2009
DOI: 10.1080/15578770902952181
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Contingency Estimation for Construction Projects Through Risk Analysis

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 sough… Show more

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Cited by 25 publications
(21 citation statements)
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“…Peleskei et al (2015) say that German authors Girmscheid and Busch (2007) recommend the Monte Carlo simulation tool for quantifying risk. In using the Monte Carlo simulation tool each risk has a minimum, maximum, and the most reliable outcome (Panthi et al, 2009). Below are some examples of this approach in construction:…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…Peleskei et al (2015) say that German authors Girmscheid and Busch (2007) recommend the Monte Carlo simulation tool for quantifying risk. In using the Monte Carlo simulation tool each risk has a minimum, maximum, and the most reliable outcome (Panthi et al, 2009). Below are some examples of this approach in construction:…”
Section: Methodsmentioning
confidence: 99%
“…• Panthi et al, (2009) study combined Monte Carlo with Analytical Hierarchy Process (AHP) to combine the risk distributions of various Bill of quantities items in hydropower construction projects. This resulted in a risk adjusted cost from which the contingency was determined.…”
Section: Methodsmentioning
confidence: 99%
“…Many studies seek to estimate contingency in construction. Panthi et al [40] suggested a contingency estimation method through the relation between project risk and bill of quantity (BOQ) items. Elbarkouky et al [41] developed a contingency estimate model based on project risk with fuzzy arithmetic analysis.…”
Section: Relation Between Contingency and Returnmentioning
confidence: 99%
“…Construction is one of the most risky, difficult and dynamic industries (Hwang et al, 2017) as, due to its financial intensity, complex procedures, long project durations, risky environment and partner relationships, this industry is prone to a variety of risks (Panthi et al, 2009). There are also vast variations in the risks that exist in in construction industries in different countries and cultures (Al-Yahya, 2009;Assaf & Al-Hejji, 2006;Deloitte, 2016;El-Sayegh, 2008;Odongo et al, 2012;Randeree and Chaudhry, 2012).…”
Section: Introductionmentioning
confidence: 99%