Modeling of tri-parameter contracts integrating cost, time and risk

Abstract

Delay is a crucial determinant to the success of a construction project as time has an impact on the financial returns and/or the social benefits for public projects. As cost contingencies are essential to mitigate the risk of unforeseen conditions, time contingencies are also as important. For decades, the low-bid system has been the most popular contracting method. Nevertheless, problems arise in the current complex construction industry as owners rely solely on cost, and the time parameter is usually not evaluated as part of the awarding criteria. Recently, the bi-parameter bidding system, A+B, introduced the time parameter to the awarding criteria; yet, risks will not cease to exist. Reducing the duration by compressing the schedule consumes the float of non-critical activities, which reduces the schedule flexibility of a project. Therefore, the likelihood of critical delays occurring increases which lowers the probability of finishing on time. A new tri-parameter system, A+B+R, is introduced and brought into the broader view. The key value of A+B+R system is that it remains within the framework of the competitive bidding system, while controlling the risk resulting from float loss. The A+B+R system does not only take the time parameter into consideration, but it also incorporates the risk parameter into the awarding criteria to diminish the risk of finishing late. Henceforth, project managers can exercise new tradeoffs between cost, time and risk; ultimately, improving the chances of achieving the project objectives. Two different models are proposed for the A+B+R system suggesting a three-way tradeoff, which defines a new optimum project duration. The first model considers stochastic scheduling to quantify the float loss impact at the project level while the second model considers a deterministic approach through the calculation of float loss cost for each activity individually to determine the risk parameter. In this study, application examples are implemented and discussed for both models. Results show that adding the risk parameter in the evaluation criteria changed the ranking of the bidders, which validates the significance of the system. The evaluated risk parameter weighed 3-5% of the original bid price which checks with the typical projects' contingency.