Name
Abstract | ||
|---|---|---|
The probability of schedule overruns for construction and engineering projects can be ascertained using a 'best fit' probability distribution from an empirical distribution. The statistical characteristics of schedule overruns occurring in 276 Australian construction and engineering projects were analysed. Skewness and kurtosis values revealed that schedule overruns are non-Gaussian. Theoretical probability distributions were then fitted to the schedule overrun data; including the Kolmogorov-Smirnov, Anderson-Darling and Chi-Squared non-parametric tests to determine the 'Goodness of Fit'. A Four Parameter Burr probability function best described the behaviour of schedule overruns, provided the best overall distribution fit and was used to calculate the probability of a schedule overrun being experienced. The statistical characteristics of contract size and schedule overruns were also analysed, and the Wakeby (<AU$1 m and AU$11-50 m), Three Parameter Log-logistic (AU$1-A$10 m) and Beta (AU$51-A$100 m and >AU$101 m) models provided the best distribution fits and were used to calculate schedule overrun probabilities by contract size. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1057/jors.2013.29 | JORS |
Keywords | Field | DocType |
probability,probability distribution,distribution fitting | Empirical distribution function,Computer science,Distribution fitting,Probability distribution,Probability density function,Goodness of fit,Operations management,Kurtosis | Journal |
Volume | Issue | ISSN |
64 | 8 | 0160-5682 |
Citations | PageRank | References |
0 | 0.34 | 7 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Peter E. D. Love | 1 | 1236 | 111.34 |
| C.-P. Sing | 2 | 0 | 0.68 |
| Xiangyu Wang | 3 | 30 | 3.26 |
| D. J. Edwards | 4 | 0 | 0.34 |
| Henry Odeyinka | 5 | 3 | 0.97 |