Overruns in Transportation Infrastructure Projects
dc.contributor.author | Love, Peter | |
dc.contributor.author | Sing, Michael | |
dc.contributor.author | Wang, Xiangyu | |
dc.contributor.author | Irani, Z. | |
dc.contributor.author | Thwala, D. | |
dc.date.accessioned | 2017-01-30T11:04:42Z | |
dc.date.available | 2017-01-30T11:04:42Z | |
dc.date.created | 2015-04-16T05:48:10Z | |
dc.date.issued | 2014 | |
dc.identifier.citation | Love, P. and Sing, M. and Wang, X. and Irani, Z. and Thwala, D. 2014. Overruns in Transportation Infrastructure Projects. Structure and Infrastructure Engineering. 10 (2): pp. 141-159. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/8114 | |
dc.identifier.doi | 10.1080/15732479.2012.715173 | |
dc.description.abstract |
Transportation infrastructure projects are prone to cost and schedule overruns. At the time of contract award, a construction contingency budget is often used to accommodate for unplanned events such as scope changes. Recent empirical research has shown that rework during construction as a result of design changes, errors and omission are the major contributors of overruns in projects. The statistical characteristics of rework, and cost and schedule overruns that are experienced from a project’s contract award for 58 Australian transportation infrastructureprojects are analysed. Theoretical probability distributions are fitted to the rework, cost and schedule overrun data. Goodness of fit tests are used in conjunction with probability-probability (P-P) plots to compare the sample distribution from the known theoretical distribution. A Generalised Logistic probability density function is found to describe the behaviour of cost-overruns and provides the best overall distribution fit. The best fitting distribution for schedule overruns and rework data were the Four Parameter Burr and a Johnson SB distribution, respectively. Thedistributions are used to calculate the probability of rework, cost and schedule overruns being experienced. A case illustration is presented and discussed to demonstrate how the derived probabilities may be utilised in practice. | |
dc.publisher | Taylor & Francis Group | |
dc.title | Overruns in Transportation Infrastructure Projects | |
dc.type | Journal Article | |
dcterms.source.volume | 10 | |
dcterms.source.number | 2 | |
dcterms.source.startPage | 141 | |
dcterms.source.endPage | 159 | |
dcterms.source.issn | 1573-2479 | |
dcterms.source.title | Structure and Infrastructure Engineering | |
curtin.department | Department of Civil Engineering | |
curtin.accessStatus | Fulltext not available |