Quantitative analysis of the impact of craft worker availability on construction project safety performance

• Published in: Construction innovation Vol. 16; no. 3; pp. 307 - 322
• Main Authors: Karimi, Hossein, Taylor, Timothy R.B, Goodrum, Paul M, Srinivasan, Cidambi
• Format: Journal Article
• Language: English
• Published: London Emerald Group Publishing Limited 11-07-2016
• Subjects: Construction accidents & safety; Construction industry; Construction methods; Crafts; Data collection; Datasets; Federal agencies; Hypotheses; Impact analysis; Labor shortages; Occupational safety; Poisson density functions; Project engineering; Quantitative analysis; Regression analysis; Regression models; Research projects; Safety engineering; Shortages; Statistical analysis; Workers; Workforce planning; United States > US; Construction incidents; Poisson regression analysis; Safety; Craft worker shortage; Risk assessment; Statistical model
• ISSN: 1471-4175; 1477-0857
• DOI: 10.1108/CI-10-2015-0050

Purpose
This paper aims to quantify the impact of craft worker shortage on construction project safety performance.
Design/methodology/approach
A database of 50 North American construction projects completed between 2001 and 2014 was compiled by taking information from a research project survey and the Construction Industry Institute Benchmarking and Metrics Database. The t-test and Mann-Whitney test were used to determine whether there was a significant difference in construction project safety performance on projects with craft worker recruiting difficulty. Poisson regression analysis was then used to examine the relationship between craft worker recruiting difficulty and Occupational Safety and Health Administration Total Number of Recordable Incident Cases per 200,000 Actual Direct Work Hours (TRIR) on construction projects.
Findings
The result showed that the TRIR distribution of a group of projects that reported craft worker recruiting difficulty tended to be higher than the TRIR distribution of a group of projects with no craft worker recruiting difficulty (p-value = 0.004). Moreover, the average TRIR of the projects that reported craft worker recruiting difficulty was more than two times the average TRIR of projects that experienced no craft recruiting difficulty (p-value = 0.035). Furthermore, the Poisson regression analysis demonstrated that there was a positive exponential relationship between craft worker recruiting difficulty and TRIR in construction projects (p-value = 0.004).
Research limitations/implications
The projects used to construct the database are heavily weighted towards industrial construction.
Practical implications
There have been significant long-term gains in construction safety within the USA. However, if recent craft shortages continue, the quantitative analyses presented herein indicate a strong possibility that more safety incidents will occur unless the shortages are reversed. Innovative construction means and methods should be developed and adopted to work in a safe manner with a less qualified workforce.
Originality/value
The Poisson regression model is the first model that quantifiably links project craft worker availability to construction project safety performance.