Model for Quantifying the Impact of Change Orders on Project Cost for U.S. Roadwork Construction
Publication: Journal of Construction Engineering and Management
Volume 136, Issue 9
Abstract
Change orders are very common in almost every construction project nowadays, often resulting in increases of 5–10% in the contract price. Understanding the consequences of such trends, several studies have attempted to quantify the impact of change orders on the project cost. Most of the studies aimed at the quantification of the change orders were sponsored by contractors’ organizations, where statistical models used to quantify the impact of the change orders on the project cost were based on data supplied by the contractors; a situation that can lead to owner-contractor disagreements related to the quantification method used. In addition, most of the studies tackled commercial and electromechanical work, and very rare studies tackled the field of heavy construction; a field that suffers from change orders because of errors and omissions, scope of work changes, or changes because of unforeseen conditions. This study addresses the need for a statistical model to quantify the increase of the contract price due to change orders in heavy construction projects in Florida. The model is based on data collected from 16 Florida DOT projects with contract values that ranged between $10–$25 million, and that encountered an increase in the contract price from 0.01 to 15%. Eleven variables were analyzed to test their impact on the cost of the change orders. The study concluded that most significant variables that impact the value of the change order, which are (1) the timing of the change order and (2) when the reason for issuing the change order is unforeseen conditions. Two regression models are developed and validated as follows: (1) a model to quantify the percentage increase in the contract price due to the change orders that increase the contract price from 0.01 to 5% and (2) a model to quantify the percentage increase in the contract price due to the change orders that increase the contract price from 5 to 15%. Those models will provide the owner with a retrospective or forward pricing of the change orders, and hence, allow the owner to estimate and utilize contingency amounts.
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Acknowledgments
The writers would like to thank the Florida Department of Transportation for their great support in providing the data needed to conduct this research. Also, Florida Department of Transportation claims consultants who guided the researchers to the problem areas that need to be further studied in heavy construction projects.
References
Adrian, J. (1987). Construction productivity improvement, Elsevier Science, New York.
American Institute of Architects. (1977). “General conditions of the contract for construction.” AIA document A201, Washington, D.C.
Burati, J. L., Farrington, J. J., and Ledbetter, W. B. (1992). “Causes of quality deviations in design and construction.” J. Constr. Eng. Manage., 118(1), 34–49.
Chick, D. (1999). “The time value of project change.” Cost Eng., 41(6), 27–31.
Derksen, S., and Keselman, H. J. (1992). “Backward, forward and stepwise automated subset selection algorithms: Frequency of obtaining authentic and noise variables.” Br. J. Math. Stat. Psychol., 45, 265–282.
Finke, M. (1998). “A better way to estimate and mitigate disruption.” J. Constr. Eng. Manage., 124(6), 490–497.
Grimm, C. T., and Wagner, N. K. (1974). “Weather effects on mason productivity.” J. Constr. Div., 11(CO3), 319–334.
Habing, B. (2004). “Transformation of variables.” ⟨http://www.stat.sc.edu/curricula/courses/516/516s7p8sup.pdf⟩ (Apr. 10, 2006).
Hanna, A. S., Russell, J. S., Gotzion, T. W., and Nordheim, E. V. (1999a). “Impact of change orders on labor efficiency for mechanical construction.” J. Constr. Eng. Manage., 125(3), 176–184.
Hanna, A. S., Russell, J. S., Nordheim, E. V., and Bruggink, M. J. (1999b). “Impact of change orders on labor efficiency for electrical construction.” J. Constr. Eng. Manage., 125(4), 224–232.
Hayter, A. (2006). Probability and statistics for engineers and scientists, Duxbury.
Hsieh, T. -Y. (1998). “Impact of subcontracting on site productivity: Lessons learned in Taiwan.” J. Constr. Eng. Manage., 124(2), 91–99.
Ibbs, C. W., and Allen, W. E. (1995). “Quantitative impacts of project change.” Source document 108, Construction Industry Institute (CII), Univ. of Texas at Austin, Austin, Tex.
Ibbs, W. (2005). “Impact of change’s timing on labor productivity.” J. Constr. Eng. Manage., 131(11), 1219–1223.
Ibbs, W., Wong, C., and Kwak, Y. (2001). “Project change management system.” J. Manage. Eng., 17(3), 159–165.
Kartam, N. (1996). “Making effective use of construction lessons learned in project life cycle.” J. Constr. Eng. Manage., 122(1), 14–21.
Moselhi, O., Charles, L., and Fazio, P. (1991). “Impact of change orders on construction productivity.” Can. J. Civ. Eng., 18(3), 484–492.
Naoum, S. (1994). “Critical analysis of time and cost of management and traditional contracts.” J. Constr. Eng. Manage., 120(4), 687–705.
Serag, E., Oloufa, A., and Malone, L. (2008). “Reconciliation of owner and contractor views in heavy construction projects.” J. Profl. Issues Eng. Educ. Pract., 134(1), 128–137.
Shwartzkoph, W. (1995). Calculating lost labor productivity in construction claims, Wiley, New York.
Stat Soft, Inc. (2003). “General regression models.” ⟨http://www.statsoft.com/textbook/stgrm.html⟩ (Dec. 12, 2005).
Sweet, J., and Schneir, M. (2004). Legal aspects of architecture, engineering, and the construction process, 7th Ed., Brookscole, Calif.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 136 • Issue 9 • September 2010
Pages: 1015 - 1027
Copyright
© 2010 ASCE.
History
Received: Dec 2, 2009
Accepted: Feb 15, 2010
Published online: Aug 13, 2010
Published in print: Sep 2010
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