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Time–cost relationship for predicting construction duration

Wybrane pełne teksty z tego czasopisma
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Reliable estimates of project cost and duration are necessary inputs for decision-making in the earliest stages of construction projects. As little data is available, the estimates can only rest upon records of similar completed schemes. The tools that use such records to facilitate project planning continue to be the object of interest of researchers. This paper investigates the applicability of a simple regression model for the prediction of road construction duration on the basis of early cost estimates. Statistical validity of the model was confirmed, and its predictive ability tested.
Rocznik
Strony
518--526
Opis fizyczny
Bibliogr. 43 poz., tab., wykr.
Twórcy
  • Lublin University of Technology, ul. Nadbystrzycka 40, 20-618 Lublin, Poland
autor
  • AGH University of Science and Technology, Department of Geomechanics, Civil Engineering and Geotechnics, Al. Mickiewicza 30, 30-059 Krakow, Poland
Bibliografia
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  • [11] J.S. Chou, Generalized linear model-based expert system for estimating the cost of transportation projects, Expert Systems with Applications 36 (2009) 253-4267.
  • [12] A. Choudhury, S.S. Rajan, Time Cost Relationship for Residential Construction in Texas, Construction Informatics Digital Library, 2003. URL http://itc.scix.net/paperw78-2003-73.content.
  • [13] E. Koźniewski, Z. Orłowski, Forecasting of the concrete mix production by multiple regression (Prognozowanie zapotrzebowania na beton towarowy za pomocą regresji wielorakiej), in: A. Łapko, J.A. Prusiel (Eds.), Problemy naukowo-badawcze budownictwa, Tom III: Materiały, technologie i organizacja w budownictwie, Polska Akademia Nauk, Komitet Inżynierii Lądowej i Wodnej, Wydawnictwo Politechniki Białostockiej, Białystok, 2007, pp. 265-273 (in Polish).
  • [14] Y.-R. Wang, G.E. Gibson Jr., A study of preproject planning and project success using ANNs and regression models, Automation in Construction 19 (3) (2010) 341-346.
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  • [16] P. Jaśkowski, S. Biruk, R. Bucoń, Assessing contractor selection criteria weights with fuzzy AHP method application in group decision environment, Automation in Construction 19 (2) (2010) 120-126.
  • [17] M. Rogalska, W. Bożejko, Z. Hejducki, Time/cost optimization using hybrid evolutionary algorithm in construction project scheduling, Automation in Construction 18 (1) (2008) 24-31.
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  • [26] M. Ifran, M.B. Khursid, P. Anastasopoulos, S. Labi, F. Moavenzadeh, Planning-stage estimation of highway project duration on the basis of anticipated project cost, project type, and contract type, International Journal of Project Management 29 (1) (2011) 78-92.
  • [27] D.H.T. Walker, Y.J. Shen, Project understanding, flexibility of management action and construction time performance: two Australian case studies, Construction Management and Economics 20 (2002) 31-44.
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  • [29] Ch. Stoy, S. Polalis, Early estimation of building construction speed in Germany, International Journal of Project Management 25 (2007) 283-289.
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  • [36] D.H.T. Walker, An investigation into construction time performance, Construction Management and Economics 13 (1995) 263-274.
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  • [38] Time and Cost Predictability of Construction Projects, Analysis of UK Performance, Building Cost Information Service, London, 2000.
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Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-ee9a2ccb-88f5-4fe7-9cd7-0bd69c48d22a
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