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Arshad, M F, Thaheem, M J, Nasir, A R and Malik, M S A (2019) Contractual Risks of Building Information Modeling: Toward a Standardized Legal Framework for Design-Bid-Build Projects. Journal of Construction Engineering and Management, 145(04).
Baek, M and Ashuri, B (2019) Analysis of the Variability of Submitted Unit Price Bids for Asphalt Line Items in Highway Projects. Journal of Construction Engineering and Management, 145(04).
Chao, L and Liaw, S (2019) Fuzzy Logic Model for Determining Minimum Overheads-Cum-Markup Rate. Journal of Construction Engineering and Management, 145(04).
Deng, Y, Gan, V J L, Das, M, Cheng, J C P and Anumba, C (2019) Integrating 4D BIM and GIS for Construction Supply Chain Management. Journal of Construction Engineering and Management, 145(04).
Hacker, M E, Kaminsky, J and Faust, K M (2019) Legitimizing Involvement in Emergency Accommodations: Water and Wastewater Utility Perspectives. Journal of Construction Engineering and Management, 145(04).
Jin, R and Chen, Q (2019) Overview of Concrete Recycling Legislation and Practice in the United States. Journal of Construction Engineering and Management, 145(04).
Kereri, J O and Harper, C M (2019) Social Networks and Construction Teams: Literature Review. Journal of Construction Engineering and Management, 145(04).
Kim, J, Ham, Y, Chung, Y and Chi, S (2019) Systematic Camera Placement Framework for Operation-Level Visual Monitoring on Construction Jobsites. Journal of Construction Engineering and Management, 145(04).
Li, H, Wang, M and Dong, X (2019) Resource Leveling in Projects with Stochastic Minimum Time Lags. Journal of Construction Engineering and Management, 145(04).
Li, Y, Li, G, Wang, T, Zhu, Y and Li, X (2019) Semicustomized Design Framework of Container Accommodation for Migrant Construction Workers. Journal of Construction Engineering and Management, 145(04).
Mitikie, B B and Lee, T S (2019) Experimental Investigation of Enzyme Stabilization and Its Effect on Clay Brick. Journal of Construction Engineering and Management, 145(04).
Nasirian, A, Arashpour, M, Abbasi, B and Akbarnezhad, A (2019) Optimal Work Assignment to Multiskilled Resources in Prefabricated Construction. Journal of Construction Engineering and Management, 145(04).
Noorizadeh, A, Peltokorpi, A and Avkiran, N K (2019) Supplier Performance Evaluation in Construction Projects: Challenges and Possible Solutions. Journal of Construction Engineering and Management, 145(04).
O’Connor, J T and Mock, B D (2019) Construction, Commissioning, and Startup Execution: Problematic Activities on Capital Projects. Journal of Construction Engineering and Management, 145(04).
Oswald, D, Wade, F, Sherratt, F and Smith, S D (2019) Communicating Health and Safety on a Multinational Construction Project: Challenges and Strategies. Journal of Construction Engineering and Management, 145(04).
Son, J, Khwaja, N and Milligan, D S (2019) Planning-Phase Estimation of Construction Time for a Large Portfolio of Highway Projects. Journal of Construction Engineering and Management, 145(04).
- Type: Journal Article
- Keywords:
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001637
- Abstract:
Estimation of highway project construction time prior to design development has received comparatively little focus from researchers. State transportation agencies (STAs) and their management teams need a method or tool to estimate construction time during the project planning and development phases, where STAs typically manage hundreds of projects at the program level. These programs of projects are updated periodically, which requires an estimation methodology that is efficient, less time consuming, and reliable during the phases where limited project information is available. This paper presents an approach to developing a planning-phase construction time estimation model using linear regression modeling on actual construction time and cost data from 623 highway projects completed by the Dallas District Office, Texas Department of Transportation (TxDOT). The study developed a multiple linear regression model with three project parameters that were identified as key predictors to construction time. The accuracy and reliability of the developed model were higher than those of the well-known Bromilow’s time-cost (BTC) model. The model was also validated by the Mann-Whitney test of its applicability to a large group of projects. The proposed model requires less effort to develop, update, and revise with new data, which allows STAs to conduct planning-phase estimation of the construction time of a large portfolio of diverse projects effectively and efficiently. STAs would benefit from using this model in various project planning areas such as financial planning, staff planning, transportation impact mitigation, budget allocation, and project prioritization. This study also contributes to the body of knowledge with the proposed construction time estimation methodology during the planning and development phase that has been less focused.
Wu, L, Jia, G and Mackhaphonh, N (2019) Case Study on Improving the Effectiveness of Public Participation in Public Infrastructure Megaprojects. Journal of Construction Engineering and Management, 145(04).
Xiong, B, Skitmore, M, Xia, P, Ballesteros-Pérez, P, Ye, K and Zhang, X (2019) Impact of Corporate Credit Scoring on Construction Contractors in China. Journal of Construction Engineering and Management, 145(04).