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Adeleye, T, Huang, M, Huang, Z and Sun, L (2013) Predicting Loss for Large Construction Companies. Journal of Construction Engineering and Management, 139(09), 1224–36.
Alsamadani, R, Hallowell, M R, Javernick-Will, A and Cabello, J (2013) Relationships among Language Proficiency, Communication Patterns, and Safety Performance in Small Work Crews in the United States. Journal of Construction Engineering and Management, 139(09), 1125–34.
Cruz, C O and Marques, R C (2013) Exogenous Determinants for Renegotiating Public Infrastructure Concessions: Evidence from Portugal. Journal of Construction Engineering and Management, 139(09), 1082–90.
Damci, A, Arditi, D and Polat, G (2013) Multiresource Leveling in Line-of-Balance Scheduling. Journal of Construction Engineering and Management, 139(09), 1108–16.
Franz, B W, Leicht, R M and Riley, D R (2013) Project Impacts of Specialty Mechanical Contractor Design Involvement in the Health Care Industry: Comparative Case Study. Journal of Construction Engineering and Management, 139(09), 1091–7.
Hanna, A S, Thomas, G and Swanson, J R (2013) Construction Risk Identification and Allocation: Cooperative Approach. Journal of Construction Engineering and Management, 139(09), 1098–107.
Hegazy, T, Abdel-Monem, M, Saad, D A and Rashedi, R (2013) Hands-On Exercise for Enhancing Students’ Construction Management Skills. Journal of Construction Engineering and Management, 139(09), 1135–43.
Hollar, D A, Rasdorf, W, Liu, M, Hummer, J E, Arocho, I and Hsiang, S M (2013) Preliminary Engineering Cost Estimation Model for Bridge Projects. Journal of Construction Engineering and Management, 139(09), 1259–67.
- Type: Journal Article
- Keywords: Construction management; Infrastructure; Bridges; Construction costs; Budgets; Preliminary engineering; Preconstruction; Infrastructure; Bridges; Cost estimation; Regression; Planning; Design; Budget control; Project planning and design;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000668
- Abstract:
This paper addresses one of the costs of new bridges, i.e., the cost of doing the preliminary engineering (PE). This particular aspect of cost has largely been neglected because of the difficulty in obtaining appropriate data. Typically, PE costs are determined as a percentage of construction costs, disregarding other project-specific parameters. Bridge projects let by the North Carolina (NC) DOT between 2001 and 2009 were reviewed. From an analysis of these 461 projects, the writers developed statistical models linking variation in PE costs with distinctive project parameters. The primary contribution this paper makes to the body of knowledge is the finding that PE cost estimates for bridge projects are commonly and significantly underestimated. The writers found that bridge projects exhibited a mean PE cost ratio of 28%. This result is significantly greater than the percentage used in practice. An investigation of data sources related to bridge projects, a description of regression techniques applied to predict the PE cost of such projects, and an assessment of the predictive performance of models are addressed in this paper. New knowledge contributions include identification of key factors affecting the PE costs of bridges, illustration of how those key factors enabled us to predict PE costs of future projects, and discussion of the data collection problems that hindered model development. The writers’ PE cost analyses and predictive modeling effort relate to infrastructure funding issues. All of the parties involved in infrastructure construction, from legislators to contractors, must understand costs and have confidence in the cost estimates developed to ensure efficient and effective funding of infrastructure projects. This paper on bridge PE costs addresses one component of infrastructure funding.
Jafari, A and Love, P E D (2013) Quality Costs in Construction: Case of Qom Monorail Project in Iran. Journal of Construction Engineering and Management, 139(09), 1244–9.
Jin, Z, Deng, F, Li, H and Skitmore, M (2013) Practical Framework for Measuring Performance of International Construction Firms. Journal of Construction Engineering and Management, 139(09), 1154–67.
Li, J, Chiang, Y H, Choi, T N Y and Man, K F (2013) Determinants of Efficiency of Contractors in Hong Kong and China: Panel Data Model Analysis. Journal of Construction Engineering and Management, 139(09), 1211–23.
Liu, J Y, Zou, P X W and Gong, W (2013) Managing Project Risk at the Enterprise Level: Exploratory Case Studies in China. Journal of Construction Engineering and Management, 139(09), 1268–74.
Marzouk, M and Amin, A (2013) Predicting Construction Materials Prices Using Fuzzy Logic and Neural Networks. Journal of Construction Engineering and Management, 139(09), 1190–8.
Menesi, W, Golzarpoor, B and Hegazy, T (2013) Fast and Near-Optimum Schedule Optimization for Large-Scale Projects. Journal of Construction Engineering and Management, 139(09), 1117–24.
Shahandashti, S M and Ashuri, B (2013) Forecasting {[}Engineering News-Record{]} Construction Cost Index Using Multivariate Time Series Models. Journal of Construction Engineering and Management, 139(09), 1237–43.
Sunindijo, R Y and Zou, P X W (2013) Conceptualizing Safety Management in Construction Projects. Journal of Construction Engineering and Management, 139(09), 1144–53.
Tas, E, Cakmak, P I and Levent, H (2013) Determination of Behaviors in Building Product Information Acquisition for Developing a Building Product Information System in Turkey. Journal of Construction Engineering and Management, 139(09), 1250–8.
Wang, S, Tang, W and Li, Y (2013) Relationship between Owners’ Capabilities and Project Performance on Development of Hydropower Projects in China. Journal of Construction Engineering and Management, 139(09), 1168–78.
Xie, J and Thomas Ng, S (2013) Multiobjective Bayesian Network Model for Public-Private Partnership Decision Support. Journal of Construction Engineering and Management, 139(09), 1069–81.
Yorucu, V (2013) Construction in an Open Economy: Autoregressive Distributed Lag Modeling Approach and Causality Analysis—Case of North Cyprus. Journal of Construction Engineering and Management, 139(09), 1199–210.
Zhao, X, Hwang, B and Low, S P (2013) Developing Fuzzy Enterprise Risk Management Maturity Model for Construction Firms. Journal of Construction Engineering and Management, 139(09), 1179–89.