Abstract

Electrocution is one of the four leading causes of worker deaths in the construction sector, and thus it is paramount to identify its mechanisms. This work interprets the mechanisms of an electrical accident as a chain of decision mistakes throughout the entire task process. The objective of this paper is to visualize the decision-making chains in workplace electrical safety for construction workers. Because of construction’s “one-off” nature, the researchers narrow the decision-making chain for specific “features of work” (FOW), a group of distinct activities possessing higher occupational safety and health (OSH) risks and requiring particular attention. By analyzing National Institute of Occupational Safety and Health (NIOSH) electrocution reports, the authors identify five features of work and illustrate their decision-making chains. This work promotes electrical safety and injury prevention through the decision-making lens and contributes to the scholarly body of knowledge by introducing a comprehensive approach to the decision-making chain that is applicable to other safety research.

Get full access to this article

View all available purchase options and get full access to this article.

References

Behm, M. (2005). “Linking construction fatalities to the design for construction safety concept.” Saf. Sci., 43(8), 589–611.
Biggs, D., De Ville, B., and Suen, E. (1991). “A method of choosing multiway partitions for classification and decision trees.” J. Appl. Stat., 18(1), 49–62.
BLS (U.S. Bureau of Labor Statistics). (2014). “Census of fatal occupational injuries (CFOI).” 〈http://www.bls.gov/iif/oshcfoi1.htm〉 (Aug. 30, 2014).
Bondy, J., Lipscomb, H., Guarini, K., and Glazner, J. E. (2005). “Methods for using narrative text from injury reports to identify factors contributing to construction injury.” Am. J. Ind. Med., 48(5), 373–380.
Bouchlaghem, D., Kimmance, A. G., and Anumba, C. J. (2004). “Integrating product and process information in the construction sector.” Ind. Manage. Data Syst., 104(3), 218–233.
Breiman, L., Friedman, J., Stone, C. J., and Olshen, R. A. (1984). Classification and regression trees, Wadsworth International Group, Belmont, CA.
Bunn, T. L., Slavova, S., and Hall, L. (2008). “Narrative text analysis of Kentucky tractor fatality reports.” Accid. Anal. Prev., 40(2), 419–425.
Chi, C. F., Chang, T. C., and Hung, K. H. (2004). “Significant industry-source of injury-accident type for occupational fatalities in Taiwan.” Int. J. Ind. Ergon., 34(2), 77–91.
Chou, J. S. (2012). “Comparison of multilabel classification models to forecast project dispute resolutions.” Expert Syst. Appl., 39(11), 10202–10211.
Du, J., and El-Gafy, M. (2012). “Virtual organizational imitation for construction enterprises: Agent-based simulation framework for exploring human and organizational implications in construction management.” J. Comput. Civ. Eng., 282–297.
Gambatese, J., Behm, M., and Hinze, J. (2005). “Viability of designing for construction worker safety.” J. Constr. Eng. Manage., 1029–1036.
Grover, V., and Kettinger, W. J. (2000). Process think: Winning perspectives for business change in the information age, Idea Group, Hershey, PA.
Haddon, W. (1972). “A logical framework for categorizing highway safety phenomena and activity.” J. Trauma, 12(3), 193–207.
Hartling, L., Pickett, W., and Brison, R. J. (2002). “Derivation of a clinical decision rule for whiplash associated disorders among individuals involved in rear-end collisions.” Accid. Anal. Prev., 34(4), 531–539.
Hasan, A., and Jha, K. N. (2012). “Safety incentive and penalty provisions in Indian construction projects and their impact on safety performance.” Int. J. Inj. Control Safety Promotion, 20(1), 3–12.
Hawkins, D. M. (1982). Topics in applied multivariate analysis, Cambridge University Press, Cambridge, U.K.
Higgins, D. N., Casini, V. J., Bost, P., Johnson, W., and Rautiainen, R. (2001). “The fatality assessment and control evaluation program’s role in the prevention of occupational fatalities.” Inj. Prev., 7(Suppl. 1), i27–i33.
Hill, T., and Lewicki, P. (2006). Statistics: Methods and applications, StatSoft, Bedford, U.K.
Kleiner, B. M. (1997). “An integrative framework for measuring and evaluating information management performance.” Comput. Ind. Eng., 32(3), 545–555.
Kleiner, B. M., Smith-Jackson, T., Mills, T., O’Brien, M., and Haro, E. (2008). “Design, development, and deployment of a rapid universal safety and health system for construction.” J. Constr. Eng. Manage., 273–279.
Leonard, J. (1999). Systems engineering fundamentals, DIANE, Fort Belvoir, VA.
Lim, T. S., Loh, W. Y., and Shih, Y. S. (2000). “A comparison of prediction accuracy, complexity, and training time of thirty-three old and new classification algorithms.” Machine Learning, 40(3), 203–228.
Lincoln, A. E., Sorock, G. S., Courtney, T. K., Wellman, H. M., Smith, G. S., and Amoroso, P. J. (2004). “Using narrative text and coded data to develop hazard scenarios for occupational injury interventions.” Inj. Prev., 10(4), 249–254.
Loh, W. Y. (2011). “Classification and regression trees.” WIREs Data Min. Knowl. Discovery, 1(1), 14–23.
Loh, W. Y., and Shih, Y.-S. (1997). “Split selection methods for classification trees.” Statistica Sinica, 7(4), 815–840.
McCann, M., Hunting, K. L., Murawski, J., Chowdhury, R., and Welch, L. (2003). “Causes of electrical deaths and injuries among construction workers.” Am. J. Ind. Med., 43(4), 398–406.
Pineault, M., Rossignol, M., and Barr, R. G. (1994). “Inter-rater analysis of a classification scheme of occupational fatalities by electrocution.” J. Saf. Res., 25(2), 107–115.
Quinlan, J. R. (1993). C4.5: Programs for machine learning, Morgan Kaufmann, San Francisco.
Reason, J. (2000). “Human error: Models and management.” British Medical J., 320(7237), 768–770.
Ritschard, G. (2014). “CHAIDand earlier supervised tree methods.” Contemporary issues in exploratory data mining in the behavioral sciences, J. J. McArdle and G. Ritschard, eds., Routledge, New York, 48–74.
Robbins, S. P., and Judge, T. A. (2007). Organizational behavior, Pearson/Prentice Hall, Upper Saddle River, NJ.
Sonquist, J. A., and Morgan, J. N. (1964). “The detection of interaction effects: A report on a computer program for the selection of optimal combinations of explanatory variables.” Survey Research Center, Institute for Social Research, Univ. of Michigan, Ann Arbor, MI.
SPSS version 20.0 [Computer software]. Armonk, NY, IBM.
Tan, P. N. (2006). Introduction to data mining, Pearson Education, New York.
Taylor, A. J., McGwin, G. M., Valent, F., and Rue, L. W. (2002). “Fatal occupational electrocutions in the United States.” Inj. Prev., 8(4), 306–312.
Tufféry, S. (2011). Data mining and statistics for decision making, Wiley, West Sussex, U.K.
Williamson, A., and Feyer, A. M. (1998). “The causes of electrical fatalities at work.” J. Saf. Res., 29(3), 187–196.
Witten, I. H., and Frank, E. (2005). Data mining: Practical machine learning tools and techniques, 2nd Ed., Elsevier Science, Oxford, U.K.
Zhao, D., and Lucas, J. (2015). “Virtual reality simulation for construction safety promotion.” Int. J. Inj. Control Saf. Promotion, 22(1), 57–67.
Zhao, D., McCoy, A. P., Kleiner, B. M., and Smith-Jackson, T. L. (2015). “Control measures of electrical hazards: An analysis of construction industry.” Saf. Sci., 77, 143–151.
Zhao, D., Thabet, W., McCoy, A., and Kleiner, B. (2012). “Managing electrocution hazards in the USconstruction industry using VRsimulation and cloud technology.” eWork and eBusiness in architecture, engineering and construction, ECPPM 2012, G. Gudnason and R. Scherer, eds., CRC Press, Leiden, Netherlands, 759–764.
Zhao, D., Thabet, W., McCoy, A., and Kleiner, B. (2014). “Electrical deaths in the U.S. construction: An analysis of fatality investigations.” Int. J. Inj. Control Saf. Promotion, 21(3), 278–288.

