The evidence of complex variability in labour productivity

Malcolm Horner, Milan Radoslavljevic

    Research output: Contribution to journalArticlepeer-review

    36 Citations (Scopus)

    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 languageEnglish
    Pages (from-to)3-12
    Number of pages10
    JournalConstruction Management and Economics
    Volume20
    Issue number1
    DOIs
    Publication statusPublished - 2002

    Keywords

    • Construction
    • Labour productivity
    • Normal distribution
    • Tests
    • Chaos

    Fingerprint

    Dive into the research topics of 'The evidence of complex variability in labour productivity'. Together they form a unique fingerprint.

    Cite this