Although Colombia has the potential to be a cocoa producer for fine flavor and high value markets, it is not greatly recognized as such. In spite of the government’s interest to position the country as a major specialty cocoa producer, no strategic actions have been taken to develop and strengthen this aspect of the value chain.
This practitioner’s guide, a companion volume to The Innovation Paradox picks up where the previous report left off. It aims to help policy makers in developing countries better formulate innovation policies. It does so by providing a rigorous typology of innovation policy instruments, including evidence of impact—and more importantly, the critical conditions in terms of institutional capabilities to successfully implement these policy instruments in developing countries.
The goal of this paper is to access the state, specify trends, compare with other EU states, and identify intervention needs of Agricultural Knowledge and Innovation System (AKIS) in Bulgaria, and assist policy formation for the next programing period. Modern scientific approaches of SWOT, Strategic Orientation, Gap Analysis, Comparative Institutional Analysis, etc. are used to identify actors and relations, trends in development, assess strengths, weaknesses, opportunities and threats, formulate adequate strategy, and specify overall and public intervention needs of AKIS in the country.
The latest comprehensive research agenda in the Journal of Agricultural Education and Extension was published in 2012 (Faure, Desjeux, and Gasselin 2012), and since then there have been quite some developments in terms of biophysical, ecological, climatological, social, political and economic trends that impact farming and the transformation of agriculture and food systems at large as well as new potentially disruptive technologies.
ICT-driven digital tools to support smallholder farmers are arguably inevitable for agricultural development, and they are gradually evolving with promising outlook. Yet, the development and delivery of these tools to target users are often fraught with non-trivial, and sometimes unanticipated, contextual realities that can make or mar their adoption and sustainability. This article unfolds the experiential learnings from a digital innovation project focusing on surveillance and control of a major banana disease in East Africa which is being piloted in Rwanda.
The building of sustainable innovation capabilities in Africa requires an innovation system capable of producing, disseminating and using new knowledge. This paper assesses the process of constructing the National Innovation System (NIS) in Rwanda. It is posited that consensus on and acceptance of the concept of NIS among stakeholders is crucial in the early process of constructing an efficient and dynamic innovation system. Primary empirical data are presented for the case of Rwanda and analyzed in a regional context.
This paper calls for a better integration of place-based, evidence-based and inclusive dimensions in the implementation of the Science, Technology and Innovation (STI) plans and industrial policies in sub-Saharan Africa. To this end, the analysis contrasts with and takes inspiration from the recent and ongoing international experiences in the elaboration of Innovation Strategies for Smart Specialisation (S3).
Technology and innovation are important in addressing complex problems in the agricultural sector in many developing communities. However, ways and mechanisms to integrate them in the agricultural sector are still a challenge due to the lack of clear pathways and trajectories. Value chains are seen as a strong policy instrument to increase profitability in the agricultural sector; there is also debate around whether value chains can be a potential option to organize technology and innovation trajectories in agriculture.
A central concern about achieving global food security is reconfiguring agri-food systems towards sustainability. However, historically-informed trajectories of agri-food system development remain resistant to a change in direction. Through a systematic literature review, the authors identify three research domains exploring this phenomenon and six explanations of resistance: embedded nature of technologies, misaligned institutional settings, individual attitudes, political economy factors, infrastructural rigidities, research and innovation priorities.
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.