Resilence of complex supply networks - Ledwoch, Anna (Cranfield University, 2017)
During recent decades supply chains have grown, and became increasingly interconnected due to globalisation and outsourcing. Empirical and theoretical studies now characterise supply chains as complex networks rather than the hierarchical, linear chain structures often theorised in classical literature. Increased topological complexity resulted in an increased exposure to risk, however existing supply chain risk management methodologies are designed based on the linear structure assumption rather than interdependent network structures. There is a growing need to better understand the complexities of supply networks, and how to identify, measure and mitigate risks more efficiently. The aim of this thesis is to identify how supply network topology influences resilience. More specifically, how applying well-established supply chain risk management strategies can decrease disruption impact in different supply network topologies. The influence of supply network topology on resilience is captured using a dynamic agent-based model based on empirical and theoretical supply network structures, without a single entity controlling the whole system where each supplier is an independent decision-maker. These suppliers are then disrupted using various disruption scenarios. Suppliers in the network then apply inventory mitigation and contingent rerouting to decrease impact of disruptions on the rest of the network. To the best of author’s knowledge, this is the first time the impact of random disruptions and its reduction through risk management strategies in different supply network topologies have been assessed in a fully dynamic, interconnected environment. The main lessons from this work are as follows: It has been observed that the supply network topology plays a crucial role in reducing impact of disruptions. Some supply network topologies are more resilient to random disruptions as they better fulfil customer demand under perturbations. Under random disruptions, inventory mitigation is a well-performing shock absorption mechanism. Contingent rerouting, on the other hand, is a strategy that needs specific conditions to work well. Firstly, the strategy must be applied by companies in supply topologies where the majority of supply chain members have alternative suppliers. Secondly, contingent rerouting is only efficient in cases when the reaction time to supplier’s disruption is shorter than the duration of the disruption. It has also been observed that the topological position of the individual company who applies specific risk management strategy heavily impacts costs and fill-rates of the overall system. This property is moderated by other variables such as disruption duration, disruption frequency and the chosen risk management strategy. An additional, important lesson here is that, choosing the supplier that suffered the most from disruptions or have specific topological position in a network to apply a risk management strategy might not always decrease the costs incurred by the whole system. In contrast, it might increase it if not applied appropriately. This thesis underpins the significance of topology in supply network resilience. The results from this work are foundational to the claim that it is possible to design an extended supply network that will be able reduce the impact of certain disruption types. However, the design must consider topological properties as well as moderating variables.
Keywords: complexity; supply network topology; supply chain risk management; resilience agent-based modeling