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Abdelhamid, T S and Everett, J G (2002) Physiological Demands during Construction Work. Journal of Construction Engineering and Management, 128(05), 427–37.

Bernold, L E (2002) Spatial Integration in Construction. Journal of Construction Engineering and Management, 128(05), 400–8.

Cheung, S, Suen, H C H and Lam, T (2002) Fundamentals of Alternative Dispute Resolution Processes in Construction. Journal of Construction Engineering and Management, 128(05), 409–17.

Jonasson, S, Dunston, P S, Ahmed, K and Hamilton, J (2002) Factors in Productivity and Unit Cost for Advanced Machine Guidance. Journal of Construction Engineering and Management, 128(05), 367–74.

Karumanasseri, G and AbouRizk, S (2002) Decision Support System for Scheduling Steel Fabrication Projects. Journal of Construction Engineering and Management, 128(05), 392–9.

Kululanga, G K, Price, A D F and McCaffer, R (2002) Empirical Investigation of Construction Contractors' Organizational Learning. Journal of Construction Engineering and Management, 128(05), 385–91.

Ling, Y Y (2002) Model for Predicting Performance of Architects and Engineers. Journal of Construction Engineering and Management, 128(05), 446–55.

Lu, M (2002) Enhancing Project Evaluation and Review Technique Simulation through Artificial Neural Network-based Input Modeling. Journal of Construction Engineering and Management, 128(05), 438–45.

Mawdesley, M J, Al-jibouri, S H and Yang, H (2002) Genetic Algorithms for Construction Site Layout in Project Planning. Journal of Construction Engineering and Management, 128(05), 418–26.

Mohamed, S (2002) Safety Climate in Construction Site Environments. Journal of Construction Engineering and Management, 128(05), 375–84.

Skitmore, M and Ng, S T (2002) Analytical and Approximate Variance of Total Project Cost. Journal of Construction Engineering and Management, 128(05), 456–60.

  • Type: Journal Article
  • Keywords: Costs; Correlation; Simulation; Construction; construction industry; cost optimal control; project management; simulation; civil engineering;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)0733-9364(2002)128:5(456)
  • Abstract:
    The statistical variance of total project cost is usually estimated by means of Monte Carlo simulation on the assumption that exact analytic approaches are too difficult. This paper tests that assumption and shows that, contrary to expectations, the analytic solution is relatively straightforward. It is also shown that the coefficient of variation is unaffected by the size (floor area) of the project when using standardized component costs. A case study is provided in which actual component costs are analyzed to obtain the required total cost variance. The results confirm previous work in showing that the approximation of the second moment (variance) under the assumption of independence considerably underestimates the exact value. The analysis then continues to examine the effects of professional judgment, and, with the simulated data used, the approximation is shown to be reasonably accurate—the professional judgment absorbing most of the intercorrelations involved. An example is also given in which the component unit quantities are priced by their average unit costs and which again shows the approximation to be close to the true value. Finally, this is extended to show how the exact total project cost variances may be obtained for each project.