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Testing “efficient supply chain propositions” using topological characterization of the global supply chain network

In this paper, we study the topological properties of the global supply chain network in terms of its degree distribution, clustering coefficient, degree-degree correlation, bow-tie structure, and community structure to test the efficient supply chain propositions proposed by E. J.S. Hearnshaw et al...

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Autores principales: Chakraborty, Abhijit, Ikeda, Yuichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529254/
https://www.ncbi.nlm.nih.gov/pubmed/33002029
http://dx.doi.org/10.1371/journal.pone.0239669
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author Chakraborty, Abhijit
Ikeda, Yuichi
author_facet Chakraborty, Abhijit
Ikeda, Yuichi
author_sort Chakraborty, Abhijit
collection PubMed
description In this paper, we study the topological properties of the global supply chain network in terms of its degree distribution, clustering coefficient, degree-degree correlation, bow-tie structure, and community structure to test the efficient supply chain propositions proposed by E. J.S. Hearnshaw et al. The global supply chain data in the year 2017 are constructed by collecting various company data from the web site of Standard & Poor’s Capital IQ platform. The in- and out-degree distributions are characterized by a power law of the form of γ(in) = 2.42 and γ(out) = 2.11. The clustering coefficient decays [Image: see text] with an exponent β(k) = 0.46. The nodal degree-degree correlations 〈k(nn)(k)〉 indicates the absence of assortativity. The bow-tie structure of giant weakly connected component (GWCC) reveals that the OUT component is the largest and consists 41.1% of all firms. The giant strong connected component (GSCC) is comprised of 16.4% of all firms. We observe that upstream or downstream firms are located a few steps away from the GSCC. Furthermore, we uncover the community structures of the network and characterize them according to their location and industry classification. We observe that the largest community consists of the consumer discretionary sector based mainly in the United States (US). These firms belong to the OUT component in the bow-tie structure of the global supply chain network. Finally, we confirm the validity of Hearnshaw et al.’s efficient supply chain propositions, namely Proposition S1 (short path length), Proposition S2 (power-law degree distribution), Proposition S3 (high clustering coefficient), Proposition S4 (“fit-gets-richer” growth mechanism), Proposition S5 (truncation of power-law degree distribution), and Proposition S7 (community structure with overlapping boundaries) regarding the global supply chain network. While the original propositions S1 just mentioned a short path length, we found the short path from the GSCC to IN and OUT by analyzing the bow-tie structure. Therefore, the short path length in the bow-tie structure is a conceptual addition to the original propositions of Hearnshaw.
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spelling pubmed-75292542020-10-02 Testing “efficient supply chain propositions” using topological characterization of the global supply chain network Chakraborty, Abhijit Ikeda, Yuichi PLoS One Research Article In this paper, we study the topological properties of the global supply chain network in terms of its degree distribution, clustering coefficient, degree-degree correlation, bow-tie structure, and community structure to test the efficient supply chain propositions proposed by E. J.S. Hearnshaw et al. The global supply chain data in the year 2017 are constructed by collecting various company data from the web site of Standard & Poor’s Capital IQ platform. The in- and out-degree distributions are characterized by a power law of the form of γ(in) = 2.42 and γ(out) = 2.11. The clustering coefficient decays [Image: see text] with an exponent β(k) = 0.46. The nodal degree-degree correlations 〈k(nn)(k)〉 indicates the absence of assortativity. The bow-tie structure of giant weakly connected component (GWCC) reveals that the OUT component is the largest and consists 41.1% of all firms. The giant strong connected component (GSCC) is comprised of 16.4% of all firms. We observe that upstream or downstream firms are located a few steps away from the GSCC. Furthermore, we uncover the community structures of the network and characterize them according to their location and industry classification. We observe that the largest community consists of the consumer discretionary sector based mainly in the United States (US). These firms belong to the OUT component in the bow-tie structure of the global supply chain network. Finally, we confirm the validity of Hearnshaw et al.’s efficient supply chain propositions, namely Proposition S1 (short path length), Proposition S2 (power-law degree distribution), Proposition S3 (high clustering coefficient), Proposition S4 (“fit-gets-richer” growth mechanism), Proposition S5 (truncation of power-law degree distribution), and Proposition S7 (community structure with overlapping boundaries) regarding the global supply chain network. While the original propositions S1 just mentioned a short path length, we found the short path from the GSCC to IN and OUT by analyzing the bow-tie structure. Therefore, the short path length in the bow-tie structure is a conceptual addition to the original propositions of Hearnshaw. Public Library of Science 2020-10-01 /pmc/articles/PMC7529254/ /pubmed/33002029 http://dx.doi.org/10.1371/journal.pone.0239669 Text en © 2020 Chakraborty, Ikeda http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Chakraborty, Abhijit
Ikeda, Yuichi
Testing “efficient supply chain propositions” using topological characterization of the global supply chain network
title Testing “efficient supply chain propositions” using topological characterization of the global supply chain network
title_full Testing “efficient supply chain propositions” using topological characterization of the global supply chain network
title_fullStr Testing “efficient supply chain propositions” using topological characterization of the global supply chain network
title_full_unstemmed Testing “efficient supply chain propositions” using topological characterization of the global supply chain network
title_short Testing “efficient supply chain propositions” using topological characterization of the global supply chain network
title_sort testing “efficient supply chain propositions” using topological characterization of the global supply chain network
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529254/
https://www.ncbi.nlm.nih.gov/pubmed/33002029
http://dx.doi.org/10.1371/journal.pone.0239669
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