This editorial paper brings together different streams of research providing novel perspectives on co-design and co-innovation in agriculture, including methods, tools and organizations.
More and more, development organizations are under pressure to demonstrate that their programs result in significant and lasting changes in the well-being of their intended beneficiaries. However, such "impacts" are often the product of a confluence of events for which no single agency or group of agencies can realistically claim full credit. As a result, assessing development impacts is problematic, yet many organizations continue to struggle to measure results far beyond the reach of their programs
he agricultural sector is under increasing pressure to bridge a growing concern for hunger and economic deprivation. At the centre of discussion is increase in agricultural productivity at a scale increasingly complex. This complexity challenges the capacity of both extension workers, farmers, farming systems and even the environment. This means that what matters for agricultural development and achieving the above situation is the capability of people to be effective and productive economic agents. It is here that capacity building comes in.
Climate change and climate variability are creating negative impacts to agriculture. It affects both food security and crop and livestock production. In the process, it affects the livelihood of communities. Climate-smart agriculture is seen as an alternative to mitigate the challenges of climate change. Literature studies were obtained from journal articles on capacity development. The problem investigated is that climate-smart agriculture (CSA) is a recent concept which needs to be understood with climate change, and the extension advisors do not have requisite skills.
Agricultural innovation is an essential component in achieving the SDG and accelerating the transition to more sustainable and resilient farming systems across the world. Innovations generally emerge from collective intelligence and action, which requires effective agricultural innovation systems (AIS). An AIS perspective has been widely adopted, but the analysis of AIS, especially at country level, remains a challenge. The need for and potential of a diagnostic tool for AIS analysis is currently receiving attention in the global agricultural policy debate.
The usual linear top-down approach of the innovation process has been transformed into an 'ecological vision' in which regions make up the appropriate scale for the elaboration of agricultural innovation systems (AIS). Interfaces such as institutional arrangements have been created in industrial countries. However, there is still a lack of interaction among parties involved in innovation for the agricultural sector, especially in the outermost regions and in developing countries.
Agricultural Innovation Systems (AIS) approach, arise as tool for better understanding dynamics and complexity of agricultural innovation. The objective of this article is present a framework for AIS capability development, taking as a scientific reference, emerging economy countries experiences. A multi-dimensional methodology of literature review and content analysis is implemented, supported in bibliometric and data mining techniques.
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).
Encouraging the adoption and diffusion of low-carbon agricultural technology innovation is an important measure to cope with climate change, reduce environmental pollution, and achieve sustainable agricultural development. Based on evolutionary game theory, this paper establishes a game model among agricultural enterprises, government, and farmers and analyzes the dynamic evolutionary process and evolutionary stable strategies of the major stakeholders.
Agricultural innovation happens at different scales and through different streams. In the absence of a common global research agenda, decisions on which innovations are brought to existence, and through which methods, are taken with insufficient view on how innovation affects social relations, the environment, and future food production. Mostly, innovations are considered from the standpoint of economic efficiency, particularly in relationship to creating jobs for technology-exporting countries.