Abstracts – Browse Results
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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.
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.
- Type: Journal Article
- Keywords: Construction costs; Construction materials; Fuzzy sets; Neural networks; Predictions; Pricing; Cost estimating; Construction materials prices; Fuzzy logic; Neural networks; Quantitative methods;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000707
- Abstract:
Changes in construction materials prices have a great impact on the cost of construction projects. Such changes in prices occur randomly at different rates over time. There is no clear relationship that can be used to provide accurate calculations of materials prices. One of the biggest problems that faces the construction contracts is unbalanced rights and obligations between owners and contractors (the two parties of construction contracts). It is necessary to have a system that is capable of estimating the size and amount of the change in materials prices at reasonable accuracy. There is also a need to predict the change in building materials prices (either increase or decrease) during the execution phase of the project as well as during the preparation of tenders. Thus, determination of the appropriate lead time to order needed building materials to execute various activities could be done. This research presents a system that utilizes fuzzy logic to identify construction materials that are most sensitive to the change in prices. The research proposes a methodology for identification of construction materials that are most sensitive to the change in prices to be used in modifying the contract price with an attempt to predict the amount of future change in materials prices using neural networks technique. To achieve this objective, the research classifies construction cost items into four different components (building materials, equipment, labor, and administrative expenses), which represent the basic cost elements of any cost item. The system is based on the study of the changes in materials prices that occurred in the Egyptian market from 2000 to 2010. It also provides the impact on the prices of cost items in the priced bill of quantities (BOQ), which is determined by the change in prices of cost items’ materials and their share percent on forming the cost item. Getting to identify materials’ share in the bill of quantities’ items has a great influence on the price of the cost item and the priority in ordering these materials according to their impact on the item’s price. The developed system aids construction contractors in studying bids during the tendering stage and procurement planning during the project’s execution. It can also be used by owners’ representatives to estimate the expected total cost of upcoming projects. The system data are obtained from the Central Agency for Public Mobilization and Statistics in Egypt through published periodicals. A numerical example is presented to demonstrate the use of the proposed system.
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.