Accounting for the inaccuracies in demand forecasts and construction cost estimations in transport project evaluation

Kim Bang Salling, Steen Leleur

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    For decades researchers have claimedthat particularly demand forecasts and construction cost estimations are assigned with/affected by a large degree of uncertainty. Massively, articles,research documents and reports agree that there exists a tendencytowards underestimating the costs and overestimating the demand for transport infrastructure projects. It is therefore claimed that ex-anteevaluations of trans- port-related projects are often based on inaccurate material, which ultimately can lead to severe socio- economic misperformance. This paper seeks to bridge the gap between the inaccuracies in demand and cost estimations and hence the evaluation of transport infrastructure projects. Currently, research within this area is scarce and scattered with no commonagreement on how to embed and operationalise the huge amount of empiricaldata that exist within the frame of Optimism Bias. Therefore, a full version of the UNITE-DSS model, which contains an integrated approach to socio-economic analysis, risk-based simulation and database information, will be presented. The procedure is based upon quantitative risk analysis and MonteCarlo simulation and conventionalcost-benefit analysis convertingdeterministic benefit-cost ratios (BCRs) into stochasticinterval results. A new data collection (2009–2013) forms the empirical basis for any risk simulation embeddedwithin the so-calledUP database (UNITE project database),revealing the inaccuracy of both construction costs and demandforecasts. Accordingly, the UNITE-DSS approachis therefore tested and further explored on a number of fixed case examples to investigate the performance and robustness of the traditional CBA results. Ultimately, a conclusion and perspectives of the further work will be set out.

    Original languageEnglish
    JournalTransport Policy
    Volume38
    Pages (from-to)8-18
    Number of pages11
    ISSN0967-070X
    DOIs
    Publication statusPublished - 3 Dec 2014

    Keywords

    • Transport appraisal
    • Decision support modelling
    • Monte Carlo simulation
    • Reference Class Forecasting
    • Cost overrun
    • Benefit shortfall

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