Complexity and Emergence in Supply Networks


The Global Automotive Industry


We study Supply Networks by taking a Complex Systems lens, recognising their emergent nature. In fact, the very beginning of our lab was motivated by this emergent context which led to the data-driven perspective we take today.


Initial studies on the  large-scale  structures on the automotive and aerospace industries were a first in literature which led to an understanding of universal patterns that govern supply chains. For example, we discovered the existence of scale-free, modular and nested patterns, yielding an understanding of systemic risk, and system vulnerability to disruption cascades. Such insights were later applied to detect critical firms, whose failure might impact the economy, and more recently financial risk propagation, and even transport delay propagations. We can also use insights gained from complex systems analysis to increase resilience to disruptions by reconfiguring network topologypredict hidden dependencies in the network, such as supply-buy relationships we might not be aware of. To do so, we use a multifaceted combination of tools and methods, including network science, agent based modelling and machine learning. 


Currently we are working towards applying these insights to understand potential risk cascades in sectors ranging from Critical Minerals, to Food and Maritime industry. 


Our previous and current sponsors and collaborators in this theme include: Aviva, Procter and Gamble, Jaguar Land Rover, Boeing, Innovate UK and the EPSRC.


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