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Frontiers of Engineering Management

ISSN 2095-7513

ISSN 2096-0255(Online)

CN 10-1205/N

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Front. Eng    2015, Vol. 2 Issue (4) : 344-350    https://doi.org/10.15302/J-FEM-2015059
Engineering Management Theories and Methodologies
Schedule Compression Impact on Construction Project Safety
Curt Webb1,Lu Gao2,*(),Ling-guang Song3
1. MossiGhisolfi Group, 555 N. Carancahua-Tower II Suite 800, Corpus Christi, TX 78401, USA.
2. Department of Construction Management, University of Houston, Houston, TX 77204, USA.
3. Department of Construction Management, University of Houston, Houston, TX 77204, USA.
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Abstract

Many construction projects are met with stringent timelines or the threat of exorbitant liquidated damages. In addition, construction schedulers are frequently forced to incorporate aggressive schedule compression techniques. As already discussed by previous researchers, these schedule compression techniques have direct impacts on project productivity and quality defects. Researchers have also pointed out that schedule compression will affect safety incidents such as Occupational Safety & Health Administration recordable injuries and near misses over long project durations. However, most of the existing studies treated safety as a subcategory of project productivity and project quality, and minimal research has been done to directly quantify the effect of schedule compression on safety at the project level. Therefore, in this research, we conducted a survey and statistical analysis to investigate the relationship between schedule compression and safety in construction projects. We interviewed various members of the Houston construction community from both industrial and non-industrial roles. Statistical analysis was used to identify factors that have significant impacts on the occurrence of safety incidents at an industry specific level.
Keywords construction safety      schedule compression      overtime      work shift      Hurdle model     
Corresponding Author(s): Lu Gao   
Online First Date: 23 February 2016    Issue Date: 31 March 2016
 Cite this article:   
Curt Webb,Lu Gao,Ling-guang Song. Schedule Compression Impact on Construction Project Safety[J]. Front. Eng, 2015, 2(4): 344-350.
 URL:  
https://academic.hep.com.cn/fem/EN/10.15302/J-FEM-2015059
https://academic.hep.com.cn/fem/EN/Y2015/V2/I4/344
Construction productivity Construction quality Construction safety Safety in other industries
Generalschedulecompression Chang, Hanna, Lackney, and Sullivan (2005); Nepal, Park, and Son (2006) Nepal, Park, and Son (2006)
Overtime Thomas (1992); Noyce and Hanna (1998); Hanna, Taylor, and Sullivan (2005c) Dong (2005) Duchon and Smith (1993); Caruso, Hitchcock, Dick, Russo, and Schmit (2004); Kawada and Ooya (2005)
Workshift Hanna, Chang, Sullivan, and Lackney (2005b); Folkard and Tucker (2003); Folkard andTucker (2003) Rosa (1995); Dembe, Erickson, Delbos, and Banks (2006)
Overmanning Noyce and Hanna (1998); Hanna, Chang, Lackney, and Sullivan (2005a)
Tab.1  Previous Studies of Schedule Compression’s Effect on Safety, Quality and Productivity
Industrial Projects Non-Industrial Projects
Number of responses 18 34
Average man-hour 882,384 527,528
Percentage of usage of schedule compression 67% 42%
Average OSHA recordables 2.3 0.7
Percentage of usage of safety mitigation 79.6% 63.8%
Tab.2  Descriptive Statistics
Variables Abbreviation
Number of OSHA recordables Rec
Project type (1 for industrial project and 0 for nonindustrial project) PrTyp
Project size (Manhours) PrSiz
Overtime (1 if overtime is used in the project and 0 if otherwise) OT
Hours per week (Based on 40 h workweek) HrsPW
Overtime duration (Total weeks of overtime) OTDur
Shift work (1 if shift work is used in the project and 0 if otherwise) SW
Shift work weeks (Total weeks of shiftwork) SWeek
Overmanning (1 if overmanning is used in the project and 0 if otherwise) OvrM
Out of sequence (1 if out of sequence activities are used in the project and 0 if otherwise) OutSeq
Minimum worker experience level (1 if minimum worker experience is required and 0 if otherwise) MinExp
High turnover rate (1 if there is a high turnover rate and 0 if otherwise) HTOr
Safety management program (1 if there is a safety management program and 0 if otherwise) SMP
Drug testing program (1 if a drug testing program exists and 0 if otherwise) DTP
Safety incentive program (1 if a safety incentive program exists and 0 if otherwise) SIP
Safety audits / Inspections (1 if safety audits or inspections are used and 0 if otherwise) SAI
Tab.3  Variables Used for Regression Analysis
Variable Poisson model Logit model
Estimate P-value Estimate P-value Odds ratio
Intercept -5.728×100 0.0001 -2.920×100 0.0247 0.0540
PrTyp 2.594×100 6.340×10-7 2.921×100 0.0220 18.5679
PrSiz 6.371×10-7 2.780×10-6 1.240×10-6 0.0527 1.0000
OT 1.954×100 0.5501 4.271×10-1 0.0456 1.5328
HrsPW 9.127×10-2 0.3272 4.165×10-2 0.6411 1.0425
OTDur 4.836×10-3 0.0028 3.637×10-3 0.8724 1.1359
OutSeq 8.370×10-1 0.5730 7.470×10-1 0.5173 2.1107
MinExp -9.179×10-1 0.1610 -2.166×100 0.0428 0.1146
Tab.4  Hurdle Model Results
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[1] Houchen CAO, Yang Miang GOH. Analyzing construction safety through time series methods[J]. Front. Eng, 2019, 6(2): 262-274.
[2] Lin Yang,Qi-ming Li. The Research Review of the Impact of Design to Construction Safety[J]. Front. Eng, 2015, 2(3): 224-227.
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