Lesotho's agricultural system faces a growing number of climate-related vulnerabilities with droughts, floods, pests, and extreme temperatures occurring more frequently. In response, the Government of Lesotho is collaborating with the World Bank to integrate climate change into the country’s agriculture policy agenda through the Lesotho Climate-Smart Agriculture Investment Plan (CSAIP).
Ce document de directives pratiques a été préparé dans le cadre du projet Développement des capacités pour les systèmes d'innovation agricole (CDAIS), un partenariat mondial (Agrinatura, FAO et huit pays pilotes) qui vise à renforcer la capacité des pays et des principales parties prenantes à innover dans des systèmes agricoles complexes, ce qui permet l'amélioration des moyens de subsistance en milieu rural. Le CDAIS utilise une approche de cycle d'apprentissage continu pour soutenir les systèmes nationaux d'innovation agricole dans huit pays d'Afrique, d'Asie et d'Amérique centrale.
The term ‘systemic innovation’ is increasing in use. However, there is no consensus on its meaning: four different ways of using the term can be identified in the literature. Most people simply define it as a type of innovation where value can only be derived when the innovation is synergistically integrated with other complementary innovations, going beyond the boundaries of a single organization. Therefore, the term ‘systemic’ refers to the existence of a co-ordinated innovation system.
Innovation intermediaries are individuals and organisations that enhance connectivity amongst constituencies of national, sectoral, and regional systems of innovation, thereby facilitating knowledge spillover. This paper articulates the whole picture of Indonesia's agricultural innovation system, with a special focus on how different innovation intermediaries play different roles in technology transfer and knowledge dissemination.
Synergy among the various components of national agricultural innovation systems (AISs) promotes agricultural development. This paper investigated the innovation synergy among the various innovation elements of national AISs. First, the authors developed a synergy analysis model consisting of three innovation variables (innovation allocation, innovation output, and innovation potentiality) and one control variable (government policy supports).
Transforming a centrally planned system of agricultural production to one where individual farmers are accorded choice in crop mix and land use management practices is much more than a structural change. Embedded within this process is a fundamental shift in how knowledge is generated, disseminated and adopted. Upon dissolution of the Soviet Union, one immediate priority was the privatization of state farms and thereby relaxation of policies for collective production.
The transition to a market for agricultural research and knowledge-intensive services presents various challenges for actors in the agricultural knowledge infrastructure, on both the demand side (end users of innovations such as farmers, and the government) and the supply side (providers of research and knowledge-intensive services). New organizational arrangements try to bring together supply and demand in the agricultural knowledge infrastructure. This thesis is about such new organizational arrangements
This paper applies the framework for pro-poor analysis to welfare changes from a CGE-microsimulation model to analyze what are the better or worse models for agriculture modernization, and to estimate the contribution of growth and redistribution to changes in poverty in DRC. The findings indicate that labor-using technological change generates absolute and relative pro-poor effects whereas capital-using technological change leads to immiserizing growth.
The efforts to adapt to climate change in developing countries are in their infancy, and hopefully CSA will be a major contributor to these efforts. But CSA itself is evolving, and there is a growing need to refine and adapt it to the changing realities. This section of the book focus on the implications of the empirical findings for devising effective strategies and policies to support resilience and the implications for agriculture and climate change policy at national, regional and international levels.
A foresight hub within the Directorate General Research and Innovation (DG RTD) of the European Commission will support the decision-making procedures of the EU Horizon 2020 research, technology, and innovation programme. Foresight in particular is seen as an instrument defining research priorities for European society’s needs in support of the ‘grand societal challenges’.