This paper details the analytical framework used for developing a nested understanding of systemic innovation capacity in an AIS. The paper then introduces the two case studies, along with the data and methods of analysis, followed by a presentation of the results as timelines of configurations of capabilities at different levels of the AIS.
Agriculture Innovation System (AIS) thinking and approaches are largely perceived as a sine-qua-non for the design and implementation of effective and sustainable agriculture development programmes. AIS has gained popularity in the agriculture innovation literature and has been embedded in policy documents of agriculture sector institutions in many countries. However, there is much less evidence of AIS thinking influencing the behaviours of research and extension institutions and staff ‘on the ground’.
Although agricultural innovation systems (AIS) have recently received considerable attention in academic and development circles, links between an AIS's regional specifications and structural-functional analysis have been neglected. This paper aims to understand how regional and structural dimensions determine systemic problems and blocking mechanisms that, in turn, hinder a regional AIS's function.
The agricultural innovation systems approach emphasizes the collective nature of innovation and stresses that innovation is a co-evolutionary process, resulting from alignment of technical, social, institutional and organizational dimensions. These insights are increasingly informing interventions that focus on setting up multi-stakeholder initiatives, such as innovation platforms and networks, as mechanisms for enhancing agricultural innovation, particularly in sub-Saharan Africa.
The World Bank has a long relationship with Uruguay's agricultural sector, expanding over a period of more than 60 years in which several projects and various analytical and advisory assistance initiatives have been implemented.
The Agriculture Technology Program for Turkmenistan (AgTech) takes a comprehensive approach to agricultural development in Turkmenistan by implementing high-impact activities in the livestock and greenhouse horticulture sectors to achieve the two objectives: improve genetics, education and organizations for private livestock producers; introduce successful agribusiness practices.
The Agriculture Technology Program for Turkmenistan (AgTech) takes a comprehensive approach to agricultural development in Turkmenistan by implementing high-impact activities in the livestock and greenhouse horticulture sectors to achieve the two objectives: improve genetics, education and organizations for private livestock producers; introduce successful agribusiness practices.
The Agriculture Technology Program for Turkmenistan (AgTech) takes a comprehensive approach to agricultural development in Turkmenistan by implementing high-impact activities in the livestock and greenhouse horticulture sectors to achieve the two objectives: improve genetics, education and organizations for private livestock producers; introduce successful agribusiness practices.
The recent proliferation of mobile phones in rural Africa has also led to increased interest in mobile financial services (MFS), such as mobile money and mobile banking. Such services are often portrayed as promising tools to improve agricultural finance, especially among smallholders who are typically underserved by traditional banks. However, empirical evidence on the actual use of MFS for agricultural activities is thin. Here, we use nationally representative data from Kenya to analyze the use of mobile payments, mobile savings, and mobile credit among the farming population.
In this paper, is introduced an integrated supply chain planning tool for fresh vegetables that takes into consideration the characteristics and resources of three specific states in Mexico, to make recommendations in terms of the crops to be planted, the timing of planting and harvesting, and what markets to target such that the farmers’ profits are maximized. Also relevant is the selection of the appropriate agriculture technology level (e.g. open field, shade structures, or greenhouse) within each region analyzed.