Perera Supun, Bell Michael G H, Bliemer Michiel C J
Institute of Transport and Logistics (ITLS), University of Sydney Business School, Darlington, NSW 2006 Australia.
Appl Netw Sci. 2017;2(1):33. doi: 10.1007/s41109-017-0053-0. Epub 2017 Oct 10.
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.
由于全球供应链网络（SCNs）日益复杂且相互关联，最近一系列研究已应用网络科学方法来模拟供应链网络的增长，并随后分析各种拓扑特征，如稳健性。本文提供：（1）对文献中用于建模供应链网络拓扑和稳健性的方法进行全面综述；（2）总结各种数据驱动研究中报告的现实世界供应链网络的拓扑特征；以及（3）讨论现有网络增长模型在现实表征供应链网络观察到的拓扑特征方面的局限性。最后，提出了一个新的视角，即通过基于适应性的生成网络模型来模拟实证研究中报告的供应链网络拓扑。
