The paper explores the strength of social networks in the agricultural innovation systems (AISs) in Ghana and the effect of AISs on adoption of improved farm technology. The paper uses social network analysis (SNA) tools to identify, map and analyze the AISs and the two-stage Heckman selection model. Combining qualitative and quantitative methods allows testing the differential effects of social networks on technology adoption in the Ghananian Plantain Sector
This sourcebook contributes to identifying, designing, and implementing the investments, approaches, and complementary interventions that appear most likely to strengthen Agricultural innovation systems (AIS) and to promote agricultural innovation and equitable growth. It emphasizes the lessons learned, benefits and impacts, implementation issues, and prospects for replicating or expanding successful practices. The information in this sourcebook derives from approaches that have been tested at different scales in different contexts.
Given the diversity and context-specificity of innovation systems approaches, in March 2007 the World Bank organized a workshop in which about 80 experts (representing donor agencies, development and related agencies, academia, and the World Bank) took stock of recent experiences with innovation systems in agriculture and reconsidered strategies for their future development. This paper summarizes the workshop findings and uses them to develop and discuss key issues in applying the innovation systems concept. The workshop’s recommendations, including next steps for the wider
This book aims to identify the characteristics of innovative farmers and suggests policy strategies to encourage agricultural innovations. The analysis shows that agricultural innovations are taking place in Turkey and various public and private stakeholders contribute to the development and adoption of innovation in agriculture. Agricultural enterprises and cooperatives, clusters of innovation, non-governmental organizations, research institutes, government, and international institutions play an important part in the collaborative effort to create and disseminate innovation.
This brief explores the definition of Agricultural Knowledge and Information System (AKIS) and the inventory of AKIS in Europe.
This paper offers a perspective on the Agricultural Knowledge and Innovation System. The first chapter gives an introduction to the subject and explains the role of SCAR and of the Strategic Working Group AKIS. The second chapter investigates the AKIS and their role in innovation, including the policy context of the European Innovation Partnership “Agricultural productivity and sustainability”. Chapter 3 discusses the relation in a globalised world between Agricultural Research (AR) and Agricultural Research for Development (ARD).
Multi-actors networks are increasingly used by farmers to link between them and to be interactively connected with other partners, such as advisory organizations, local governments, universities, and non-farm organizations. Given the importance assigned to the agricultural innovation by EU resorting to the networking between the research chain actors and the farmers, a strong focus on enhancing the creation of learning and innovation networks is expected.
Poor farmers seldom benefit from new agricultural technologies. In response, research and extension approaches based on agricultural innovation systems are popular. Often agricultural research organisations are the network brokers, facilitating the emergence of the innovation system. Based on an analysis of the Sustainable Modernization of Traditional Agriculture (MasAgro) initiative in Mexico, this viewpoint suggests that such organisations are more often suitable network brokers when the objective is the development and scaling out of a technology by itself.
Kenya has emerged as a frontrunner in information and communication technologies (ICT) in Sub-Saharan Africa. The government has been actively supporting the ICT sector as one of the key drivers of economic growth. In addition to large international firms that are setting up offices in Nairobi, such as Nokia, IBM and Google, local start-ups have also been expanding rapidly.
This research aimed to figure out the attitude and readiness of agriculture extension officers in using the Information and Communication Technology. Data collection was done through a survey with total sample 60 respondents. Data gained were primary data from questionnaire filling by respondents who were all extension officers in Food Security and Extension Implementation Agency. Data analyses used in this research were reliability and validity analysis, Fishbein’s Attitude Model, and regression analysis which continued with F and t test.