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This study presents a risk-perception-based contingency management framework (CMF) aimed at improving project risk management (PRM) by integrating structured decision-making with data-driven analysis. The CMF utilizes the Monte Carlo method to optimize contingency reserves and guide risk responses, thereby addressing both short- and long-term cost overruns in projects. The framework is validated through simulation on various project configurations, demonstrating its applicability and effectiveness in enhanc
- Author
- mertsenol1612
- Language
- EN