This paper introduces a new approach of applying feasibility risk assessment within transport project infrastructure appraisal. The procedure is based upon quantitative risk analysis and Monte Carlo simulation in combination with conventional cost-benefit analysis converting deterministic benefit-cost ratios (BCRs) into stochastic interval results. Recent research has proven that particularly input based impacts such as construction cost and demand forecasts (travel time savings) often are respectively underestimated and overestimated creating so-called Optimism Bias. Decision-makers and stakeholders are, hereby, often basing their decisions on wrongful material. The presented approach to transport infrastructure appraisal is to include uncertainties and risks in the evaluation. Correspondingly, the handling of uncertainties and risk within transport project assessment are often made up by sensitivity tests producing deterministically based output values. Research has proven that traditional sensitivity analysis seldomnly captures the total variability especially as concerns the costs and demands estimated in the pre-stage of the evaluation. Therefore, this paper introduces an approach to decision support based upon so-called reference class forecasting using historical information from similar past projects. The scheme is made evident through a brand new database sample (UPD: the UNITE Project Database) which contains almost 200 specific European transport infrastructure projects. Hence, the approach will be tested and further explored upon a fixed case example depicting a new fixed link between Elsinore (Denmark) and Helsingborg (Sweden) revealing a severe decrease in economical return including relevant UPD information. Finally, a conclusion and perspective of the further work will be discussed.
Procedia - Social and Behavioral Sciences, 2013, Vol 74
Quantiative risk analysis; Monte Carlo simulation; decision support systems; transport infrastruture appraisal; cost- benefit analysis; optimism bias
Main Research Area:
International Project Management Association, 2013