Open Access

Gilbert Fridgen, Christian Stepanek, Thomas Wolf

• Almost all major companies are embedded in complex, global supply networks, consisting of multiple nested supply chains, and building up a high level of complexity. Exogenous shocks on these networks (e.g. natural disasters) can directly and indirectly impact companies and even cause their entire supply network to fail. However, today it is extremely difficult for a company to predict the actual impact of an exogenous shock on its supply network. Hence, companies are not able to identify adequate counteractive measures. Therefore safeguarding measures are oftentimes insufficient or even counterproductive. This paper deals with modelling, analyzing and quantifying impacts of exogenous shocks on supply networks using Petri Nets. It provides means to simulate the vulnerability of different network constellations regarding exogenous influences. In order to evaluate the proposed method, we simulate different intensities of an exogenous shock delaying the delivery for an exemplary supplyAlmost all major companies are embedded in complex, global supply networks, consisting of multiple nested supply chains, and building up a high level of complexity. Exogenous shocks on these networks (e.g. natural disasters) can directly and indirectly impact companies and even cause their entire supply network to fail. However, today it is extremely difficult for a company to predict the actual impact of an exogenous shock on its supply network. Hence, companies are not able to identify adequate counteractive measures. Therefore safeguarding measures are oftentimes insufficient or even counterproductive. This paper deals with modelling, analyzing and quantifying impacts of exogenous shocks on supply networks using Petri Nets. It provides means to simulate the vulnerability of different network constellations regarding exogenous influences. In order to evaluate the proposed method, we simulate different intensities of an exogenous shock delaying the delivery for an exemplary supply network. We thereby illustrate which results could be yielded from a real-world application. For our exemplary network we find that the marginal effect of a disruption declines with an increasing intensity of shock. Moreover, the impact of shocks can be mitigated by appropriate counteractive measures like in this example by an increased safety margin of stock.…