Cost of Occupational Incidents for Electrical Contractors: Comparison Using Robust-Factorial Analysis of Variance
Cost of Occupational Incidents for Electrical Contractors: Comparison Using Robust-Factorial Analysis of Variance
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DOI：
10.1061/(asce)co.1943-7862.0001861
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发表时间：
2020-07-01
影响因子：
5.1
通讯作者：
Esmaeili, Behzad
中科院分区：
文献类型：
--
作者：
Gholizadeh, Pouya;Esmaeili, Behzad
建筑事故可能对项目的绩效产生负面影响。评估这些事故的经济后果是衡量其对业主，承包商和社会影响的有效方法。虽然有几项研究估计了不同行业、人口统计学、事件类型、伤害来源和伤害性质之间的伤害成本，但这些研究中的大多数提供了描述性统计数据，而没有分析任何关于平均成本之间差异的推断性统计数据。为了解决这一局限性，本研究利用三因素析因方差分析设计的位置（修剪均值）和规模（Winsorized方差）的鲁棒性措施，以检查变量对电力承包商之间的伤害成本的影响。为了建立一个可靠的电气承包商伤害事故数据库，该团队从2016年职业安全与健康管理局（OSHA）数据库中收集了388起非致命事故。为了确定应用于伤害成本分析的推断统计方法的有效性，使用三种稳健的方法检验了零假设：（1）Welch型程序;（2）Yuen方法的扩展;和（3）百分位数自举。研究结果证实，稳健的假设检验方法可以成功地实施安全性数据，即使违反了传统的检验统计的假设。在电气案例研究方面，结果表明，各种事件类型和项目最终用途可以改变电气承包商之间的伤害成本。具体而言，调查结果显示，平均而言，陷入/之间和暴露于电力事故可能导致更高的伤害成本，而不是下降到较低的水平和物体/设备事故。就项目的最终用途而言，平均而言，非建筑项目中的建筑事故造成的伤害比建筑物中的伤害更昂贵。本研究的方法结果可以帮助承包商更好地量化风险的建设项目/任务，估计潜在的事故的严重程度在货币价值。此外，本研究通过评估不需要特定假设的假设检验替代方法，为当前的安全知识体系做出了贡献。
Construction accidents can negatively affect the performance of a project. Evaluating the financial consequences of these accidents is an effective method for measuring their impacts on owners, contractors, and society. While several studies have estimated the cost of injuries among different trades, demographics, event types, injury sources, and nature of injuries, most of these studies presented descriptive statistics without analyzing any inferential statistics regarding the differences between average costs. To address this limitation, this study utilized robust measures of location (trimmed mean) and scale (Winsorized variance) in a three-way factorial ANOVA design to examine the effect of variables on the cost of injuries among electrical contractors. To create a reliable accident database of electrical contractor injuries, the team aggregated 388 nonfatal accidents collected from the 2016 Occupational Safety and Health Administration (OSHA) database. To determine the effectiveness of inferential statistical methods as applied to injury-cost analysis, null hypotheses were tested using three robust methods: (1) the Welch-type procedure; (2) an extension of Yuen's method; and (3) percentile bootstrapping. The results of the study confirm that robust hypothesis testing approaches can be successfully implemented on safety data even when the assumptions of conventional test statistics are violated. In terms of the electrical case study, the outcomes indicate that various event types and project end-uses can change the cost of injuries among electrical contractors. Specifically, the findings revealed that caught in/between and exposure to electricity accidents can, on average, lead to higher injury costs than fall to lower levels and struck-by objects/equipment accidents. In terms of project's end-use, construction accidents, on average, resulted in costlier injuries in nonbuilding projects than in buildings. The methodological results of this study can help contractors better quantify the risks of a construction project/task by estimating the severity of potential accidents in monetary values. Furthermore, this study contributes to the current body of safety knowledge by assessing alternative methods of hypothesis testing that do not require specific assumptions.