Abstracts – Browse Results
Click on the titles below to expand the information about each abstract.
Viewing 7 results ...
Hallowell, M R, Hardison, D and Desvignes, M (2016) Information technology and safety: Integrating empirical safety risk data with building information modeling, sensing, and visualization technologies. Construction Innovation, 16(03), 323-47.
Holt, G D (2016) Opposing influences on construction plant and machinery health and safety innovations. Construction Innovation, 16(03), 390-414.
Karimi, H, Taylor, T R B, Goodrum, P M and Srinivasan, C (2016) Quantitative analysis of the impact of craft worker availability on construction project safety performance. Construction Innovation, 16(03), 307-22.
- Type: Journal Article
- Keywords: safety,risk assessment,construction incidents,craft worker shortage,poisson regression analysis,statistical model
- ISBN/ISSN:
- URL: https://doi.org/10.1108/CI-10-2015-0050
- Abstract:
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.
Lee, W and Migliaccio, G C (2016) Physiological cost of concrete construction activities. Construction Innovation, 16(03), 281-306.
Liu, M, Han, S and Lee, S (2016) Tracking-based 3D human skeleton extraction from stereo video camera toward an on-site safety and ergonomic analysis. Construction Innovation, 16(03), 348-67.
Siddula, M, Dai, F, Ye, Y and Fan, J (2016) Classifying construction site photos for roof detection: A machine-learning method towards automated measurement of safety performance on roof sites. Construction Innovation, 16(03), 368-89.
Teizer, J (2016) Right-time vs real-time pro-active construction safety and health system architecture. Construction Innovation, 16(03), 253-80.