS is considered a key concept in identifying, analysing and assessing the various actors in the agricultural sector as well as their communication and interaction for innovation processes. Using qualitative expert interviews and organizational mapping, the features of national AKISs were investigated in selected EU member states (Belgium, France, Ireland, Germany, Portugal and the UK).
The report specifically analyses the NIS in Peru and Colombia in the coffee and dairy sectors due to their economic importance for both countries and the large percentage of small producers in these sectors. In order to analyse the NIS, we have utilised an innovations systems approach to form the analytical framework. This framework focuses on four main areas – understanding the actors in the NIS, their roles and attitudes, the patterns of interaction of these actors, and the enabling environment with a focus on small producer inclusion.
This brief explores the definition of Agricultural Knowledge and Information System (AKIS) and the inventory of AKIS in Europe.
This paper examines the level of heterogeneity of member countries of the Organisation for Economic Co-operation and Development (OECD), regarding their potential and performance as Agricultural Sectoral Innovation Systems (ASIS). The main objective is the classification of the ASIS in an OECD context; based on a series of indicators that correspond to their productivity, competitiveness, social, economic and institutional conditions, as well as their capacities and innovation results.
Innovation learning platforms have their roots in the agricultural innovation systems (AIS) approach. AIS emphasizes a systems view of agricultural innovations and conceptualizes an innovation system as all individuals and organizations that keep on interacting in producing and using knowledge and the institutional context of knowledge sharing and learning. Research creates knowledge and technology; but innovation process goes further to include putting that knowledge into use.
Capacity development interventions in support of agricultural innovation are more effective when based on systematic and participatory assessments of existing skills and capacity needs. Recognizing that, an instrument has been developed in the context of the Capacity Development for Agricultural Innovation Systems (CDAIS) project. It consists of a capacity scoring tool that allows assessing innovation capacities, identifying strengths and weaknesses and monitoring capacity changes over time. This paper describes the scoring tool and provides guidelines on how to apply it successfully.
In an effort to raise incomes and increase resilience of smallholder farmers and their families in Feed the Future1 (FTF) countries, the United States Agency for International Development (USAID) funded the Developing Local Extension Capacity (DLEC) project. This project is led by Digital Green in partnership with the International Food Policy Research Institute (IFPRI), CARE International (CARE) and multiple resource partners.
This document on Good Practices in Extension Research and Evaluation is developed as a hands on reference manual to help young researchers, research students, and field extension functionaries in choosing the right research methods for conducting quality research and evaluation in extension. This manual has been compiled by the resource persons who participated in the Workshop on ‘Good
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.