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Badger, W, Sullivan, K, Wiezel, A and Bopp, P H (2009) Profiling the leadership of project managers. International Journal of Construction Education and Research, 5(02), 121-46.
Duncan, K, Philips, P and Prus, M (2009) The effects of prevailing wage regulations on construction efficiency in British Columbia. International Journal of Construction Education and Research, 5(02), 63-78.
Kramer, S W and Dillard, C (2009) Why do American construction professionals choose to work abroad on US embassy projects?. International Journal of Construction Education and Research, 5(02), 95-107.
Panthi, K, Ahmed, S M and Ogunlana, S O (2009) Contingency estimation for construction projects through risk analysis. International Journal of Construction Education and Research, 5(02), 79-94.
- Type: Journal Article
- Keywords: analytical hierarchy process; contingency; Monte Carlo simulation; risk allocation
- ISBN/ISSN: 1557-8771
- URL: https://doi.org/10.1080/15578770902952181
- Abstract:
Construction organizations are constantly seeking ways to avoid failure and contain risks early on in the project life-cycle. One such approach to handle risks is through the allocation of "suitable" contingency or reserve. However, when it comes to determining this suitable contingency fund, project personnel often face difficulty. In order to provide a logical basis upon which to allocate contingency to projects, a methodology that incorporates risk assessment is presented. Based on subjective judgment sought from the project personnel regarding the likelihood and severity of risks in their project, the degree of risk of the project is determined. Contingency funds are then allocated based on this quantified degree of risk. The developed methodology was applied to a hydropower project to check the adequacy of the contingency fund allocated. All the construction risks were identified for these projects. Their effects were quantified by determining the probability and severity using the Analytical Hierarchy Process (AHP). Ranging was also performed on Bill of Quantity items. An Activity/Risk factor matrix was developed, which was then used as an input to the Monte Carlo simulation to combine the risk distributions of various BOQ items. This resulted in a risk adjusted cost from which the contingency was determined.
Reposa, J H (2009) Comparison of USGBC LEED for homes and the NAHB national green building program. International Journal of Construction Education and Research, 5(02), 108-20.