Highway Construction Data Collection and Treatment in Preparation for Statistical Regression Analysis
Publication: Journal of Construction Engineering and Management
Volume 135, Issue 12
Abstract
Currently, there is not an understanding of the project factors having a statistically significant relationship with highway construction duration. Other industry sectors have successfully used statistical regression analysis to identify and model the project parameters related to construction duration. While the need is seen for such work in highway construction, there are very few studies which attempt to identify duration-influential parameters and their relationship with the highway construction duration. The purpose of this work is to describe the highway construction data needed for such a study, identify a data source, collect early-design project data, and prepare the data for statistical regression analysis. The Virginia Department of Transportation is identified as the optimal data source. The data collected include historical contract and project level parameters. To prepare for statistical regression analysis, the contract duration collected is converted to construction duration by a seasonal adjustment process which removes historically typical nonworking days.
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References
Bromilow, F. J. (1969). “Contract time performance expectations and the reality.” Building Forum, 1(3), 70–80.
Burrows, T. K., Pegg, I., and Martin, J. (2005). “Predicting building construction duration.” Proc., 49th Annual Meeting of Association for the Advancement of Cost Engineering (AACE) Int., AACE, 14–9.
Chan, A. P. C. (1999). “Modeling building durations in Hong Kong.” Constr. Manage. Econom., 17, 189–196.
Chan, A. P. C., and Chan, D. W. M. (2004). “Developing a benchmark model for project construction time performance in Hong Kong.” Build. Environ., 39, 339–349.
Chan, D. W. M., and Kumaraswamy, M. M. (1995). “A study of the factors affecting construction durations in Hong Kong.” Constr. Manage. Econom., 13, 319–333.
Chou, J. -S. (2005). “Item-level quantity-based preliminary cost estimating system for highway earthwork, landscape, subgrade treatments, base, surface courses, pavement and traffic control.” Ph.D., Univ. of Texas at Austin, Austin, Tex.
El-Rayes, K., and Moselhi, O. (2001). “Impact of rainfall on the productivity of highway construction.” J. Constr. Eng. Manage., 127(2), 125–131.
Finke, M. R. (1990). “Weather-related delays on government contracts.” Trans. Am. Assn. Cost Eng.
Jervis, B. M., and Levin, P. (1987). Construction law-principles and practice, McGraw-Hill, New York.
Jiang, Y., and Wu, H. (2007). “A method for highway agency to estimate construction durations and set contract times.” Int. J. Construction Education Res., 3, 199–216.
Khosrowshahi, F., and Kaka, A. P. (1996). “Estimation of project total cost and duration for housing projects in the U.K.” Build. Environ., 31(4), 373–383.
Koehn, E., and Brown, G. (1985). “Climatic effects on construction.” J. Constr. Eng. Manage., 111(2), 129–137.
Kumaraswamy, M. M., and Chan, D. W. M. (1995). “Determinants of construction duration.” Constr. Manage. Econom., 13, 209–217.
Kyte, C. A., Perfater, M. A., Haynes, S., and Lee, H. W. (2004). Developing and validating a highway construction project cost estimation tool, Virginia Transportation Research Council, Charlottesville, Va.
McDonald, D. F. (2000). “Weather delays and impacts.” Construction Engineering, 42(5), 34–39.
National Cooperative Highway Research Program (NCHRP). (1978). “Effect of weather on highway construction.” Transportation Research Record. 47, Transportation Research Board, Washington, D.C.
National Oceanic and Atmospheric Administration (NOAA). (2004). “Climatography of the United States.” Rep. No. 20, U.S. Dept. of Commerce, Blacksburg, Va.
Nkado, R. N. (1992). “Construction time information system for the building industry.” Constr. Manage. Econom., 10, 489–509.
Orczyk, J. J. (1989). “Parametric construction scheduling.” Ph.D. dissertation, Purdue Univ., West Lafayette, Ind.
Ott, R. L., and Longnecker, M. (2001). An introduction to statistical methods and data analysis, Duxbury, Pacific Grove, Calif.
Roebber, P. J., Bruening, S. L., Schultz, D. M., and Cortinas, J. V., Jr. (2003). “Improving snowfall forecasting by diagnosing snow density.” Weather Forecast., 18(2), 264–287.
Skitmore, R. M., and Ng, S. T. (2001). “Australian project time-cost analysis: Statistical analysis of intertemporal trends.” Constr. Manage. Econom., 19, 455–458.
Smith, G. R., and Hancher, D. E. (1989). “Estimating precipitation impacts for scheduling.” J. Constr. Eng. Manage., 115(4), 552–566.
Information & Authors
Information
Published In
Journal of Construction Engineering and Management
Volume 135 • Issue 12 • December 2009
Pages: 1299 - 1306
Copyright
© 2009 ASCE.
History
Received: May 12, 2008
Accepted: Jun 29, 2009
Published online: Nov 13, 2009
Published in print: Dec 2009
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