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Uptake pathways: the potential of Bayesian belief networks to assist the management, monitoring and evaluation of development-orientated research

Uptake pathways: the potential of Bayesian belief networks to assist the management, monitoring and evaluation of development-orientated research The effectiveness of development assistance has come under renewed scrutiny in recent years. In an era of growing economic liberalisation, research organisations are increasingly being asked to account for the use of public funds by demonstrating achievements. However, in the natural resources (NR) research field, conventional economic assessment techniques have focused on quantifying the impact achieved rather understanding the process that delivered it. As a result, they provide limited guidance for planners and researchers charged with selecting and implementing future research. In response, “pathways” or logic models have attracted increased interest in recent years as a remedy to this shortcoming. However, as commonly applied these suffer from two key limitations in their ability to incorporate risk and assess variance from plan. The paper reports the results of a case study that used a Bayesian belief network approach to address these limitations and outlines its potential value as a tool to assist the planning, monitoring and evaluation of development-orientated research. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Agricultural Systems Elsevier
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