The purpose of this report is to provide some of the groundwork in answering the question of how the CGIAR system and other public agricultural research organisations should adapt and respond to an era of transformation framed by the SDGs. It does this by exploring the way in which this transformation agenda reframes agricultural research and innovation.
Tomando el caso de la agricultura holandesa como ejemplo, en este documento se hace un análisis del surgimiento y el papel de los gestores sistémicos de innovación en el estímulo de la interacción al interior del sistema de innovación agrícola y el desarrollo de la capacidad de innovación, además de reflexionar sobre su posible función en la agricultura de los países en vías de desarrollo y emergentes así como en la forma en que se puede promover su surgimiento y operación.
This paper aims to map the experience of the RIU Asia projects and draw out the main innovation management tactics being observed while laying the groundwork for further research on this topic. It provides a framework to help analyse the sorts of innovation management tasks that are becoming important. This framework distinguishes four elements of innovation management: (i) Functions (ii) Actions (iii) Toolsand (iv) Organisational Format.
This note presents an outline of the main strands of the innovation systems research associated with the ARISA project. It begins by locating this in the current discourse on concepts and policy perspectives on innovation and capacity building before setting out key areas of research inquiry and research activities
A central concern about achieving global food security is reconfiguring agri-food systems towards sustainability. However, historically-informed trajectories of agri-food system development remain resistant to a change in direction. Through a systematic literature review, the authors identify three research domains exploring this phenomenon and six explanations of resistance: embedded nature of technologies, misaligned institutional settings, individual attitudes, political economy factors, infrastructural rigidities, research and innovation priorities.
There are divergent views on what capacity development might mean in relation to agricultural biotechnology. The core of this debate is whether this should involve the development of human capital and research infrastructure, or whether it should encompass a wider range of activities which also include developing the capacity to use knowledge productively. This paper uses the innovation systems concept to shed light on this discussion, arguing that it is innovation capacity rather than science and technology capacity that has to be developed.
The evidence base on agri-food systems is growing exponentially. The CoSAI-commissioned study, Mining the Gaps, applied artificial intelligence to mine more than 1.2 million publications for data, creating a clearer picture of what research has been conducted on small-scale farming and post-production systems from 2000 to the present, and where evidence gaps exist.
A range of approaches and financial instruments have been used to stimulate and support innovation in agriculture and resolve interlocking constraints for uptake at scale. These include innovation platforms, results-based payments, value chain approaches, grants and prizes, incubators, participatory work with farmer networks, and many more.
A huge increase in investment in innovation for agricultural systems is critical to meet the Sustainable Development Goals and Paris Climate Agreement. Most of this increase needs to come from reorienting existing funding for innovation. However, understanding whether an investment will fully promote environmentally sustainable and equitable agri-food systems can be difficult.
The study was designed to answer the following three key questions:
(1) What types of investment instruments have been tested to support innovation in agri-food systems in the Global South, and how can these be categorized into a working typology?
(2) What is the evidence on how well different instruments have supported SAI's multiple objectives (e.g. social equality and environmental) at scale and what contextual and design factors affect their success or failure in achieving these objectives (e.g. type of value chain, who participates)?