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Modelling construction completion cost in Ghana public sector building projects

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Abstract

The research suggests that project completion cost is affected by various predictive factors. Using 911 building projects undertaken in Ghana, this paper uses the multiple regression analysis to develop a forecast model that allows estimating completion cost of projects at the contract award stage. The proposed model uses initial contract sum, number of storeys, scope change and initial duration as predictive variables for projects completion cost. Initial contract sum has a more significant influence in completion cost with the other variable also contributing to the value of completion. Sensitivity analysis was carried out to determine the best performing model among the three models developed.

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References

  • Ahiaga-Dagbui, D. D., & Smith, S. D., (2014). Exploring escalation of commitment in construction project management: Case study of the Scottish Parliament project. In A. Raiden & R. Aboagye-Nimo (Eds.), Proceedings 30th annual ARCOM conference. 1–3 September 2014 (pp. 753–762). Nottingham: Association of Researchers in Construction Management.

  • Asiedu, R. O., & Alfen, H. W. (2014a). Factors engendering cost misrepresentation of public sector projects in Ghana. International Journal of Sustainable Construction Engineering and Technology, 5(2), 13–24.

    Google Scholar 

  • Asiedu, R. O., & Alfen, H. W. (2014b). Understanding the Critical Failure Factors Contributing to Cost Overruns in Public Sector Projects. In 4th international conference on infrastructure development in Africa, Kwame Nkrumah University of Science and Technology, Kumasi, 26–28 March (pp. 106–120).

  • Asiedu, R. O., & Alfen, H. W. (2015). Understanding the underlying reasons behind time overruns of government building projects in Ghana. KSCE Journal of Civil Engineering,  20(6), 2103–2111.

    Article  Google Scholar 

  • Attalla, M., & Hegazy, T. (2003). Predicting cost deviation in reconstruction projects: Artificial neural networks versus regression. Journal of Construction Engineering and Management, 129(4), 405–411. https://doi.org/10.1061/(asce)0733-9364(2003)129:4(405).

    Article  Google Scholar 

  • Bayram, S., & Al-Jibouri, S. (2017). Cost forecasting using RCF: A case study for planning public building projects costs in Turkey. International Journal of Construction Management, 18(5), 405–417. https://doi.org/10.1080/15623599.2017.1333399.

    Article  Google Scholar 

  • Bordat, C., McCullouch, B. G., Labi, S., & Sinha, K. C. (2004). An analysis of cost overruns and time delays of INDOT projects. Publication FHWA/IN/JTRP-2004/07. West Lafayette: Joint Transportation Research Program, Indiana Department of Transportation and Purdue University. https://doi.org/10.5703/1288284313134.

  • Callegari, C., Szklo, A., & Schaeffer, R. (2018). Cost overruns and delays in energy megaprojects: How big is big enough? Energy Policy, 114, 211–220. https://doi.org/10.1016/j.enpol.2017.11.059.

    Article  Google Scholar 

  • Chan, D. W. M., & Kumaraswamy, M. (2002). Compressing construction durations: Lessons learned from Hong Kong building projects. International Journal of Project Management, 20(1), 23–35. https://doi.org/10.1016/s0263-7863(00)00032-6.

    Article  Google Scholar 

  • Chen, Q., Jin, Z., Xia, B., Wu, P., & Skitmore, M. (2016). Time and cost performance of design—Build projects. Journal of Construction Engineering and Management, 142, 1–7.

    Google Scholar 

  • Doloi, H. K. (2011). Understanding stakeholders’ perspective of cost estimation in project management. International Journal of Project Management, 29(5), 622–636. https://doi.org/10.1016/j.ijproman.2010.06.001.

    Article  Google Scholar 

  • Flyvbjerg, B. (2009). Survival of the unfittest: Why the worst infrastructure gets built–and what we can do about it. Oxford Review of Economic Policy, 25(3), 344–367. https://doi.org/10.1093/oxrep/grp024.

    Article  Google Scholar 

  • Flyvbjerg, B. (2014). What you should know about megaprojects and why: An overview. Project Management Journal, 45(2), 6–19. https://doi.org/10.1002/pmj.21409.

    Article  Google Scholar 

  • Flyvbjerg, B., Holm, M. S., & Buhl, S. (2002). Underestimating costs in public works projects: Error or lie? Journal of the American Planning Association, 68(3), 279–295. https://doi.org/10.1080/01944360208976273.

    Article  Google Scholar 

  • Flyvbjerg, B., Skamris Holm, M. K., & Buhl, Søren L. (2013). Underestimating costs in public works projects: Error or lie?. St. Louis: Federal Reserve Bank of St Louis.

