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CONTEXT: Understanding research collaboration in diverse scientific communities is key to building global agricultural research systems that support the UN Sustainable Development Goals. Characterizing collaboration patterns can inform decisions to enhance the structure and dynamics of research programs. OBJECTIVE: We introduce a new analytic framework for evaluating collaborative research networks based on scientific publications, and an associated conceptual framework for the role of research networks in achieving societal goals. We analyzed two CGIAR Research Programs: Grain Legumes and Dryland Cereals (GLDC) and Roots, Tubers and Bananas (RTB). The analysis provides a multi-dimensional perspective on a set of key questions related to research team composition, research management structures, and performance of scientific publications. METHODS: We quantified network structures of research collaborations at the level of authors, institutions, countries, and management structures, including use of temporal exponential random graph models. We used regression models to understand the associations between the characteristics of authors and publications, and the corresponding citation rates and Altmetric Attention Scores. RESULTS AND CONCLUSIONS: We identified key network hubs in the collaboration networks of both CGIAR programs. The proportion of women as authors in publications was less than a third, with a low likelihood of co-authorship between women. Institutional hubs were identified by institutional categories; these were often institutions that are considered CGIAR program “participants”, and a few were “planning partners”. For both GLDC and RTB, the countries that were the focus of most research coincided with the program's priority countries. Most international collaborations occurred between institutions headquartered in Global South countries, but most intercontinental collaborations occurred between Global South and Global North countries. Most institution

Influencing policy is an important scaling mechanism. However, if a program is to plausibly claim that it has or can influence policy, it needs to explain how. This is not straightforward because of the complex nature of policy change. Scholars suggest the use of theory to help answer the 'how' question. In this article, we show how, in practice, a middle-range policy change theory—Kingdon's Policy Window theory—helped us model the workings of four outcome trajectories that produced agricultural policy outcomes in four cases. By providing a common framework, the middle-range theory helped accumulate learning from one evaluation to the next, generating specific and generalizable insights in the process. Accumulation learning in this way can help organizations become more convincing in the proposals they write to donors, more accountable and better able to identify and deliver on their goals.

Systems approaches are widely promoted for inclusive innovation, but their use and results are seldom evaluated. We assessed applications of the Participatory Market Chain Approach (PMCA), which combines elements of innovation system and value chain approaches, in eight cases in Africa, Asia, Europe, and Latin America. We found that the PMCA performed best where the policy environment favoured value chain development, the chain offered significant potential for value addition, and the PMCA was implemented with high fidelity to its basic principles, and as part of a larger development effort. Facilitation was crucial for developing locally appropriate implementation procedures and engaging smallholders, commercial entrepreneurs, researchers, and other service providers throughout the PMCA application. By focusing on commercial innovation, the PMCA offered a strategic entry point for stimulating more systemic innovation. We conclude with six lessons on (1) how commercial innovation can trigger broader innovation; (2) the need to engage commercial entrepreneurs in innovation processes; (3) the importance of committed, motivated and capable facilitators; (4) the advantage of embedding the PMCA in a broader development effort; (5) how systems approaches can help R&D organizations respond better to market demands; and (6) the contributions of systems approaches to innovation capacity.

Native potato production is an important livelihood strategy for most rural Andean families. An inclusive value chain development approach triggered innovation processes in Peru’s potato sector, benefiting small-scale producers and value chain actors and improving theirlivelihoods, although the magnitude of the effects on poverty reduction remains to be determined, La producción de papa nativa es una de las estrategias para generar ingresos y mejorar el bienestar para la mayoría de las familias rurales andinas. Un enfoque de desarrollo inclusivo de la cadena de valor desencadenó procesos de innovación en el sector dela papa en el Perú, contribuyendo a las estrategias de desarrollo de los medios de vida de los agricultores andinos y actores de la cadena de mercado, aunque la magnitud específica de los efectos en la reducción de la pobreza aún está por determinarse

