A novel model based on Extended Monte Carlo simulation for investigating the effect of co-occurrence of risks considering utility function
Risk assessment is a part of risk management. There are different techniques for risk assessment. Monte Carlo simulation (MCS) is one of the quantitative methods for risk assessment. Extended MCS tried to solve the weakness of classic Monte Carlo simulation through using rotary algorithm. But in the real world, projects face with different risks simultaneously. Co-occurrence of risks cause to exacerbates or diminishes the effects of each other. In this paper, the effect of occurrence of other risks on one risk in each iteration is investigated and finally the utility function is calculated by considering co-occurrence of risks and rotary algorithm. The proposed model tested on petrochemical construction project data. In this project, six risks such as inflation rate, labour, temperature, rain, cost and time are identified through experts’ opinion. The results show that the utility function become closer to reality by considering the co-occurrence of risks.
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Coupling failure analysis using condition monitoring data with machine learning approach
Reza Sadeghi,
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The Relationship Between Information Technology Governance and Organizational Agility in The Digital Transformation Maturity,Case Study: Iranian Tax Administration Organization
Maryam Bayat, Alireza Hassanzadeh *, Ali Shayan,
Quarterly Journal of Management of Governmental Organizations,