Journal of Engineering, Project, and Production Management, 2014, 4(1), 26-35
Estimating Construction Duration for Public Roads During the Preplanning Phase
1Assistant Professor, Faculty of Civil Engineering and Architecture, Lublin University of Technology, 20-618 Lublin, Nadbystrzycka 40, Poland. E-mail: a.czarnigowska@pollub.pl (corresponding author).
2Professor, Department of Geomechanics, Civil Engineering and Geotechnics, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Krakow, Poland. E-mail: sobotka@agh.edu.pl
Project Management
Received May 12, 2013; revision August 28, 2013; accepted August 30, 2013
Available online December 15, 2013
Abstract: Estimates of the construction time are of key importance in the early phases of the project – they serve as a basis for the decision whether to commence with planning or not, and are used as input for budgets and programmes. Usually, such estimates base on experience with similar projects completed in the past. This experience may be recorded in the form of mathematical models that relate project characteristics to construction time. The aim of the research was, basing on real-life cases, to develop a model of public road building projects duration. The research comprised collection of input for the analyses, preselection of project features correlated with duration, and construction of three models: a simple statistical regression, a multifactor regression and a regression tree. The models were then compared to each other and to the models presented in the literature with respect to their predictive ability. With the assumed set of potential predictors of construction duration, the regression models were found statistically correct, though not precise enough be used as decision-support tools.
Keywords: Construction duration estimates, regression tree, multiple regression.
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Citation: Czarnigowska, A. and Sobotka, A. (2014). Estimating Construction Duration for Public Roads During the Preplanning Phase. Journal of Engineering, Project, and Production Management, 4(1), 26-35.
DOI:10.32738/JEPPM.201401.0004
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