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).

This report is about the Directorate General for Development and Cooperation (DEVCO) approach to Agricultural Research for Development (AR4D) in the context of how well it responds to current policy priorities in sustainable agriculture, nutrition and resilience, and how it is positioned within the European and global agenda to achieve maximum impact. The approach builds on lessons learned and reviews and evaluations of research under AR4D portfolio under the Food Security Thematic Programme.

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.

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.

The main objective of the Guidelines is to provide a non-binding complement to other guidelines and offer advice to RDP evaluation stakeholders on how to carry out the evaluation activities for answering the common evaluation questions related to innovation. Since the RDP’s effects on innovation in rural areas can be expected to take place, most likely, in the long-term, the guidelines focus in particular on those evaluation related activities, which will be reported in the AIR in 2019 and in the ex post evaluation. The Guidelines are structured in three parts:

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.