Risk-and-resilience-informed framework for schedule contingency estimation in EPC projects
Esam Alhashedi et al.
Abstract
Purpose This study proposes a novel framework for time contingency estimation in engineering, procurement and construction (EPC) projects that accounts for risk interdependencies and project resilience to disruptions, overcoming the limitations of conventional methods. Design/methodology/approach A risk-and-resilience-informed time contingency framework (R2TCF) was developed by integrating a Noisy-MAX Bayesian model (NMBM) for EPC risk propagation with quantitative modeling of project resilience to generate reliable time contingencies. The framework is applied to a case project and validated via scenario analysis under varying risk probabilities, preparedness levels and extreme conditions. Findings The R2TCF estimates time contingencies that reflect the distinct risk and resilience profiles of the EPC phases while capturing intra-phase variability across activities. The contingencies remained responsive and consistent across different risk exposures and preparedness levels, reinforcing the framework's robustness and decision-support utility. Practical implications This study equips EPC contractors with a practical time contingency forecasting tool by simulating the realistic interplay of EPC risks and resilience capacities across project phases, thereby enhancing schedule reliability, resource allocation and proactive uncertainty management. Originality/value This research introduces a novel framework that advances contingency planning by integrating risk propagation and resilience dynamics for realistic time contingency estimation. It offers new insights into resilience-informed decision-making in EPC projects from the general contractor's perspective.
Evidence weight
Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40
| F · citation impact | 0.50 × 0.4 = 0.20 |
| M · momentum | 0.50 × 0.15 = 0.07 |
| V · venue signal | 0.50 × 0.05 = 0.03 |
| R · text relevance † | 0.50 × 0.4 = 0.20 |
† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.