Perera, SupunSupunPereraBell, Michael GHMichael GHBellBliemer, Michiel CJMichiel CJBliemer2019-08-232019-08-232017-10-10Applied Network Science, 2017, 2 (33), pp.1-252364-8228http://hdl.handle.net/10044/1/72868Due 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.© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.Journal Articlehttps://www.dx.doi.org/10.1007/s41109-017-0053-0https://appliednetsci.springeropen.com/articles/10.1007/s41109-017-0053-0