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Burleson, R C, Haas, C T, Tucker, R L and Stanley, A (1998) Multiskilled Labor Utilization Strategies in Construction. Journal of Construction Engineering and Management, 124(06), 480–9.

Camfield, F E (1998) Guidelines for Quarrystone Armor Units. Journal of Construction Engineering and Management, 124(06), 465–6.

Diekmann, J E and Featherman, W D (1998) Assessing Cost Uncertainty: Lessons from Environmental Restoration Projects. Journal of Construction Engineering and Management, 124(06), 445–51.

Finke, M R (1998) A Better Way to Estimate and Mitigate Disruption. Journal of Construction Engineering and Management, 124(06), 490–7.

Harper, R S and Koehn, E (1998) Managing Industrial Construction Safety in Southeast Texas. Journal of Construction Engineering and Management, 124(06), 452–7.

Kale, S and Arditi, D (1998) Business Failures: Liabilities of Newness, Adolescence, and Smallness. Journal of Construction Engineering and Management, 124(06), 458–64.

Konchar, M and Sanvido, V (1998) Comparison of U.S. Project Delivery Systems. Journal of Construction Engineering and Management, 124(06), 435–44.

  • Type: Journal Article
  • Keywords:
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(1998)124:6(435)
  • Abstract:
    Construction management at risk, design/build and design/bid/build are three principal project delivery systems used in the United States today. This paper empirically compares cost, schedule, and quality performance of these three project delivery systems, using project-specific data collected from 351 U.S. building projects. The study included collecting, checking, and validating industry data, significance testing of univariate comparisons and the statistical development of multivariate linear regression models for predicting average project performance. A nonresponse study verified statistically that collected data were appropriate for analysis and representative of the industry from which they were drawn. Significance testing and multivariate comparisons used nearly 100 explanatory and interacting variables to explain project cost, schedule, and quality performance. Specific comparisons between project delivery systems, performance metrics, and six facility classes are discussed. Results and the level of confidence that surrounds each finding are presented.

Molenaar, K R and Songer, A D (1998) Model for Public Sector Design-Build Project Selection. Journal of Construction Engineering and Management, 124(06), 467–79.

Sonmez, R and Rowings, J E (1998) Construction Labor Productivity Modeling with Neural Networks. Journal of Construction Engineering and Management, 124(06), 498–504.