Adapting through innovation is one way for rural communities to sustain and improve their livelihoods and environments. Since the 1980s research and development organizations have developed participatory approaches to foster rural innovation. This paper develops a model, called the Learning-to-Innovate (LTI) model, of four basic processes linked to decision making and learning which regulate rate and quality of innovation. The processes are: creating awareness of new opportunities; deciding to adopt; adapting and changing practice; and learning and selecting.

The three system CGIAR research programs on Integrated Systems for the Humid Tropics, Dryland Systems and Aquatic Agricultural Systems have included “capacity to innovate” as an intermediate development outcome in their respective theories of change. The wording of the intermediate development outcome is “increased systems capacity to innovate and contribute to improved livelihoods of low-income agricultural communities.” This note captures the CGIAR's collective thinking about this intermediate development outcome from a systems perspective to clarify it and inspire other programs.

This paper describes the learning selection approach to enabling innovation that capitalizes on the complexity of social systems at different scales of analysis. The first part of the paper describes the approach and how it can be used to guide the early stages of setting up a “grassroots” innovation process. The second part of the paper looks at how the learn selection model can be used “top-down” to guide research investments to trigger large-scale systemic change.

This paper (Part I) present a case study of work conducted by the International Centre for Tropical Agriculture (CIAT) to adapt network mapping techniques to a rural and developing country context. It reports on work in Colombia to develop a prototype network diagnosis tool for use by service providers who work to strengthen small rural groups. It is complemented by a further paper in this issue by Louise Clark (Part II) which presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia.

There have been repeated calls for a ‘new professionalism’ for carrying out agricultural research for development since the 1990s. At the centre of these calls is a recognition that for agricultural research to support the capacities required to face global patterns of change and their implications on rural livelihoods, requires a more systemic, learning focused and reflexive practice that bridges epistemologies and methodologies.

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.

The Applied Research and Innovation Systems in Agriculture project (ARISA) started in December 2014 with the aim of increasing net farm income for 10,000 smallholder farming households in eastern Indonesia. The project was designed to address a key challenge in agricultural research for development: how to ensure that proven research outputs1 are available and accessible for use in farming communities.

This brief discusses the emergence of Asia as a hotpot of innovation and the implications for Australia's own innovation capacity

This paper reflects on the experiences of the Applied Research and Innovation Systems in Agriculture (ARISA) project to caralyse agricultural innovation by bringing RIs and private sector (PS) actors together in partnerships. Facilitating partnerships to caralyse innovation requires capacity building of individuals as well as institutional change. This paper examines the approaches to parnering for innovation, successes, challenges and lessons learned

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.