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Aljassmi, H, Han, S and Davis, S (2014) Project Pathogens Network: New Approach to Analyzing Construction-Defects-Generation Mechanisms. Journal of Construction Engineering and Management, 140(01).

Casanovas, M d M, Armengou, J and Ramos, G (2014) Occupational Risk Index for Assessment of Risk in Construction Work by Activity. Journal of Construction Engineering and Management, 140(01).

Chang, C (2014) Principal-Agent Model of Risk Allocation in Construction Contracts and Its Critique. Journal of Construction Engineering and Management, 140(01).

Choi, S, Kim, D Y, Han, S H and Kwak, Y H (2014) Conceptual Cost-Prediction Model for Public Road Planning via Rough Set Theory and Case-Based Reasoning. Journal of Construction Engineering and Management, 140(01).

González, P, González, V, Molenaar, K and Orozco, F (2014) Analysis of Causes of Delay and Time Performance in Construction Projects. Journal of Construction Engineering and Management, 140(01).

Laryea, S and Lubbock, A (2014) Tender Pricing Environment of Subcontractors in the United Kingdom. Journal of Construction Engineering and Management, 140(01).

Ling, F Y Y, Ke, Y, Kumaraswamy, M M and Wang, S (2014) Key Relational Contracting Practices Affecting Performance of Public Construction Projects in China. Journal of Construction Engineering and Management, 140(01).

Narbaev, T and De Marco, A (2014) Combination of Growth Model and Earned Schedule to Forecast Project Cost at Completion. Journal of Construction Engineering and Management, 140(01).

  • Type: Journal Article
  • Keywords: Construction management; Construction costs; Forecasting; Scheduling; Construction management; Cost forecasting; Earned schedule; Earned value management; Growth model; Nonlinear regression; Cost and schedule;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000783
  • Abstract:
    To improve the accuracy of early forecasting the final cost at completion of an ongoing construction project, a new regression-based nonlinear cost estimate at completion (CEAC) methodology is proposed that integrates a growth model with earned schedule (ES) concepts. The methodology provides CEAC computations for project early-stage and middle-stage completion. To this end, this paper establishes three primary objectives, as follows: (1) develop a new formula based on integration of the ES method and four candidate growth models (logistic, Gompertz, Bass, and Weibull), (2) validate the new methodology through its application to nine past projects, and (3) select the equation with the best-performing growth model through testing their statistical validity and comparing the accuracy of their CEAC estimates. Based on statistical validity analysis of the four growth models and comparison of CEAC errors, the CEAC formula based on the Gompertz model is better-fitting and generates more accurate final-cost estimates than those computed by using the other three models and the index-based method. The proposed methodology is a theoretical contribution towards the combination of earned-value metrics with regression-based studies. It also brings practical implications associated with usage of a viable and accurate forecasting technique that considers the schedule impact as a determinant factor of cost behavior.

Ning, Y and Ling, F Y Y (2014) Boosting Public Construction Project Outcomes through Relational Transactions. Journal of Construction Engineering and Management, 140(01).

Panas, A and Pantouvakis, J P (2014) Simulation-Based and Statistical Analysis of the Learning Effect in Floating Caisson Construction Operations. Journal of Construction Engineering and Management, 140(01).

Rosenfeld, Y (2014) Root-Cause Analysis of Construction-Cost Overruns. Journal of Construction Engineering and Management, 140(01).

Sun, C, Mackley, A and Edara, P (2014) Programmatic Examination of Missouri Incentive/Disincentive Contracts for Mitigating Work Zone Traffic Impacts. Journal of Construction Engineering and Management, 140(01).

Syal, M, Duah, D, Samuel, S, Mazor, M, Mo, Y and Cyr, T (2014) Information Framework for Intelligent Decision Support System for Home Energy Retrofits. Journal of Construction Engineering and Management, 140(01).

Yang, I, Lin, Y and Lee, H (2014) Use of Support Vector Regression to Improve Computational Efficiency of Stochastic Time-Cost Trade-Off. Journal of Construction Engineering and Management, 140(01).

Zhang, S, Du, C, Sa, W, Wang, C and Wang, G (2014) Bayesian-Based Hybrid Simulation Approach to Project Completion Forecasting for Underground Construction. Journal of Construction Engineering and Management, 140(01).