This paper identifies market failures that limit agricultural R&D for Africa and other resource-poor environments, and proposes a way to complement existing institutions with cash prizes for the dissemination of successful new technologies adopted by low-income farmers. The proposed prize institution would use agronomic experiments and farm surveys to document the value of innovations after their initial diffusion, and offer payments in proportion to estimated social benefits in target regions.
This paper discusses the challenges and determinants of agro-operations and innovation initiatives in developing countries. With particular reference to the Caribbean region, available country statistics and data are analysed. A generic model of collaborative innovation for agriculture that stresses collaboration among the stakeholders (government, knowledge institutions, public and private firms and others) is described.
Rather than merely supporting R&D and strengthening innovation systems, the focus of innovation policy is currently shifting towards addressing societal challenges by transforming socio-economic systems. A particular trend within the emerging era of transformative innovation policy is the pursuit of challenge-based innovation missions, such as achieving a 50 % circular economy by 2030. By formulating clear and ambitious societal goals, policy makers are aiming to steer the directionality and adoption of innovation.
Individuals from a diverse range of backgrounds are increasingly engaging in research and development in the field of artificial intelligence (AI). The main activities, although still nascent, are coalescing around three core activities: innovation, policy, and capacity building. Within agriculture, which is the focus of this paper, AI is working with converging technologies, particularly data optimization, to add value along the entire agricultural value chain, including procurement, farm automation, and market access.
Establishing food security remains a global challenge; it is thus a specific objective of the United Nations Sustainable Development Goals for 2030. Successfully delivering productive and sustainable agricultural systems worldwide will form the foundations for overcoming this challenge. Smart agriculture is often perceived as one key enabler when considering the twin objectives of eliminating world hunger and undernourishment. The practical realization, deployment, and adoption of smart agricultural systems remain distant due to a confluence of technological, social, and economic factors.
The agricultural innovation system can be strengthened by increasing the learning capacity of research and field organisations. Participatory methods were developed to study three dimensions of the capacity of such organisations in Nicaragua to access and analyse information, highly correlated to learning capacity – the individual routines of their professionals, the formal procedures of the organisation and the organisation's use of collaborative projects to strengthen core operations.
Public–private partnerships that aim at the development of innovations have gained increasing attention from governments, public research and private companies, because they enable partners to draw from complementary resources and profit from synergy and joint learning. This article develops arguments for when partnerships should form and compares them with experiences in real partnership cases in Latin America.
Empirical studies on agricultural technology adoption generally divide a population into adopters and nonadopters, and analyse the reasons for adoption or nonadoption at a point in time. In reality, technology adoption is not a one-off static decision, rather it involves a dynamic process in which information gathering, learning and experience play pivotal roles, particularly in the early stage of adoption. A conceptual framework for an adoption pathway is suggested in which farmers move from learning to adoption, to continuous or discontinuous use over time.
This study describes the evolving context and organisational linkages in the agricultural innovation system of Azerbaijan and suggests ways to promote effective organisational ties for the development, distribution and use of new or improved information and knowledge related to agriculture. Graph-theoretic principles and concepts are employed to assess the existing organisational linkages vital for agricultural innovations.
This study introduces a framework for managing information flow in innovation systems. An organisation's capacity to receive information, to share it with others and to learn from it is assumed to be the key factor that shapes the flow patterns and, hence, the performance of the innovation system concerned. The framework is applied to characterise the information structure underlying the agricultural innovation system of Azerbaijan and to develop an information strategy for the system to accelerate the information flow.