Profitability Estimation Model of Egyptian Construction Projects Using Artificial Neural Network | ||||
| Engineering Research Journal (Shoubra) | ||||
| Volume 53, Issue 1, January 2024, Page 142-149 PDF (919.55 K) | ||||
| Document Type: Research articles | ||||
| DOI: 10.21608/erjsh.2023.227997.1199 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Alaa Nabil EL-HAZEK 1; Sahar Shahat Ghareeb2; Amr Mohamed Ibrahim  1
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| 1Department of Civil Engineering, Faculty of Engineering at Shoubra Benha University, Egypt. | ||||
| 2Construction and Project Management Research Institute, Housing and Building National Research Center (HBRC) | ||||
| Abstract | ||||
| The profit ratio is important for any construction project. There is a high need to determine the profit ratio in the tendering stage. This paper investigates the factors affecting the determination of the profit ratio in the tendering stage for Egyptian construction projects. The effect of the characteristics of the project, contractor, owner, tender, and external condition on the profit ratio was studied to determine the significant factors affecting the determination of the profit ratio. A questionnaire was designed to determine the importance of 35 factors affecting the profit ratio decision and 267 responses were studied. The results indicated that most companies did not rely on any equations or analyses to determine the profit ratio for construction projects in Egypt. Employing the Relative Importance Index, the most important factors for profit ratio determination were economic stability, cash flow, degree of difficulty, size of the contract, and type of contract. The least important factors for profit ratio determination were delay penalties, safety rules, and the experience of the client. Pareto analysis was employed, and the 35 factors influencing the profit ratio were reduced to 12 significant factors. A second questionnaire was designed to identify the profit ratio for construction projects and responses were studied. An Artificial Neural Network model was developed to determine the profit ratio. Validation tests were conducted using six construction projects in Egypt. The absolute differences between actual and predicted profit ratios ranged between -0.0315% and 0.043%. This model will help to determine the profit ratio easily. | ||||
| Keywords | ||||
| Profit; Markup; Margin size; Tendering; and Artificial Neural Network modeling | ||||
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