Badawy, M., Alqahtani, F. and Hafez, H. orcid.org/0009-0004-8917-680X (2022) Identifying the risk factors affecting the overall cost risk in residential projects at the early stage. Ain Shams Engineering Journal, 13 (2). 101586. ISSN: 2090-4479
Abstract
Many previous studies have developed models for estimating the total cost, whether in the planning stage or the early stage of the project. However, models for estimating the overall risk were proposed in the planning stage only. This paper identifies the factors affecting the overall risk in residential projects at the early stage. The 43 risk factors at the planning stage were identified using a Delphi technique. Experts summarize the 43 risk factors into four factors that can be used to predict the overall risk in the early stage of the project. A multilayer perceptron model with one hidden layer was proposed. The mean absolute error rate for the proposed model was 10%. Risk factors can be used to develop a model to predict the impact of overall risk on project cost at the early stage. The developed model helps stakeholders decide whether the project should continue or be terminated.
Metadata
| Item Type: | Article |
|---|---|
| Authors/Creators: |
|
| Copyright, Publisher and Additional Information: | © 2021 the author. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY-NC-ND 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
| Keywords: | Overall risk; Artificial Neural Network (ANN); Residential projects; Multilayer perceptron; Data mining |
| Dates: |
|
| Institution: | The University of Leeds |
| Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Civil Engineering (Leeds) |
| Date Deposited: | 11 Dec 2025 12:22 |
| Last Modified: | 11 Dec 2025 12:22 |
| Status: | Published |
| Publisher: | Elsevier |
| Identification Number: | 10.1016/j.asej.2021.09.013 |
| Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:235334 |
Download
Filename: 1-s2.0-S2090447921003518-main.pdf
Licence: CC-BY-NC-ND 4.0

CORE (COnnecting REpositories)
CORE (COnnecting REpositories)