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 paper addresses four questions: · What lessons can be drawn from the "rise and decline" of NARS in Africa? · What can African research managers learn from some of the successful reforms of NARS in Asia and Latin America over the past 10 to 15 years? · What are the major challenges facing the NARS in the ASARECA region in the coming 10-20 years? · What are the critical reforms and the incentives needed to develop pluralistic, accountable, productive and financially self-sustaining NARS in AFRICA?
Climate change is threatening development gains and intensifying global inequities—putting peace and important gains in human well-being at risk.
Providing farmers with essential agricultural information and training in the era of COVID-19 has been a challenge that has prompted a renewed interest in digital extension services. There is a distinct gender gap, however, between men’s and women’s access to, use of, and ability to benefit from information and communication technologies (ICTs).
ICARDA scientists along with CGIAR LIVESTOCK developed a cloud-based genetic database platform to boost breed improvement programs in community-based livestock breeding programs in Ethiopia.
Le Programme d’appui au développement des filières agricoles (PADFA) a pour objectif d’améliorer les activités après-récolte (conditionnement, stockage, transformation et commercialisation) dans les filières du riz, des légumes et de la mangue en Côte d'Ivoire. Cette brochure réunit les témoignages de petits producteurs ayant participé au programme et dont les cultyures étaient affectés par les effets des changements climatiques et les insectes.
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.
Climate smart agriculture (CSA) technologies are innovations meant to reduce the risks in agricultural production among smallholder farmers. Among the factors that influence farmer adoption of agricultural technologies are farmers' risk attitudes and household livelihood diversification. This study, focused on determining how farmers' risk attitudes and household livelihood diversification influenced the adoption of CSA technologies in the Nyando basin. The study utilized primary data from 122 households from two administrative regions of Kisumu and Kericho counties in Kenya.
The spatial and temporal variability of soil properties (fluid composition, structure, and water content) and hydrogeological properties employed for sustainable precision agriculture can be obtained from geoelectrical resistivity methods. For sustainable precision agricultural practices, site-specific information is paramount, especially during the planting season.
The determination of bunch features that are relevant for bunch weight estimation is an important step in automatic vineyard yield estimation using image analysis. The conversion of 2D image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology varies greatly. This paper aims to explore the relationships between bunch weight and bunch features obtained from image analysis considering a multicultivar approach.