Seed systems research is central to achieving the United Nations Sustainable Development Goals. Improved varieties with promise for ending hunger, improving nutrition, and increasing livelihood security may be released, but how do they reach and benefit different types of farmers? Without widespread adoption the genetic gains achieved with improved crop varieties can never be actualized. Progress has been made toward demand responsive breeding, however the draft CGIAR 2030 Research and Innovation Strategy fails to recognize the complexity of seed systems and thus presents a narrow vision for the future of seed systems research. This points to the lack of evidence-based dialogue between seed systems researchers and breeders. This perspective paper presents findings from an interdisciplinary group of more than 50 CGIAR scientists who used a suite of seed systems tools to identify four knowledge gaps and associated insights from work on the seed systems for vegetatively propagated crops (VPCs), focusing on bananas (especially cooking bananas and plantains), cassava, potato, sweetpotato, and yam. We discuss the implications for thinking about and intervening in seed systems using a combined biophysical and socioeconomic perspective and how this can contribute to increased varietal adoption and benefits to farmers. The tools merit wider use, not only for the seed systems of VPCs, but for the seed of crops facing similar adoption challenges. We argue for deeper collaboration between seed systems researchers, breeders and national seed system stakeholders to address these and other knowledge gaps and generate the evidence and innovations needed to break through the 40% adoption ceiling for modern varieties, and ensure good quality seed once the new varieties have been adopted. Without this, the achievements of breeders may remain stuck in the seed delivery pipeline.

Scaling of innovations is a key requirement for addressing societal challenges in sectors such as health, agriculture, and the environment. Research for development (R4D) programs, projects and other interventions struggle to make particular innovations go to scale. Current conceptualizations of scaling are often too simplistic; more systemic and multidimensional perspectives, frameworks and measures are needed. There is a gap between new complexity-aware theories and perspectives on innovation, and tools and approaches that can improve strategic and operational decision-making in R4D interventions that aim to scale innovations. This paper aims to bridge that gap by developing the key concepts and measures of Scaling Readiness. Scaling Readiness is an approach that encourages critical reflection on how ready innovations are for scaling and what appropriate actions could accelerate or enhance scaling. Scaling Readiness provides action-oriented support for (1) characterizing the innovation and innovation system; (2) diagnosing the current readiness and use of innovations as a proxy for their readiness to scale; (3) developing strategy to overcome bottlenecks for scaling; (4) facilitating and negotiating multi-stakeholder innovation and scaling processes; and (5) navigating and monitoring the implementation process to allow for adaptive management. Scaling Readiness has the potential to support evidence-based scaling strategy design, implementation and monitoring, and – if applied across multiple interventions – can be used to manage a portfolio of innovation and scaling investments.

This Editorial to the Special Issue “Science of Scaling: connecting the pathways of agricultural research and development for improved food, income and nutrition security” presents the framing, overview and analysis of 10 articles focussed on scaling innovation in the agricultural research for development sector. The publications cut across three categories that focus on: (i) Understanding the scaling trajectory retrospectively from a longer term, systems perspective, (ii) Understanding scaling of innovation retrospectively as part of shorter term agricultural research for development interventions, and (iii) Conceptual or methodological approaches aimed at guiding scaling prospectively. Cross-cutting review of the publications leads to several insights and critically questions dominant ways of understanding and guiding scaling of innovation in the agricultural research for development sector. This provides a starting point for proposing more outcome-oriented scaling as a third wave of understanding and guiding scaling, beyond technology adoption (first wave) and the scaling of innovation (second wave). The Editorial proposes three Research Domains for the Science of Scaling: (1) ‘Understand the big picture of scaling innovation’ that can inform more realistic ideas about the factors, conditions and dynamics that affect innovation and scaling processes; (2) ‘Develop instruments that nurture efficient and responsible scaling’ that comprises new approaches, concepts and tools that can facilitate the development of evidence-based scaling strategies; and (3) ‘Create a conducive environment for scaling innovation’ that focusses on the institutional arrangements, partnership models, and monitoring and learning for scaling of innovation.