Project Cost, Benefit and Risk Analysis using Bayesian Networks Anthony Constantinou 0 2 Norman Fenton 0 2 Martin Neil 0 2 Eike Luedeling 0 3 Keith Shepherd 0 3 Barbaros Yet Department of Industrial Engineering, Hacettepe University , Turkey School of Electronic Engineering and Computer Science, Queen Mary University of London , UK World Agroforestry Centre , Kenya

Uncertainty and risks are common elements of all major projects. Yet such uncertainty is rarely effectively calculated when analysing project costs and benefits. This paper presents a Bayesian network (BN) modelling framework to calculate the costs, benefits, and return on investment of a project over a specified time period, allowing for changing circumstances and trade-offs. The framework uses hybrid and dynamic BNs containing both discrete and continuous variables over multiple time stages. The BN calculates costs and benefits based on multiple causal factors including the effects of individual risk factors, budget deficits, and time value discounting. The method is illustrated using a case study of an agricultural development project.

 Project Management Project Risk Analysis Bayesian Networks -

This paper is published as an abstract only.