Risk measurement in the global supply chain using monte-carlo simulation

Nowadays, logistics and supply chain management (SCM) is critical to compete in the current turbulent markets. In addition, in the global context, there are many uncertainties which affect on the market. One of the most important risks is supplier disruption. The first step to cope with these uncertainties is quantifying them. In this regard many researches have focused on the problem but measurement of the risk in the global SCM is yet a challenge. In the uncertain conditions, simulation is a good tool to study the system. This paper aims to study a global supply chain with related risks and measurement of the risks using simulation. Global aspects considered in the paper are: 1- currency exchange rate, 2- extended leadtime for abroad supplies, 3- regional and local uncertainties. In this regard, two popular risk measurement approaches (VaR and CVaR) are used in the simulation of uncertainties in the global supply chain. Results showed that adopting risk averse behavior to cope with the uncertainties leads to the lower stockouts and also higher costs.