Incident Analysis and Prediction of Safety Performance on Construction Sites

Abstract

The hazardous nature of the construction environment and current incident statistics indicate a pressing need for safety performance improvement. One potential approach is the strategic analysis of leading indicators for measuring safety performance as opposed to using only lagging indicators, which has protractedly been the norm. This study presents a systematic safety performance measurement framework and statistical modeling processes for analyzing safety incident data for accident prediction and prevention on construction sites. Using safety incident data obtained from a construction corporation that implements proactive safety management programs, statistical modeling processes are utilized to identify variables with high correlations of events and incidents that pose dangers to the safety and health of workers on construction sites. The findings of the study generated insights into the different types and impacts of incident causal factors and precursors on injuries and accidents on construction sites. One of the key contributions of this study is the promotion of proactive methods for improving safety performance on construction sites. The framework and statistical models developed in this study can be used to collect and analyze safety data to provide trends in safety performance, set improvement targets, and provide continuous feedback to enhance safety performance on construction sites.