The neural network model for predicting the financing cost for construction projects

E.M. Elkassas, H.H. Mohamed and H.H. Massoud

International Journal of Project Organisation and Management, 2009, vol. 1, issue 3, 321-334

Abstract: This study introduces the solution of a major problem facing contractors when submitting a tender for a new construction project. This problem is concerned with the estimation of the expected cost of finance and the maximum capital needs for new projects. In this study, the Artificial Neural Network (ANN) technique is used and proposed as a tool for management to better facilitate the prediction of the financing cost and the maximum capital needs for a new construction project. This prediction is valuable particularly at the tendering stage, when little information about the project cash flow and time schedule are known. The predictions of the two values have a great impact on the contractor's profit and affect the contractor's decision to tender. The inaccurate estimation of these two values could lead the project to stop without completion and may lead the contractor to insolvency.

Keywords: finance costs; maximum capital needs; artificial neural networks; ANNs; project cash flow; prediction; construction projects; project management; tendering. (search for similar items in EconPapers)
Date: 2009
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