Modeling Supply Networks: A Structural Analysis of the Toyota Supply Chain

We assemble a large‐scale empirical dataset that allows us to examine the local and global topology of relationships between firms in the Toyota supply network. On this basis we propose novel measures that allow us to characterise the resilience of the entire supply network. Our findings show that simple linear supply chain models are inadequate, because they neglect important lateral dependencies between suppliers. Hence, we argue that it is necessary to describe and model the supply chain as a complex network. We observe that the degree distribution for this network scales exponentially, so that disruptions at randomly chosen suppliers have little impact but vulnerability to disruptions at highly connected suppliers is significant. These potential vulnerabilities are mitigated by the network’s ‘small‐world’ structure, where the average path to any given supplier via other suppliers is very low, and the number of relations between suppliers that produce the same product types is high, especially within the Kyoho‐kai supplier association. Membership of the tightly‐knit Kyoho‐kai supplier association is positively correlated with an increase in the number of connections that a supplier has, leading to a segmentation that favours highly connected hubs. The network also exhibits a high degree of product type redundancy, where multiple suppliers offer similar product types. When we examine product diversity along the chain we find that upper tiers show higher diversification given their vulnerability to changing customer demands. Our analysis of a unique, large‐scale empirical dataset aims to move the field of supply chain management beyond stylised facts, and to demonstrate how methods from interdisciplinary work on complex networks can contribute novel insights.