This Economic and Sector Work paper, “Enhancing Agricultural Innovation: How to Go Beyond the Strengthening of Research Systems,” was initiated as a result of the international workshop, “Development of Research Systems to Support the Changing Agricultural Sector,” organized by the Agriculture and Rural Development Department of the World Bank in June 2004 in Washington, DC.
This guide is mainly for researchers already involved in natural resource management (NRM). It assumes some familiarity with the often complex and chaotic reality of NRM projects, and tries to provide a systematic treatment of all the issues that may need to be considered. While many issues are considered in the guide, only a subset of them have to be dealt with in any specific NRM project. This booklet will also be of interest to implementers of NRM projects, as many of the elements and strategies are common to research and implementation.
The provision of basic market information is a service that aims to increase the efficiency of agricultural markets and contribute towards overcoming basic issues of market failure based on asymmetrical access to information. However, debate on the need for long-term support to a market information system (MIS) continues. A quantitative and qualitative survey was undertaken to provide a measure of accessibility, usefulness and utility of the current MIS, and to access how this type of service may be financed and improved in the future.
Innovations generally arise out of a network of actors and relationships and network structure determines how effective networks are at fostering innovation. This paper (Part II) presents work to develop a network diagnosis tool for stakeholders involved in agricultural supply chains in Bolivia. The prototype method used is based on social network analysis methodology. This paper concludes with a final section to identify lessons learnt and makes recommendations for future research.
Este libro, originalmente un documento de trabajo económico y sectorial del Banco Mundial, se inició como resultado de un taller internacional,“Desarrollo de sistemas de investigación para el apoyo a un cambiante sector agrícola”, que fue organizado por el Departamento de Agricultura y Desarrollo Rural del Banco Mundial en junio de 2004 en Washington, DC.
Assessing or understanding the agriculture innovation system (AIS) is an essential step to better understand the needs, new skills and functions needed by the actors and the system. To accelerate the uptake of innovation and progress towards eradicating poverty, there is an urgent need for well-coordinated, demand-driven, and market-oriented information, knowledge, technologies and services.
Agricultural Internet of Things (IoT) has brought new changes to agricultural production. It not only increases agricultural output but can also effectively improve the quality of agricultural products, reduce labor costs, increase farmers' income, and truly realize agricultural modernization and intelligence. This paper systematically summarizes the research status of agricultural IoT. Firstly, the current situation of agricultural IoT is illustrated and its system architecture is summarized. Then, the five key technologies of agricultural IoT are discussed in detail.
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.