The increasing complexity of technology development and adoption is rapidly changing the effectiveness of scientific and technological policies. Complex technologies are developed and disseminated by networks of agents. The impact of these networks depends on the assets they command, their learning routines, the socio-economic environment in which they operate and their history.
Economic development and the successful transformation ofagriculture have been at the core of impressive change in countriessuch as China, India, Indonesia, Brazil, Mexico, and Argentina. This transformation has relied on substantial and effective investment inagriculture, and, in particular, building capacity in all aspects of agricultural change – from technology development and transfer through infrastructural development and the processing of agricultural commodities into consumer products.
Georeferenced data are a key factor in many decision-making systems. However, their interpretation is user and context dependent so that, for each situation, data analysts have to interpret them, a time-consuming task. One approach to alleviate this task, is the use of semantic annotations to store the produced information. Annotating data is however hard to perform and prone to errors, especially when executed manually. This difficulty increases with the amount of data to annotate.
One of the most important challenges for the researchers in the 21st Century is related to global heating and climate change that can have as consequence the intensification of natural hazards. Another problem of changes in the Earth's climate is its impact in the agriculture production. In this scenario, application of statistical models as well as development of new methods become very important to aid in the analyses of climate from ground-based stations and outputs of forecasting models. Additionally, remote sensing images have been used to improve the monitoring of crop yields.
This paper has been presented at the Fifth International Seminar on Dynamics of Farmer Managed Irrigation Systems: Socio-Institutional, Economic and Technical Context, Kathmandu, Nepal, 25-26 March 2010, organized by Farmer Managed Irrigation System Trust. International Water Management Institute, the then International Irrigation Management Institute (IWMI) began its activities in Nepal since 1986 with a Memorandum of Understanding with His Majesty's Government of Nepal, now the Government of Nepal.
This background note for the development of an AIS Investment Sourcebook provides a menu of tools and guidance to invest in agricultural innovation in different contexts. The content is drawn on tested good practice examples and innovative approaches with emphasis on lessons learned, benefits and impacts, implementation issues, and replicability
In this chapter the authors compute measures of total factor productivity (TFP) growth for developing countries and then contrast TFP growth with technological capital indexes. In developing these indexes, the authors incorporate schooling capital to yield two new indexes: Invention-Innovation Capital and Technology Mastery. They find that TFP performance is strongly related to technological capital and that technological capital is required for TFP and cost reduction growth.
This paper aims to map the experience of the RIU Asia projects and draw out the main innovation management tactics being observed while laying the groundwork for further research on this topic. It provides a framework to help analyse the sorts of innovation management tasks that are becoming important. This framework distinguishes four elements of innovation management: (i) Functions (ii) Actions (iii) Tools and (iv) Organisational Format.
This paper sets out to explore the nature of new organisational and institutional vehicles for managing innovation in order to put research into use for social gain. It has reviewed four classes of such vehicles found in South Asia.
This paper argues that impact assessment research has not made more of a difference because the measurement of the economic impact has poor diagnostic power. In particular it fails to provide research managers with critical institutional lessons concerning ways of improving research and innovation as a process. Paper's contention is that the linear input-output assumptions of economic assessment need to be complemented by an analytical framework that recognizes systems of reflexive, learning interactions and their location in, and relationship with, their institutional context.