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Journal Article

Citation

Akcay C, Aslan S, Sayin B, Manisalı E. Safety Sci. 2018; 109: 361-367.

Copyright

(Copyright © 2018, Elsevier Publishing)

DOI

10.1016/j.ssci.2018.06.021

PMID

unavailable

Abstract

In the recent years, occupational health and safety (OHS) has become a popular topic in many sectors and holds its ground on the agenda with legal regulations. Given that work accidents occur at a higher rate in the construction industry compared to other sectors, this reality increases the importance of the topic of determining OHS costs in the construction sector. After all, it is notable that the estimation of OHS costs at the project stage is assessed as a situation that requires a great effort from the contractors' standpoint. The aim of this study is to determine the variation in health and safety costs using mathematical methods based on the size of construction areas in construction projects. Moreover, the reflection of considering or ignoring OHS to the level of occurrence of work accidents is determined. In the first stage of the study, variation in the costs of six major health and safety categories according to the size of construction area based on thirty-construction projects was determined using regression analysis. Secondly, considering four hundred-work accidents, the variation in work accidents according to the situations where relevant occupational health and safety equipment categories were considered or not was determined using Pareto analysis. Then, a comparison was made between OHS equipment category costs and work accidents. The findings showed that each category and the total OHS cost exhibited a linear variation with the size of construction area. Thereby, OHS costs could be estimated based on the size of construction areas in the construction projects. It is concluded that the effect of lacking any OHS on the rate of increase of work accidents can be provided using the results of the study.


Language: en

Keywords

Construction industry; OHS; Pareto analysis; Regression analysis; SPSS

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