Topological Structure of Manufacturing Industry Supply Chain Networks

TY - JOUR

T1 - Topological Structure of Manufacturing Industry Supply Chain Networks

AU - Parhi, Mamata

AU - Perera, Supun

AU - Piraveenan, Mahendrarajah

AU - Kasthurirathna, Dharshana

PY - 2018/10/3

Y1 - 2018/10/3

N2 - Empirical analyses of supply chain networks (SCNs) in extant literature have been rare due to scarcity of data. As a result, theoretical research have relied on arbitrary growth models to generate network topologies supposedly representative of real world SCNs. Our study aims to fill the above gap by systematically analysing a set of manufacturing sector SCNs to establish their topological characteristics. In particular, we compare the differences in topologies of undirected contractual relationships (UCR) and directed material flow (DMF) SCNs. The DMF SCNs are different from the typical UCR SCNs since they are characterised by a strictly tiered and an acyclic structure which doesn’t permit clustering. Additionally, we investigate the SCNs for any self-organized topological features. We find that most SCNs indicate disassortative mixing and power law distribution in terms of inter-firm connections. Furthermore, compared to randomised ensembles, self-organized topological features were evident in some SCNs in the form of either over-represented regimes of moderate betweenness firms or under-represented regimes of low betweenness firms. Finally, we introduce a simple and intuitive method for estimating the robustness of DMF SCNs, considering the loss of demand due to firm disruptions. Our work could be used as a benchmark for any future analyses of SCNs.© 2018, The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/

AB - Empirical analyses of supply chain networks (SCNs) in extant literature have been rare due to scarcity of data. As a result, theoretical research have relied on arbitrary growth models to generate network topologies supposedly representative of real world SCNs. Our study aims to fill the above gap by systematically analysing a set of manufacturing sector SCNs to establish their topological characteristics. In particular, we compare the differences in topologies of undirected contractual relationships (UCR) and directed material flow (DMF) SCNs. The DMF SCNs are different from the typical UCR SCNs since they are characterised by a strictly tiered and an acyclic structure which doesn’t permit clustering. Additionally, we investigate the SCNs for any self-organized topological features. We find that most SCNs indicate disassortative mixing and power law distribution in terms of inter-firm connections. Furthermore, compared to randomised ensembles, self-organized topological features were evident in some SCNs in the form of either over-represented regimes of moderate betweenness firms or under-represented regimes of low betweenness firms. Finally, we introduce a simple and intuitive method for estimating the robustness of DMF SCNs, considering the loss of demand due to firm disruptions. Our work could be used as a benchmark for any future analyses of SCNs.© 2018, The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/

U2 - 10.1155/2018/3924361

DO - 10.1155/2018/3924361

M3 - Article

SN - 1099-0526

JO - Complexity

JF - Complexity

ER -