This paper explores the use of complex adaptive systems theory in development policy analysis using a case study drawn from recent events in Uganda. It documents the changes that took place in the farming system in Soroti district during an outbreak of African cassava mosaic virus disease (ACMVD) and the subsequent decline in cassava production — the main staple food in the area. Resultant adaptation impacts are analysed across cropping, biological, economic and social systems each of which operate as an interlinked sub-system.

This paper argues that impact assessment research has not made more of a difference because the measurement of the economic impact has poor diagnostic power. In particular it fails to provide research managers with critical institutional lessons concerning ways of improving research and innovation as a process. Paper's contention is that the linear input-output assumptions of economic assessment need to be complemented by an analytical framework that recognizes systems of reflexive, learning interactions and their location in, and relationship with, their institutional context.

In the post-harvest area and in agriculture research in general, both in India and internationally, policy attention is returning to the question of how innovation can be encouraged and promoted and thus how impact on the poor can be achieved. This publication assembles several cases from the post-harvest sector. These provide examples of successful innovation that emerged in quite different ways. Its purpose is to illustrate and analyze the diversity and often highly context-specific nature of the processes that lead to and promote innovation.

This policy brief sets out the conceptual and empirical underpinnings of a learning-orientated monitoring and evaluation approach known as Institutional Learning and Change (ILAC) and discusses options for learning-oriented interventions and policy research. 

This paper reviews a recent donor-funded project concerning the introduction of post-harvest technology to poor hill farmers in India. Rather than conform to conventional development aid projects of either a “research” or an “interventionist” nature, it combines both approaches in a research-action program, which has more in common with a business development approach than a formal social science one. An important conclusion is that the work (and apparent success) of the project is consistent with an understanding of development that emphasizes the importance of innovation systems.

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.

Innovation for sustainable agricultural intensification (SAI) is challenging. Changing agricultural systems at scale normally means working with partners at different levels to make changes in policies and social institutions, along with technical practices. This study extracts lessons for practitioners and investors in innovation in SAI, based on concrete examples, to guide future investment.