Abstract
Construction firms face considerable risks that might lead to business bankruptcy. Failed construction companies leave behind unfinished projects, which leads to huge losses to project owners. While previous studies were conducted to understand the factors that contribute to the bankruptcy of construction organizations, little to no research was performed to quantitatively assess the risk of construction business bankruptcy. Hence, this paper addresses this knowledge gap by developing a fuzzy model for predicting the probability of business bankruptcy of construction companies. First, the following six failure warning signs were considered: financial management system, borrowed credit, estimating and job-cost reporting, project management, business plan, and communication. Second, 22 business-related attributes were identified and included in the proposed decision-support tool. Third, fuzzy membership functions and linguistic rules were developed based on expert consultation. Fourth, the Mamdani method was utilized for the inference and composition of the fuzzy linguistic terms. Finally, demonstrative case studies were presented to show the use of the developed fuzzy model and decision support tool. The results compared the risk of business bankruptcy for different scenarios as well as investigated the impacts of different combinations of business warning signs on the probability of bankruptcy. The findings also highlighted the importance of having early warning mechanisms for business management in the construction industry. This paper adds to the body of knowledge by developing a predictive model that helps construction companies forecast the risk of bankruptcy and take the needed corrective actions to avoid business bankruptcy.
Recommended Citation
R. H. Assaad et al., "A Fuzzy Model And Decision-Support Tool For Assessing And Predicting The Probability Of Bankruptcy Of Construction Companies," Computing in Civil Engineering 2023: Visualization, Information Modeling, and Simulation - Selected Papers from the ASCE International Conference on Computing in Civil Engineering 2023, pp. 213 - 220, American Society of Civil Engineers, Jan 2024.
The definitive version is available at https://doi.org/10.1061/9780784485231.026
Department(s)
Civil, Architectural and Environmental Engineering
International Standard Book Number (ISBN)
978-078448523-1
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2024 American Society of Civil Engineers, All rights reserved.
Publication Date
01 Jan 2024
