Analyzing Contingency Estimation for Residential Turnkey Projects in Saudi Arabia: A Neural Network Approach

• Published in: Buildings (Basel) Vol. 14; no. 6; p. 1844
• Main Author: Salman, Alaa
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.06.2024
• Subjects: @Risk 7.5; artificial neural network (ANN); Artificial neural networks; Comparative analysis; Complexity; Concrete; Construction industry; Contingency; Contingency planning; Contractors; Cost analysis; Cost estimates; Decision making; Estimation; Expenditures; Life cycle assessment; Life cycles; Neural networks; NeuralTools 7.5; Project engineering; project life cycle; Reinforced concrete; Residential areas; Residential buildings; Risk management; turnkey; Turnkey contracts; Saudi Arabia
• ISSN: 2075-5309; 2075-5309
• DOI: 10.3390/buildings14061844

Utilizing a turnkey approach to deliver a construction project entails significant risks from the contractor’s perspective. Essentially, the owner awaits project completion without commitments regarding additional expenditures incurred by the contractor during the project’s duration. This paper specifically focuses on estimating and analyzing the contingency value for residential turnkey projects in Saudi Arabia. The contingency value across the project’s life cycle is estimated using six Artificial Neural Network (ANN) models, which are compared to identify the best-trained network according to project complexity, contingency factor, and contingency impact during the project phases. The output layer provides the contingency factor percentages for each project phase. A 13-story reinforced concrete (RC) residential building established in one of Saudi Arabia’s cities was selected to implement the developed methodology. The contingency estimation, performed using @Risk 7.5 and NeuralTools 7.5, was determined to be 11.34% and was distributed across the five phases of the project’s life cycle: 0.30% for predesign, 0.99% for design, 2.61% for preconstruction, 6.33% for construction, and 1.12% for postconstruction. Furthermore, it was found that the estimated contingency varies based on project complexity, which is 7.20% for low complexity, 8.16% for medium complexity, 9.41% for complicated, and 11.34% for very complicated projects. Historical data and peer review approaches are employed to validate the results, both of which are endorsed by professionals in this field. This paper highlights two main contributions: Firstly, it significantly enhances risk management by facilitating a comprehensive understanding and systematic analysis of risks, thus improving the contractors’ ability to mitigate potential negative impacts on projects. Secondly, it supports more informed decision-making through the use of advanced techniques to estimate and analyze contingency values. These contributions are critical for contractors engaged in Saudi construction projects, particularly those involving residential buildings.