Development of an approximate construction duration prediction model during the project planning phase for general office buildings
Abstract
Accurate prediction of the construction duration is imperative to the reliable cash flow analysis during the project planning phase when feasibility analysis is carried out. However, lack of information and frequent changes that occur as a result of a negotiation process between the owner and the designer in defining the project scope make it difficult to compute real-time construction duration. Domestic and foreign models for calculating the construction durations cannot be readily applied to computation of construction duration for general office buildings in Korea specifically during the project planning phase as there is a limit in its applicability due to numerous restrictions. Moreover, there are no preceding studies suggesting different computational approaches to predict the entire construction duration for office buildings with the approximate construction duration concept during planning phase. Therefore, based on the collected performance data, this study proposes a multiple linear regression model that facilitates reliable prediction of approximate construction duration for office buildings in the project planning phase. The model will allow the owner and other stakeholders to predict the real-time construction duration using the basic information on office buildings and to assess the construction durations incorporating frequent changes during the project planning phase.
Keyword : general office building, approximate duration, prediction model, multiple linear regression analysis, project planning phase, construction schedule
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Czarnigowska, A.; Sobotka, A. 2014. Estimating construction duration for public roads during the preplanning phase, Journal of Engineering, Project, and Production Management 4(1): 26–35.
Hoffman, G. J.; Thal Jr., A. E.; Webb, T. S.; Weir, J. D. 2007. Estimating performance time for construction projects, Journal of Management in Engineering 23(4). https://doi.org/10.1061/(ASCE)0742-597X(2007)23:4(193)
Hwang, H. S. 2002. Analysis of actual duration by effecting elements to duration estimate – focused on standard duration of the office building construction: Master’s thesis. Hangyang University.
Hwang, H. S.; Kim, K. R.; Suh, S. W.; Kim, C. D.; Shin, D. W. 2002. Analysis of actual duration by effecting elements to duration estimate, Korean Journal of Construction Engineering and Management 3(3).
Ji, W. S. 1990. A study on computation of construction period for high-rise office buildings: Master’s thesis. Chung-Ang University.
Jin, R. Z.; Han, S. W.; Hyun, C. T.; Cha, Y. W. 2016. Application of case-based reasoning for estimating preliminary duration of building project, Journal of Management in Engineering 142(2). https://doi.org/10.1061/(ASCE)CO.1943-7862.0001072
Kaka, A.; Price, A. D. F. 1991. Relationship between value and duration of construction projects, Construction Management and Economics 9(4): 383–400. https://doi.org/10.1080/01446199100000030
Khosrowshahi, F.; Kaka, A. P. 1996. Estimation of project total cost and duration for housing projects in the U.K., Building and Environment 31(4): 375–383. https://doi.org/10.1016/0360-1323(96)00003-0
Kim, J.; Yun, W.; Kim, I. 2016. Estimating approximate construction duration of CFRD in the planning stage, KSCE Journal of Civil Engineering 20(7): 2604–2613. https://doi.org/10.1007/s12205-016-0810-0
Kim, S. H. 2014. Estimation model for no-construction activity duration reflecting characteristics of each construction work type: Master’s thesis. Inha University.
Ko, Y.; Han, S. 2017. A duration prediction using a materialbased progress management methodology for construction operation plans, Sustainability 9: 635. https://doi.org/10.3390/su9040635
Koo, C.; Hong, T.; Chang, T.; Koo, K. 2010. A CBR-based hybrid model for predicting a construction duration and cost based on project characteristics in multi-family housing projects, Canadian Journal of Civil Engineering 37(5): 739–752. https://doi.org/10.1139/L10-007
Lee, H. D.; Lee, S. H.; Seo, Y. C.; Lee, S. B. 2010. Development of a CBR-Based construction duration estimation model for construction projects: Dissertation. Architectural Institute of Korea.
Lin, M. C.; Tseng, H. P.; Ho, S. P.; Young, D. L. 2011. Developing a construction-duration model based on a historical dataset for building project, Journal of Civil Engineering and Management 17(4): 529–539. https://doi.org/10.3846/13923730.2011.625641
Love, P. E. D.; Tse, R. Y. C.; Edwards, D. J. 2005. Time-cost relationships in Australian building construction projects, Journal of Construction Engineering and Management 131(2): 187–194. https://doi.org/10.1061/(ASCE)0733-9364(2005)131:2(187)
Mačková, D.; Bašková, R. 2014. Applicability of Bromilow’s timecost model for residential projects in Slovakia, Selected Scientific Papers – Journal of Civil Engineering 9(2): 5–12. https://doi.org/10.2478/sspjce-2014-0011
Martin, J.; Burrows, T. K.; Pegg, I. 2006. Predicting construction duration of building projects”, in XXIII FIG Congress “Shaping the Change”, 8–13 October 2006, Munich, Germany.
Owolabi, J. D.; Amusan, L. M.; Oloke, C. O.; Olusanya, O.; Tun - jiOlayeni, P.; Owolabi, D.; Peter, J.; Omuh, I. 2014. Causes and effect of delay on project construction delivery time, International Journal of Education and Research 2(4): 197– 208.
Peško, I.; MuIenski, V.; Šešlija, M.; Radović, N.; Vujkov, A.; Bibić, D.; Krklješ, M. 2017. Estimation of costs and dura - tions of construction of urban roads using ANN and SVM, Complexity, Article ID 2450370. https://doi.org/10.1155/2017/2450370
Ryu, H. G.; Kim, S. G.; Lee, H. S. 2006. A Competitive advantage analysis of construction duration through the comparison of actual data of domestic construction firms, Korean Journal of Construction Engineering and Management 7(1).
Thomas, N.; Mak, M. Y.; Skitmore, M.; Lam, K. C.; Varnam, M. 2001. The predictive ability of Bromilow’s time–cost model, Construction Management and Economics 19(2): 165173. https://doi.org/10.1080/01446190150505090
Thomas, N.; Thomas, A. V. 2016. Regression modelling for pre - diction of construction cost and duration, Applied Mechanics and Materials 857: 195–199. https://doi.org/10.4028/www.scientific.net/AMM.857.195