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.
The challenges faced by agricultural systems call for an advance in risk management (RM) assessments. This research identifies and discusses potential improvements to RM across 11 European Union (EU) farming systems (FS). The paper proposes a comprehensive, participatory approach that accounts for multi-stakeholder perspectives relying on 11 focus groups for brainstorming and gathering suggestions to improve RM.
The “ONE WORLD – No Hunger” Initiative (SEWOH) by the German Federal Ministry for Economic Cooperation and Development (BMZ) is part of the G7 goal to free 500 million people from hunger and malnourishment by 2030. SEWOH intends to contribute significantly to reducing poverty and hunger in developing countries in general and Cameroon in particular. The Cameroonian project is part of the framework of the global project – “Green Innovation Centres for the Agriculture and Food Sector” (ProCISA).
This toolbox has been developed to collate different tools and methods that can be used for food system analysis.
It is specifically based on systems thinking for food system analysis, with the aim to formulate actionable recommendations that can bring about systemic change.It describes both the process of a food system analysis, as well as a set of tools that can be used at different stages.
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)?
This shift in thinking will require major shifts in policy, research, and investment. But where should these investments go? What foundations should be strengthened? Which gaps need filling? What’s working? What’s not?
In order to answer these questions in an informed way, we need to examine the evidence that exists and identify areas where more research is needed.
But this is easier said than done.
This paper discusses innovation in low and middle-income countries, focusing on the role it has played in local and national responses to the COVID-19 pandemic, and the lessons from this effort for how innovation might be harnessed to address wider development and humanitarian challenges by mobilising resources, improving processes, catalysing collaboration and encouraging creative and contextually grounded approaches. The paper also examines how international development and humanitarian organisations can improve their support for local and national innovation efforts.
One-fifth of the innovative solutions to fight the Covid-19 pandemic have emerged from low and middle-income countries, and these responses offer promising insights for how we think about, manage, and enable innovation. As the international community now faces the historic challenge of vaccinating the world, more attention and resources must be directed to the innovators who are developing technically novel, contextually relevant, and socially inclusive alternatives to mainstream innovation management practices.
This study draws on social-psychology in an attempt to identify the various motivations for technology adoption (TA), including both economic and non-economic, and to gain insights into how and why Brazilian innovative beef farmers make decisions about whether or not to adopt particular technologies.