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dc.contributor.authorLove, P.
dc.contributor.authorTeo, Pauline
dc.identifier.citationLove, P. and Teo, P. 2017. Statistical Analysis of Injury and Nonconformance Frequencies in Construction: Negative Binomial Regression Model. Journal of Construction Engineering and Management. 143 (8): Article ID 05017011.

Quality and safety data from 456 projects constructed by an Australian contractor are analyzed. A total of 21,104 and 17,464 injuries and nonconformances (NCR), respectively, were identified and categorized. A total of 86% of injuries that were incurred were because of minor cuts or sprains, but allowed the person to continue to carry out their normal duties. NCRs less than AU$20 thousand accounted for 96% of the total costs incurred. Moreover, NCRs greater than AU$100 thousand and those between AU$20 thousand to AU$100 thousand accounted for 42 and 36%, respectively. The number of NCRs attributed to rework was 47%, which represented 84% of their total cost. Further analysis revealed that injuries were significantly correlated with NCRs, specifically rework (p<0.01 p<0.01 ). As the variance for injuries significantly exceeded its mean, there was overdispersion within the data. Therefore, a negative binomial model was developed to predict injuries, while simultaneously considering the relationship with NCRs and different types of projects based on the worker-hours worked. The mean monthly predicted against actual injuries for 106-month period was computed. The developed model provides an accurate prediction of injury frequency and thus could be used as a passive lead-indicator as part of a contractor’s safety and quality performance programs. In addition, it is promulgated that it can support the process of requisite imagination, which involves anticipating what might go wrong and provide the impetus for testing problems in advance of commencing the construction process with regard to quality and safety issues.

dc.publisherAmerican Society of Civil Engineers
dc.titleStatistical Analysis of Injury and Nonconformance Frequencies in Construction: Negative Binomial Regression Model
dc.typeJournal Article
dcterms.source.titleJournal of Construction Engineering and Management
curtin.departmentDepartment of Civil Engineering
curtin.accessStatusFulltext not available

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