Poisson Model of Construction Incident Occurrence
Publication: Journal of Construction Engineering and Management
Volume 131, Issue 6
Abstract
Construction incidents are essentially random events because they have a probabilistic component that causes their occurrence to be indeterministic. Thus, as with most random events, one of the best ways to understand and analyze construction incidents is to apply statistical methods and tools. Consequently, this paper presents a statistical framework based on the modified loss causation model (MLCM). Even though the MLCM has been used for the framework, the approach can be readily adapted for other incident causation models. The MLCM is separated into two basic components: random and systematic. The random component is represented by a probability density function (PDF), which has parameters influenced by the systematic component of the MLCM, while the systematic component is represented by the situational variables and quality of the safety management system. In particular, this paper proposes that the PDF can be represented by the Poisson distribution. Besides being a convenient and simple distribution that can be easily used in applications, the Poisson distribution had been used in various industries to model random failures or incidents. The differences in contexts and the undesirable effects of adopting an unrepresentative distribution will require formal analysis to determine the suitability of the Poisson distribution in modeling the random component of construction incident occurrence. Incident records for 14 major projects were used in the analysis. Hypothesis testing using the chi-square goodness-of-fit and dispersion tests shows that the incident occurrences can be modeled as a Poisson process characterized by some mean arrival rate. The paper also presents some applications of the proposed Poisson model to improve construction safety management, focusing on two specific concepts: the Bayesian approach and the partitioned Poisson.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
This study would not have been possible without the support of the Safety Department of Singapore’s Land Transport Authority, in particular its cooperation in facilitating access to SITS. The writers are also grateful for the time and effort of its numerous staff.
References
Alsop, J., and Langley, J. (2001). “Under-reporting of motor vehicle traffic crash victims in New Zealand.” Accid. Anal. Prev., 33, 353–359.
Ang, H. S., and Tang, W. H., (1975). Probability concepts in engineering planning and design. Vol. 1, Basic principles, Wiley, New York.
Bendell, A. (1991). “Analysis methodologies.” Reliability data banks, A. G. Cannon and A. Bendell, eds., Galliard Ltd., London.
British Standards Institution (BSI). (1996). “Guide to occupational health and safety management systems.” BS 8800, London.
British Standards Institution (BSI). (2000). “Occupational health and safety management systems—Guidelines for the implementation of OHSAS 18001.” OHSAS 18002, London.
Cattledge, G. H., Hendricks, S., and Stanevich, R. (1996). “Fatal occupational falls in the U.S. construction industry, 1980–1989.” Accid. Anal Prev., 28(5), 647–654.
Chua, D. K. H., and Goh, Y. M. (2003). “Application of case based reasoning in construction safety planning.” Computing in civil engineering, A. D. Songer and J. C. Miles, eds., ASCE, Reston, Va., 298–307.
Chua, D. K. H., and Goh, Y. M. (2004). “Incident causation model for improving feedback of safety knowledge,” J. Constr. Eng. Manage., 130(4), 542–551.
Cochran, W. G. (1954). “Some methods of strengthening the common chi-square tests.” Biometrics, 10, 417–451.
Conover, W. J. (1980). Practical non-parametric statistics, 2nd Ed., Wiley, New York.
Cox, D. R., and Lewis, P. A. (1966). The statistical analysis of series of events, Methuen and Wiley, London.
Fridstrom, L., Ifver, I., Ingebrigtsen, S., Kulmala, R., and Thomsen, L. K. (1995). “Measuring the contribution of randomness, exposure, weather and daylight to the variation in road accident counts.” Accid. Anal. Prev., 27(1), 1–20.
Hinze, J., Pedersen, C., and Fredley, J. (1998). “Identifying root causes of construction injuries.” J. Constr. Eng. Manage., 124(1), 67–71.
Jeong, B. Y. (1998). “Occupational deaths and injuries in the construction industry.” Appl. Ergon., 29(5), 355–360.
Kartam, N. A., and Bouz, R. G. (1998). “Fatalities and injuries in the Kuwaiti construction industry.” Accid. Anal. Prev., 30(6), 805–814.
Larsson, T. J., and Field, B. (2002). “The distribution of occupational injury risks in the Victorian construction industry.” Safety Sci., 40, 439–456.
McKinnon, R. C. (2000). Cause, effect, and control of accidental loss with accident investigation kit, Lewis Publishers, Boca Raton, Fla.
Modarres, M., Kaminskiy, M., and Krivtsov, V. (1999). Reliability engineering and risk analysis—A practical guide, Marcel Dekker, New York.
Montgomery, D. C., and Runger, G. C. (1999). Applied statistics and probability for engineers, 2nd Ed., Wiley, Singapore.
Nicholson, A. J. (1986). “The randomness of accident counts.” Accid. Anal. Prev., 18, 193–198.
Nicholson, A. J., and Wong, Y. D. (1993). “Are accidents Poisson distributed? A statistical test.” Accid. Anal. Prev., 25(1), 91–97.
Productivity and Standards Board (PSB). (1999). “Code of practice for safety management system for construction worksites.” CP 79, Singapore.
Ramsey, J. (1985). “Ergonomics factors in task analysis for consumer product safety.” Journal of Occupational Accidents, 7, 113–123.
Reason, J. (1990). Human error, Cambridge University Press, New York.
Ross, S. M. (2000). Introduction to probability models, Academic Press, New York.
Sanders, M., and Shaw, B. (1988). Research to determine the contribution of system factors in the occurrence of underground injury accidents, Bureau of Mines, Pittsburgh.
Wolff, R. W. (1989). Stochastic modeling and the theory of queues, Prentice-Hall, Englewood Cliffs, N.J.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 131 • Issue 6 • June 2005
Pages: 715 - 722
Copyright
© 2005 ASCE.
History
Received: Mar 3, 2003
Accepted: Mar 2, 2004
Published online: Jun 1, 2005
Published in print: Jun 2005
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.