    Google Scholar 

  • Frimpong, Y., Oluwoye, J., & Crawford, L. (2003). Causes of delays and cost overruns in construction groundwater projects in developing countries: Ghana case study. International Journal of Project Management, 21, 321–326.

    Article  Google Scholar 

  • Huo, T., Ren, H., Cai, W., Shen, G. Q., Liu, B., Zhu, M., et al. (2018). Measurement and dependence analysis of cost overruns in megatransport infrastructure projects: Case study in Hong Kong. Journal of Construction Engineering and Management, 144(3), 05018001. https://doi.org/10.1061/(asce)co.1943-7862.0001444.

    Article  Google Scholar 

  • Kahneman, D., & Lovallo, D. (2003). Delusions of success—How optimism undermines executive’s decisions. Harvard Business Review, 81, 56–63.

    Google Scholar 

  • Love, P. E. D., Ahiaga-Dagbui, D. D., Smith, S. D., Sing, M. C.-P., & Tokede, O. (2018). Cost profiling of water infrastructure projects. Journal of Infrastructure Systems, 24(4), 04018023. https://doi.org/10.1061/(asce)is.1943-555x.0000441.

    Article  Google Scholar 

  • Love, P. E. D., Edwards, D. J., & Irani, Z. (2012). Moving beyond optimism bias and strategic misrepresentation: An explanation for social infrastructure project cost overruns. IEEE Transactions on Engineering Management, 59(4), 560–571.

    Article  Google Scholar 

  • Love, P. E. D., Edwards, D. J., & Smith, J. (2005). Contract Documentation and the Incidence of Rework in Projects. Architectural Engineering and Design Management, 1(4), 247–259. https://doi.org/10.1080/17452007.2005.9684596.

    Article  Google Scholar 

  • Love, P. E. D., Smith, J., Simpson, I., Regan, M., & Olatunji, O. (2015). Understanding the landscape of overruns in transport infrastructure projects. Environment and Planning B: Planning and Design, 42(3), 490–509. https://doi.org/10.1068/b130102p.

    Article  Google Scholar 

  • Odeck, J. (2004). Cost overruns in road construction—What are their sizes and determinants? Transport Policy, 11(1), 43–53.

    Article  Google Scholar 

  • Ökmen, Ö., & Öztaş, A. (2010). Construction cost analysis under uncertainty with correlated cost risk analysis model. Construction Management and Economics, 28(2), 203–212. https://doi.org/10.1080/01446190903468923.

    Article  Google Scholar 

  • Plummer Braeckman, J., Disselhoff, T., & Kirchherr, J. (2019). Cost and schedule overruns in large hydropower dams: An assessment of projects completed since 2000. International Journal of Water Resources Development. https://doi.org/10.1080/07900627.2019.1568232.

    Google Scholar 

  • Sinesilassie, E. G., Tabish, S. Z. S., & Jha, K. N. (2017). Critical factors affecting cost performance: A case of Ethiopian public construction projects. International Journal of Construction Management, 18(2), 108–119. https://doi.org/10.1080/15623599.2016.1277058.

    Article  Google Scholar 

  • Sovacool, B. K., Gilbert, A., & Nugent, D. (2014). An international comparative assessment of construction cost overruns for electricity infrastructure. Energy Research & Social Science, 3, 152–160. https://doi.org/10.1016/j.erss.2014.07.016.

    Article  Google Scholar 

  • Suk, S. J., Chi, S., Mulva, S. P., Caldas, C. H., & An, S. H. (2016). Quantifying combination effects of project management practices on cost performance. KSCE Journal of Civil Engineering. https://doi.org/10.1007/s12205-016-0499-0.

    Google Scholar 

  • Wachs, M. (1990). Ethics and advocacy in forecasting for public policy. Business and Professional Ethics Journal, 9(1–2), 141–157.

    Article  Google Scholar 

  • Walker, D. H. T. (1995). An investigation into construction time performance. Construction Management and Economics, 13, 263–274.

    Article  Google Scholar 

  • Zarina, A., Zawawi, E. M. A., Yusof, K., & Aris, N. M. (2014). Determining critical success factors of project management practice: a conceptual framework. In Proceedings of the AMER international conference; 2014 Jan 4–5; Malaysia.

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Correspondence to George Harrison Coffie.

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Coffie, G.H., Aigbavboa, C.O. & Thwala, W.D. Modelling construction completion cost in Ghana public sector building projects. Asian J Civ Eng 20, 1063–1070 (2019). https://doi.org/10.1007/s42107-019-00165-7

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  • DOI: https://doi.org/10.1007/s42107-019-00165-7

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