This study examines patterns in CWAs in Indonesia, utilizing 14,962 accident records from 2014 to 2020. The analysis relates accidents to workforce composition, building and project characteristics, and seasonality, by conceptualizing accidents as a systemic phenomenon influenced by factors such as workforce, organizational context, and temporal context.
Objective
This study identifies areas with accident rates disproportionate to workforce size, analyses temporal trends, assesses associations between workforce characteristics and construction accidents, assesses the gap between accident risk and safety monitoring capacity, and recommends targeted safety interventions for high-risk projects and building types.
Methods
We summarized accident frequencies and proportions by category; applied chi-square tests for goodness-of-fit and Fisher's Exact Test; mapped provincial CWAs and an Accident Index to identify high-risk areas; analyzing trends and seasonal patterns using a time series approach; compared CWAs across 13 building and project types via one-way ANOVA and Welch ANOVA; and applied Pearson correlation and negative binomial regression for over dispersed count data.
Results
The analysis reveals an uneven spatial and seasonal distribution of CWAs with a peak in October–December. New projects, industrial, residential, and transportation, are at the highest risk. Some pairs of categories are not significantly related. The negative binomial regression indicates that the CWN-SE is negatively and significantly related to accidents.
Conclusions
Temporal factors, project type, and safety capacity influence construction accidents. More CWN-SE means fewer accidents than more technical people do. Safety policies must be risk-based and systems-oriented and take account of the dynamics of time and project characteristics.
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