Abstract:
Recent developments in the area of network
science has encouraged researchers to adopt a topological
perspective in modelling Supply Chain Networks (SCNs). While
topological models can provide macro level insights into the
properties of SCN systems, the lack of specificity due to high level
of abstraction in these models limit their real-world applicability,
especially in relation to assessing the impact on SCNs arising due
to individual firm or supply channel level disruptions. In
particular, beyond the topological structure, a more
comprehensive method should also incorporate the heterogeneity
of various components (i.e. firms and inter-firm links) which
together form the SCN. To fill the above gap, this work proposes
using the idea of absorbing Markov chains to model disruption
impacts on SCNs. Since this method does not require path
enumeration to identify the number of supply chains which form
the SCN, it is deemed more efficient compared to the other
traditional methods.