Information & Authors

Information

Published In

Go to Journal of Construction Engineering and Management
Journal of Construction Engineering and Management
Volume 142Issue 1January 2016

History

Received: Feb 2, 2015
Accepted: May 28, 2015
Published online: Jul 15, 2015
Discussion open until: Dec 15, 2015
Published in print: Jan 1, 2016

Permissions

Request permissions for this article.

Authors

Affiliations

Dong Zhao, Ph.D., A.M.ASCE [email protected]
Assistant Professor, Michigan State Univ., 552 West Circle Dr., East Lansing, MI 48824; formerly, Postdoctoral Fellow, Myers-Lawson School of Construction, Virginia Tech, Blacksburg, VA 24061-0188 (corresponding author). E-mail: [email protected]
Andrew P. McCoy, Ph.D. [email protected]
Associate Professor and Assistant Director, Myers-Lawson School of Construction, Virginia Tech, Blacksburg, VA 24061-0188. E-mail: [email protected]
Brian M. Kleiner, Ph.D. [email protected]
Professor and Director, Myers-Lawson School of Construction, Virginia Tech, Blacksburg, VA 24061-0188. E-mail: [email protected]
Jing Du, Ph.D. [email protected]
Assistant Professor, Dept. of Construction Science, Univ. of Texas at San Antonio, San Antonio, TX 78207. E-mail: [email protected]
Tonya L. Smith-Jackson, Ph.D. [email protected]
Professor and Head, Dept. of Industrial and Systems Engineering, North Carolina A&T State Univ., Greensboro, NC 27411. E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share