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Adams, F K (2006) Expert elicitation and Bayesian analysis of construction contract risks: an investigation. Construction Management and Economics, 24(01), 81-96.
Aibinu, A A (2006) The relationship between distribution of control, fairness and potential for dispute in the claims handling process. Construction Management and Economics, 24(01), 45-54.
Andi (2006) The importance and allocation of risks in Indonesian construction projects. Construction Management and Economics, 24(01), 69-80.
Arif, M, Al Zubi, M, Gupta, A D, Egbu, C, Walton, R O and Islam, R (2017) Knowledge sharing maturity model for Jordanian construction sector. Engineering, Construction and Architectural Management, 24(01), 170-88.
Asiedu, R O, Frempong, N K and Alfen, H W (2017) Predicting likelihood of cost overrun in educational projects. Engineering, Construction and Architectural Management, 24(01), 21-39.
- Type: Journal Article
- Keywords: cost overruns; model; educational projects; ghanaian construction industry; multi linear regression; predictive variables
- ISBN/ISSN:
- URL: https://doi.org/10.1108/ECAM-06-2015-0103
- Abstract:
Purpose Being able to predict the likelihood of a project to overrun its cost before the contract signing phase is crucial in developing the required mitigating measures to avert it. Known parameters that permit the timely prediction of cost overrun provide the basis for such predictions. Therefore, the purpose of this paper is to develop a model for forecasting cost overruns. Design/methodology/approach Ten predictive variables known before the contract signing phase of a project are identified. Based on a survey approach, information on 321 educational projects completed are compiled. A multiple linear regression analysis is adopted for the model development. Findings Five variables - initial contract sum, gross floor area, number of storeys, source of funds and contractors’ financial classification are observed to influence cost overruns. The model, however, yields a fairly weak coefficient of determination with a mean absolute percentage error of 30.22 and 138 per cent, respectively. Research limitations/implications The model developed focussed on data only educational projects sampled from three out of the ten administration regions in Ghana based on a purposive sampling approach. Practical implications Policy makers and construction managers working on public projects stand to gain tremendous assistance in formulating and strengthening their own in-house cost forecasting at the precontract phase based on “what if” analysis to generate various alternative predictions of cost overruns. Originality/value Considering the innate nature of cost overruns within the Ghanaian construction industry often resulting to project abandonment, this research presents a unique dimension for tackling cost overruns based on a predictive approach.
Assaf, S A and Barhamain, S Y (1996) Factors affecting construction practices in Makkah Al-Mukkaramah, Saudi Arabia. Building Research & Information, 24(01), 27–30.
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Dann, N, Hills, S and Worthing, D (2006) Assessing how organizations approach the maintenance management of listed buildings. Construction Management and Economics, 24(01), 97-104.
Davies, K, McMeel, D J and Wilkinson, S (2017) Making friends with Frankenstein: Hybrid practice in BIM. Engineering, Construction and Architectural Management, 24(01), 78-93.
Dawood, N and Sriprasert, E (2006) Construction scheduling using multi-constraint and genetic algorithms approach. Construction Management and Economics, 24(01), 19-30.
De Silva, G, Perera, B and Rodrigo, M (2019) Adaptive reuse of buildings: the case of Sri Lanka. Journal of Financial Management of Property and Construction, 24(01), 79–96.
Enshassi, A (1996) Materials control and waste on building sites. Building Research & Information, 24(01), 31–4.
Friedman, A and Cammalleri, V (1996) The impact of R-2000 building technology on Canadian housing. Building Research & Information, 24(01), 5–13.
Huang, Y C (2006) Graphical-based multistage scheduling method for RC buildings. Construction Management and Economics, 24(01), 5-18.
K.V., P, V., V, R., V and Bhat, N (2019) Analysis of causes of delay in Indian construction projects and mitigation measures. Journal of Financial Management of Property and Construction, 24(01), 58–78.
Kärnä, S and Junnonen, J-M (2017) Designers’ performance evaluation in construction projects. Engineering, Construction and Architectural Management, 24(01), 154-69.
Kalutara, P, Zhang, G, Setunge, S and Wakefield, R (2017) Factors that influence Australian community buildings’ sustainable management. Engineering, Construction and Architectural Management, 24(01), 94-117.
Leung, M-Y, Liu, A M M and Wong, M M-k (2006) Impact of stress-coping behaviour on estimation performance. Construction Management and Economics, 24(01), 55-67.
Lu, W, Hua, Y and Zhang, S (2017) Logistic regression analysis for factors influencing cost performance of design-bid-build and design-build projects. Engineering, Construction and Architectural Management, 24(01), 118-32.
Lu, W, Li, Z and Wang, S (2017) The role of justice for cooperation and contract’s moderating effect in construction dispute negotiation. Engineering, Construction and Architectural Management, 24(01), 133-53.
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Velho Júnior, V E, Costa Melo, I, Alves Junior, P N and Rebelatto, D A d N (2019) Analysis of real estate management of lease service agreements by the public sector of a Latin American metropolis. Journal of Financial Management of Property and Construction , 24(01), 97–122.
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