Risk is endemic in construction projects and previous studies suggest that variability between contract sum and final account was as a result of risk occurring during the project‘s life. This study uses the risk theory to uncover the significant risk variables thought to impact the construction phase with attendant impact on the out turn cost of construction projects. The significant risk variables were then used to develop models for assessing risk impacts on the variability between contract sum and final account. A two-stage approach was adopted in data collection. The first was an online questionnaire survey of risk factors thought to impact the variability between contract sum and final account. A ranking of the mean score of the survey responses enabled the significant risk factors to be determined. The second stage of the data collection involved collection of data regarding contract sum and final account from recently completed projects. Quantity Surveyors whoworked on the projects were then requested to score the extent of occurrence of the dentified significant risk factors on a Likert-type scale. The pair of data set obtained was then used to model risk impacts on the variability between contract sum and final account using artificial neural network modelling method. The result obtained was promising and the developed models could help the construction contractor to predict the likely impacts of risk occurring at project execution phase on out turn construction cost.Keywords: artificial neural network, contract sum, final account, risk variables, risk modelling
|Title of host publication||COBRA 2011: Proceedings of the RICS Foundation Construction and Property Research Conference|
|Place of Publication||Salford|
|Publisher||Royal Institution of Chartered Surveyors|
|ISBN (Print)||ISBN: 978-1-907842-19-1|
|Publication status||Published (in print/issue) - 12 Sept 2011|
Bibliographical noteReference text: Akintoye, A. and MacLeod, M. (1997) Risk analysis and management in construction, International Journal of Project Management, Vol. 15, No. 1, pp. 31-38
Asworth, A. (1994) Cost Studies of Buildings. Essex. Longman Group Limited.
Baloi, B and Price, A. (2001) Modelling global risk factors affecting construction cost performance, International Journal of Project Management, Vol. 21, Issue 4, pp 261–269
Barnes, M (1990) Financial Control, Engineering Management Series. Thomas Telford.
Bennet, F.R. (2003) The Management of Construction: A Project Life Cycle Approach. Butterworth Heinemann.
Chapman, R (2001) The controlling influences on effective risk identification and assessment for construction design management, International Journal of Project Management Vol. 19, pp 147-160
Cooke, B and Williams, P. (2009). Construction Planning, Programming and Control. Third Edition. Wiley –Blackwell.
Flanagan, R. and Norman, G. (1993) Risk Management and Construction. Blackwell Science, London.
Flanagan, R. and Tate, B. (1997): Cost Control in Building Design. Oxford, Blackwell Science Ltd.
Harper, W.M. (1976) Management Accounting. M and E Handboooks, McDonald and Evans.
Heale, J R. (1982) 'Contingency funds evaluation' Transaction of American Association of Cost Engineers B3.1-B3.4
Joint Contracts Tribunal (2005) Standard Building Contract with Quantities, The Joint Contracts Tribunal Ltd, London.
Mason, G. (1973) A Quantitative Risk Management Approach to the Selection of a Construction Contract Provisions. Ph.D. Thesis, Department of Civil Engineering, Stanford University.
Morris PWG, Hough GH. (1991). The anatomy of major projects: a study of the reality of project management. Chichester, UK: Wiley.
Moavenzadeh, F and Rossow, J. (1976) 'Risks and risk analysis in construction management' Proceedings of the C1B W65, Symposium on Organisation and Management of Construction, US National Academy of Science, Washington DC, USA, 19-20.
Oberlender, G.D. (1993) Project Management for Engineering and Construction. McGraw-Hill.
Odeyinka, H.A. (2007) Modelling risk impacts on the budgeted cost of traditionally procured
building projects. Proceedings of The 23rd Annual ARCOM Conference, Belfast, pp 755-763
Odeyinka, H.A., Kelly, S. and Perera S. (2009). An Evaluation of the Budgetary Reliability of Bills of Quantities in Building Procurement. The construction and building research conference of the Royal Institution of Chartered Surveyors held at the University of Cape Town, pp 435-446.
Pilcher, R. (1992) Project Cost Control in Construction Projects, Second Edition. Oxford. Blackwell Scientific Publications.
Potts, K. (2008) Construction Cost Management, learning from case studies. Taylor & Francis
Project Management Institute (2008) A Guide to the Project Management Body of Knowledge, 4th Edition. Project Management Institute, Pennsylvania.
Smith, N.J. (1999) Managing Risk in Construction Projects. Blackwell Science
Wideman R.M. (1986) Risk Management. Project Management Journal, Vol. 17, no. 4, pp 20-6.
Winch G.M. (2010) Managing Construction Projects, 2nd Edition. Oxford, Blackwell Publishing.
- artificial neural network
- contract sum
- final account
- risk variables
- risk modelling