Construction cost analysis under uncertainty with correlated cost risk analysis model

Abstract

Cost estimation is an important task in construction projects. Since various risk‐factors affect the construction costs, the actual costs generally deviate from the estimated costs in a favourable or an adverse direction. Therefore, not only estimation of the costs but also an analysis of the uncertainty of the estimated costs is required. This requirement gains more importance in projects constrained by money as the main driver. The traditional cost estimation, i.e. predicting the construction costs and simply calculating the total, is deterministic and insufficient. This approach neglects the uncertainty and the correlation effects. A new simulation‐based model—the correlated cost risk analysis model (CCRAM)—is proposed to analyse the construction costs under uncertainty when the costs and risk‐factors are correlated. CCRAM captures the correlation between the costs and risk‐factors indirectly and qualitatively. The efficiency and effectiveness of the model is evaluated through an application of CCRAM and Monte Carlo simulation (MCS) based method using the same hypothetical data. The findings show that CCRAM operates well and produces more consistent results compatible with the theoretical expectancies.

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