Article ID: | iaor20104160 |
Volume: | 10 |
Issue: | 1 |
Start Page Number: | 91 |
End Page Number: | 99 |
Publication Date: | Jan 2010 |
Journal: | European Journal of Transport and Infrastructure Research |
Authors: | Banister David, Salling Kim Bang |
Keywords: | artificial intelligence: decision support |
This paper presents the final version of the CBA-DK (Cost Benefit Analysis, Denmark) decision support model for assessment of transport projects. The model makes use of conventional cost-benefit analysis resulting in aggregated single point estimates and quantitative risk analysis using Monte Carlo simulation resulting in interval results. Two special concerns in this paper is firstly the treatment of feasibility risk assessment adopted for evaluation of transport infrastructure projects, and secondly whether this can provide a more robust decision support model. This means moving away from a single point estimate to an interval result, and the determination of suitable probability distributions. Use is made of the reference class forecasting information, such as that developed in Optimism Bias for adjustments to investment decisions that relate to all modes of transport. The CBA-DK decision support model results in more informed decision support towards decision-makers and stakeholders in terms of accumulated descending graphs. The decision support method developed in this paper aims to provide assistance in the analysis and ultimately the choice of action, while accounting for the uncertainties surrounding any transport appraisal scheme.