Quantitative model for determining incentive/disincentive amounts through schedule simulations

One groundbreaking way of expediting any construction is to offer contractors a monetary incentive. To be effective, the incentive amount should be larger than the contractor´s additional cost (CAC) for expediting construction time. Yet, estimating the CAC poses a major challenge because contractors are reluctant to disclose their profit information. This study introduces a quantitative model that estimates realistic CACs through schedule simulations on four different resource usage levels. An innovative and reliable tool called Construction Analysis for Pavement Rehabilitation Strategies (CA4PRS) was used for the simulation. Using CA4PRS, a set of contractors´ time-cost tradeoff data was created and a linear regression analysis was performed to predict the CAC growth rate and to analyze how this interacts with the agency´s specified schedule goal. The robustness of the proposed model was also validated through a case study. This model can assist decision-makers to make better decisions when estimating optimal incentive amounts.