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Arditi, D and Ongkasuwan, D (2009) Duties and Responsibilities of Construction Managers: Perceptions of Parties Involved in Construction. Journal of Construction Engineering and Management, 135(12), 1370–4.

Bayraktar, M E and Hastak, M (2009) Bayesian Belief Network Model for Decision Making in Highway Maintenance: Case Studies. Journal of Construction Engineering and Management, 135(12), 1357–69.

Braimah, N and Ndekugri, I (2009) Consultants’ Perceptions on Construction Delay Analysis Methodologies. Journal of Construction Engineering and Management, 135(12), 1279–88.

Davis, K A and Songer, A D (2009) Resistance to IT Change in the AEC Industry: Are the Stereotypes True?. Journal of Construction Engineering and Management, 135(12), 1324–33.

Fong, P S W and Kwok, C W C (2009) Organizational Culture and Knowledge Management Success at Project and Organizational Levels in Contracting Firms. Journal of Construction Engineering and Management, 135(12), 1348–56.

Hallowell, M R and Gambatese, J A (2009) Construction Safety Risk Mitigation. Journal of Construction Engineering and Management, 135(12), 1316–23.

Lee, H, Shin, J, Park, M and Ryu, H (2009) Probabilistic Duration Estimation Model for High-Rise Structural Work. Journal of Construction Engineering and Management, 135(12), 1289–98.

Sacks, R, Treckmann, M and Rozenfeld, O (2009) Visualization of work flow to support lean construction. Journal of Construction Engineering and Management, 135(12), 1307–15.

Tuuli, M M and Rowlinson, S (2009) Performance Consequences of Psychological Empowerment. Journal of Construction Engineering and Management, 135(12), 1334–47.

Williams, R C, Hildreth, J C and Vorster, M C (2009) Highway Construction Data Collection and Treatment in Preparation for Statistical Regression Analysis. Journal of Construction Engineering and Management, 135(12), 1299–306.

  • Type: Journal Article
  • Keywords: Statistics; Data collection; Regression analysis; Highways and roads; Construction management; Seasonal variations; Weather conditions;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000112
  • 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.