This event launches a new phase of the JP RWEE that will even further enhance its holistic approach to advancing rural women’s economic empowerment by integrating a climate resilience lens to tackle deep rooted social norms which limit women’s participation and leadership in rural communities including through applying gender transformative approaches.
Katalyst has identified that Bangladesh’s craft sector possesses a vast potential to contribute to women’s economic empowerment (WEE). . The ‘Empowering Women in Craft’ publication shows how an innovative partnership between Katalyst and BRAC-Aarong provides new perspectives for independent producers and women artisans in the craft industry.
Social learning processes can be the basis of a method of agricultural innovation that involves expert and empirical knowledge. In this sense, the objective of this study was to determine the effectiveness and sustainability of an innovation process, understood as social learning, in a group of small farmers in the southern highlands of Peru. Innovative proposals and its permanence three years after the process finished were evaluated. It was observed that innovation processes generated are maintained over time; however, new innovations are not subsequently generated
The Australian story of farmer innovation in Conservation Agriculture reveals a complex interplay of policy, economics, science, and farming. Farmer experimentation with Conservation Agriculture began in the 1960's and has continued to this day where around 80%-90% of Australia's 23.5 million hectares of winter crops are now grown using Conservation Agriculture principles. This remarkable achievement is the result of both sustained investment in agricultural research and development and farmer innovation.
Following the food price crisis in 2008, African governments implemented policies aiming at crowding in investment in rice value chain upgrading to help domestic rice compete with imports. This study assess the state of rice value chain upgrading in West Africa by reviewing evidence on rice millers’ investment in semi-industrial and industrial milling technologies, contract farming and vertical integration during the post-crisis period 2009–2019. We find that upgrading is more dynamic in countries with high rice production and import bills and limited comparative advantage in demand.
This paper discusses ICT for Open Innovation (OI) from a capabilities perspective. The study distinguish two types of capabilities for OI: strategic, which need to be developed so that the organization can take advantage of an OI strategy proactively, and operational for the efficient implementation of OI processes.
This article conceptualizes the diffusion of user innovations from a service ecosystem perspective. With the focus on sustainable innovations, the service ecosystem is evaluated, along with other systemic innovation concepts, as a possible theoretical basis for explaining the first adoption and diffusion of user innovations.
Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions.
There is a broad consensus that farmers are not simply recipients of promoted techniques: rather, they are also an important source of agricultural innovations. They invent farm tools and equipment, develop new crop varieties, and add value to externally promoted technologies. When scouting, documenting and promoting such farmer-generated innovations, the thorny issue of intellectual property rights (IPRs) often emerges.
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.