Probabilistic Cash Flow Analysis Considering Risk Impacts by Integrating 5D-Building Information Modeling and Bayesian Belief Network
Abstract
1. Introduction
Research Significance and Identified Gaps
- Contribution 1: The study is the first to combine 5D-BIM with a BBN for cash flow prediction. This can provide an efficient approach that automates the cash flow calculations while considering the complex impact of inter-related risk factors.
- Contribution 2: The proposed approach will also address three significant challenges associated with traditional BBN methods, including the following:
- ○
- The inability to consider uncertainty and vagueness in experts’ opinions:One significant challenge in using BBNs is relying on professionals’ expertise and subjective judgment because of the scarcity of objective project-specific data for risk assessment during the project’s initial phase [36]. However, such judgment-based assessment is often biased, inconsistent, and imprecise [37]. To address the challenge, this research integrates fuzzy logic into the BBN to handle the vagueness or uncertainty in expert’s opinions when limited information is available. A hybrid approach combining fuzzy theory and a BBN has been widely employed in risk management research, yielding robust outcomes and gaining substantial attention from scholars [27,38,39].
- ○
- Failure to provide a suitable systematic method to determine the BBN structure:Another challenge in using a BBN is confirming the BBN structure with reality and project complexities [40]. To overcome this challenge, the Fuzzy DEMATEL-ISM method will be used to form the structure of the BBN.
- ○
- A lack of ability to reduce the elicitation workload to complete the parametric component of the BBN:
2. Materials and Methods
2.1. Cash Flow Analysis Using 5D-BIM
2.1.1. Preparation of 5D-BIM
2.1.2. Cash Flow Analysis
2.2. Risk Assessment Using BBN
2.2.1. Risk Identification
2.2.2. Risk Network Development
2.2.3. Risk Analysis Using BBN
2.3. Integrating 5D-BIM and BBN Models
2.4. Source of Expert and Information
3. Results
3.1. Cash Flow Analysis Using 5D-BIM for the Case Study Project
3.1.1. Preparation of 5D-BIM for the Mass Housing Project
3.1.2. Cash Flow Analysis for the Mass Housing Project
3.2. Risk Assessment Using a BBN for the Case Study Project
3.2.1. Risk Identification Results
3.2.2. Risk Network Development Result
3.2.3. Risk Analysis Results Using BBN
3.3. Result of Integrating 5D-BIM and BBN Models
Scenario Analysis
4. Discussion
5. Conclusions
- Presenting an integrated 5D-BIM and BBN approach for probabilistic cash flow forecasting;
- Improving reliability by using fuzzy logic to deal with expert opinion uncertainty;
- Overcoming the shortcomings of classical BBNs by introducing a hybrid fuzzy DEMATEL-ISM approach to systematically define the network structure and using the RNM method to reduce the parameter elicitation workload.
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
Abbreviations
BIM | Building information modeling |
BBN | Bayesian Belief Network |
RNM | Ranked Node Method |
DEMATEL | Decision-making trial and evaluation laboratory |
ISM | Interpretive structural modeling |
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Experts | Age | Work Experience | Degree | Job Title |
---|---|---|---|---|
01 | 73 | 42 years | M.S/Civil Engineering | Project manager |
02 | 63 | 30 years | B.S/Civil Engineering | Head of the technical office |
03 | 55 | 22 years | B.S/Civil Engineering | Site manager |
04 | 49 | 18 years | B.S/Civil Engineering | Deputy site manager |
05 | 53 | 21 years | B.S/Civil Engineering | Deputy site manager |
Risk Classification | Risk Factors | Codes |
---|---|---|
Risks associated with owner | Specification variations during building | O1 |
Delays in approvals | O2 | |
Owner’s managerial deficiency | O3 | |
Risks associated with contractor | Insufficient expertise and experience | C1 |
Delay in procurement | C2 | |
Contractor’s managerial deficiency | C3 | |
Inadequate site safety management | C4 | |
Poor workmanship | C5 | |
Poor planning and scheduling | C6 | |
Financial risks | Inflation | F1 |
Client’s payment delay | F2 | |
Financial insufficiency of the contractor | F3 | |
Management risks | Inadequate communication of project stakeholders | M1 |
Conflict among project stakeholders | M2 | |
Procurement risks | Insufficient supplies of materials and equipment | P1 |
Public conditions risks | Complexity of the project | PU1 |
Risks associated with consultant | Insufficient expertise and experience, as well as managerial shortcomings | CO1 |
Design mistakes | CO2 | |
Delay in design delivery | CO3 | |
Modifying the specs of materials and equipment throughout the building process | CO4 | |
Country conditions risks | Economic volatility | G1 |
Non-economic instabilities | G2 | |
Legal systems’ immaturity and weak bureaucracy | G3 | |
Environmental conditions risks | Bad weather condition | E1 |
Force majeure | E2 | |
Risks imposed by environmental regulations | E3 | |
Operational risks | Corruption and fraud | OP1 |
Defects in construction method | OP2 | |
Damage incurred to the contractor’s equipment and tools | OP3 | |
Rework | OP4 | |
Not adhering to the job orders and delay in completing the predecessors | OP5 |
Linguistic Terms | Triangular Fuzzy Numbers |
---|---|
Very high influence | (0.75, 1, 1) |
High influence | (0.5, 0.75, 0.1) |
Medium influence | (0.25, 0.5, 0.75) |
Low influence | (0, 0.25, 0.5) |
No influence | (0, 0, 0.25) |
Level | 1st | 2nd | 3rd | 4th | 5th | 6th | 7th | 8th | 9th | 10th |
---|---|---|---|---|---|---|---|---|---|---|
Risk factors | G1 | F1 | C1; G3; F2 | F3; CO1; C3 | G2; O3 | P1; M1; O2; OP1; O1; | C2; C6; M2; PU1 | E2; OP2 | CO2; OP3 | C4; E3; C5; OP4 CO3; CO4; OP5; E1 |
State | Cost Over-Run Magnitude (Percentage) |
---|---|
Low | 0–15% |
Medium | 15–40% |
High | 40–100% |
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Madihi, M.H.; Tafazzoli, M.; Shirzadi Javid, A.A.; Nasirzadeh, F. Probabilistic Cash Flow Analysis Considering Risk Impacts by Integrating 5D-Building Information Modeling and Bayesian Belief Network. Buildings 2025, 15, 1774. https://doi.org/10.3390/buildings15111774
Madihi MH, Tafazzoli M, Shirzadi Javid AA, Nasirzadeh F. Probabilistic Cash Flow Analysis Considering Risk Impacts by Integrating 5D-Building Information Modeling and Bayesian Belief Network. Buildings. 2025; 15(11):1774. https://doi.org/10.3390/buildings15111774
Chicago/Turabian StyleMadihi, Mohammad Hosein, Mohammadsoroush Tafazzoli, Ali Akbar Shirzadi Javid, and Farnad Nasirzadeh. 2025. "Probabilistic Cash Flow Analysis Considering Risk Impacts by Integrating 5D-Building Information Modeling and Bayesian Belief Network" Buildings 15, no. 11: 1774. https://doi.org/10.3390/buildings15111774
APA StyleMadihi, M. H., Tafazzoli, M., Shirzadi Javid, A. A., & Nasirzadeh, F. (2025). Probabilistic Cash Flow Analysis Considering Risk Impacts by Integrating 5D-Building Information Modeling and Bayesian Belief Network. Buildings, 15(11), 1774. https://doi.org/10.3390/buildings15111774