Network Science Approach to Modelling the Topology and Robustness of Supply Chain Networks: a Review and Perspective

Overview

Journal Appl Netw Sci

Date 2018 Nov 17

PMID 30443587

Citations 6

Authors

Supun Perera

Michael G H Bell

Michiel C J Bliemer

Affiliations

Soon will be listed here.

Abstract

Due to the increasingly complex and interconnected nature of global supply chain networks (SCNs), a recent strand of research has applied network science methods to model SCN growth and subsequently analyse various topological features, such as robustness. This paper provides: (1) a comprehensive review of the methodologies adopted in literature for modelling the topology and robustness of SCNs; (2) a summary of topological features of the real world SCNs, as reported in various data driven studies; and (3) a discussion on the limitations of existing network growth models to realistically represent the observed topological characteristics of SCNs. Finally, a novel perspective is proposed to mimic the SCN topologies reported in empirical studies, through fitness based generative network models.

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