Abstract
The complex variability of the 12 construction labour productivity data sets has been examined by analysing the central moments of tendency, and applying the Kolmogorov-Smirnov and Anderson-Darling tests of normality. The results consistently show that the productivity is not normally distributed. In addition, undefined variance causes a failure of the central limit theorem, thus indicating that some basic statistical diagnostics like correlation coefficients and t statistics may give misleading results and are not applicable. A brief comparison with volatility studies in econometrics has revealed surprising similarity with Pareto distributions, which can model undefined or infinite variance. Such distributions are typical of chaotic systems like the logistic equation, whose properties also are described briefly. Therefore, it is suggested that future research should be focused on studying the applicability of chaos theory to construction labour.
Original language | English |
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Pages (from-to) | 3-12 |
Number of pages | 10 |
Journal | Construction Management and Economics |
Volume | 20 |
Issue number | 1 |
DOIs | |
Publication status | Published - 2002 |
Keywords
- Construction
- Labour productivity
- Normal distribution
- Tests
- Chaos