While intrapreneurship and scaling are key themes in the International Business (IB) discussion, our research is the first to show how these concepts manifest in the context of the United Nations and how learnings from IB may be transferred. The United Nations (UN) organizations are tasked with solving the world’s pressing and difficult problems. These organizations are major players in international governance and are characterized by bureaucratic, globally dispersed and politically driven structures, but are hardly ever considered in IB research.
This training manual, which is based on a methodology developed by FAO’s Research and Extension Unit (OINR), presents a training course on assessing AIS consisting of eight modules.
Green Extension is an umbrella term used to describe rural advisory services which support the scaling up of sustainable agriculture. This encompasses a range of methods to promote various types of content. What these approaches have in common is a process of socio-ecological learning, i.e., supporting farmers to analyse local problems and opportunities, and test alternative practices under local conditions.
How do innovations move from the edges to the core of what an organization does? For maximum impact, innovations must cease to be innovative and become institutionalized and normalized.
Mission-Oriented Innovation Policies (MOIPs) are one approach that can advance the required transformations. As our colleague Philippe Larrue noted in a 2021 paper, MOIPs are "a co-ordinated package of policy and regulatory measures tailored specifically to mobilise science, technology and innovation in order to address well-defined objectives related to a societal challenge, in a defined timeframe".
Droughts are causing severe damages to tropical countries worldwide. Although water abundant, their resilience to water shortages during dry periods is often low. As there is little knowledge about tropical drought characteristics, reliable methodologies to evaluate drought risk in data scarce tropical regions are needed.
Digitization in agriculture is rapidly advancing further on. New technologies and solutions were developed and get invented which ease farmers’ daily life, help them and their partners to gain knowledge about farming processes and environmental interrelations. This knowledge leads to better decisions and contributes to increased farm productivity, resource efficiency, and environmental health. Along with numerous advantages, some negative aspects and dependencies risk seamless workflow of agricultural production.
This article extends social science research on big data and data platforms through a focus on agriculture, which has received relatively less attention than other sectors like health. In this paper, I use a responsible innovation framework to move attention to the social and ethical dimensions of big data “upstream,” to decision-making in the very selection of agricultural data and the building of its infrastructures.
Cotton, a major crop worldwide, is harvested in mechanized production systems once at the end of the growing season. To facilitate harvest and maximize fiber quality, the plants are typically defoliated when about 60% of the cotton bolls are open. Due to non-uniform maturation, the bolls that have opened early expose their fiber to weather until harvest, commonly for weeks, degrading fiber quality. Furthermore, high capacity harvesting machines are heavy, potentially compacting the soil that in turn reduces hydraulic conductivity in the wheel tracks and reducing yield.
Accurate and operational indicators of the start of growing season (SOS) are critical for crop modeling, famine early warning, and agricultural management in the developing world. Erroneous SOS estimates–late, or early, relative to actual planting dates–can lead to inaccurate crop production and food-availability forecasts. Adapting rainfed agriculture to climate change requires improved harmonization of planting with the onset of rains, and the rising ubiquity of mobile phones in east Africa enables real-time monitoring of this important agricultural decision.