IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2003.02343.html
   My bibliography  Save this paper

Bow-tie structure and community identification of global supply chain network

Author

Listed:
  • Abhijit Chakraborty
  • Yuichi Ikeda

Abstract

We study on topological properties of global supply chain network in terms of degree distribution, hierarchical structure, and degree-degree correlation in the global supply chain network. The global supply chain data is constructed by collecting various company data from the web site of Standard & Poor's Capital IQ platform in 2018. The in- and out-degree distributions are characterized by a power law with in-degree exponent = 2.42 and out-degree exponent = 2.11. The clustering coefficient decays as power law with an exponent = 0.46. The nodal degree-degree correlation indicates the absence of assortativity. The Bow-tie structure of GWCC reveals that the OUT component is the largest and it consists 41.1% of total firms. The GSCC component comprises 16.4% of total firms. We observe that the firms in the upstream or downstream sides are mostly located a few steps away from the GSCC. Furthermore, we uncover the community structure of the network and characterize them according to their location and industry classification. We observe that the largest community consists of consumer discretionary sector mainly based in the US. These firms belong to the OUT component in the bow-tie structure of the global supply chain network. Finally, we confirm the validity for propositions S1 (short path length), S2 (power-law degree distribution), S3 (high clustering coefficient), S4 ("fit-gets-richer" growth mechanism), S5 (truncation of power-law degree distribution), and S7 (community structure with overlapping boundaries) in the global supply chain network.

Suggested Citation

  • Abhijit Chakraborty & Yuichi Ikeda, 2020. "Bow-tie structure and community identification of global supply chain network," Papers 2003.02343, arXiv.org.
  • Handle: RePEc:arx:papers:2003.02343
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2003.02343
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aoyama,Hideaki & Fujiwara,Yoshi & Ikeda,Yuichi & Iyetomi,Hiroshi & Souma,Wataru Preface by-Name:Yoshikawa,Hiroshi, 2010. "Econophysics and Companies," Cambridge Books, Cambridge University Press, number 9780521191494.
    2. Abhijit Chakraborty & Yuichi Kichikawa & Takashi Iino & Hiroshi Iyetomi & Hiroyasu Inoue & Yoshi Fujiwara & Hideaki Aoyama, 2018. "Hierarchical communities in the walnut structure of the Japanese production network," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-25, August.
    3. Chakraborty, Abhijit & Krichene, Hazem & Inoue, Hiroyasu & Fujiwara, Yoshi, 2019. "Characterization of the community structure in a large-scale production network in Japan," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 513(C), pages 210-221.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Abhijit Chakraborty & Yuichi Kichikawa & Takashi Iino & Hiroshi Iyetomi & Hiroyasu Inoue & Yoshi Fujiwara & Hideaki Aoyama, 2018. "Hierarchical communities in the walnut structure of the Japanese production network," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-25, August.
    2. Hiromitsu Goto & Wataru Souma & Mari Jibu & Yuichi Ikeda, 2020. "Multilayer Network Analysis of the Drug Pipeline in the Global Pharmaceutical Industry," Papers 2003.04620, arXiv.org.
    3. Corrado Di Guilmi & Yoshi Fujiwara, 2020. "Does the supply network shape the firm size distribution? The Japanese case," CAMA Working Papers 2020-66, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Abhijit Chakraborty & Hiroyasu Inoue & Yoshi Fujiwara, 2020. "Economic complexity of prefectures in Japan," PLOS ONE, Public Library of Science, vol. 15(8), pages 1-13, August.
    5. Hideaki Aoyama, 2021. "XRP Network and Proposal of Flow Index," Papers 2106.10012, arXiv.org.
    6. Abhijit Chakraborty & Hiroyasu Inoue & Yoshi Fujiwara, 2020. "Economic complexity of prefectures in Japan," Papers 2002.05785, arXiv.org, revised Aug 2020.
    7. Bahrami, Mohammad & Chinichian, Narges & Hosseiny, Ali & Jafari, Gholamreza & Ausloos, Marcel, 2020. "Optimization of the post-crisis recovery plans in scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 540(C).
    8. Juliana D. Araujo & Povilas Lastauskas & Chris Papageorgiou, 2017. "Evolution of Bilateral Capital Flows to Developing Countries at Intensive and Extensive Margins," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 49(7), pages 1517-1554, October.
    9. Atushi Ishikawa & Takayuki Mizuno & Shouji Fujimoto, 2022. "Employee Number Dependence in Labor Productivity Distribution," The Review of Socionetwork Strategies, Springer, vol. 16(2), pages 465-477, October.
    10. Daisuke Sato & Yuichi Ikeda & Shuichi Kawai & Maxmilian Schich, 2020. "The sustainability and the survivability of Kyoto’s traditional craft industry revealed from supplier-customer network," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-23, November.
    11. MIZUNO Makoto & AOYAMA Hideaki & FUJIWARA Yoshi, 2020. "Constructing the Customer Journey Map of Competitive Brands: A Complex Time-series Analysis," Discussion papers 20070, Research Institute of Economy, Trade and Industry (RIETI).
    12. Hosseiny, Ali & Gallegati, Mauro, 2017. "Role of intensive and extensive variables in a soup of firms in economy to address long run prices and aggregate data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 51-59.
    13. Michal Fabinger & E. Glen Weyl, 2018. "Functional Forms for Tractable Economic Models and the Cost Structure of International Trade," CIRJE F-Series CIRJE-F-1092, CIRJE, Faculty of Economics, University of Tokyo.
    14. Povilas Lastauskas, 2013. "Europe’s Revolving Doors: Import Competition and Endogenous Firm Entry InstitutionS," Cambridge Working Papers in Economics 1360, Faculty of Economics, University of Cambridge.
    15. Inoue, Jun-ichi & Ghosh, Asim & Chatterjee, Arnab & Chakrabarti, Bikas K., 2015. "Measuring social inequality with quantitative methodology: Analytical estimates and empirical data analysis by Gini and k indices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 184-204.
    16. Ma, Tao & Holden, John G. & Serota, R.A., 2013. "Distribution of wealth in a network model of the economy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(10), pages 2434-2441.
    17. FUJIWARA Yoshi & INOUE Hiroyasu & YAMAGUCHI Takayuki & AOYAMA Hideaki & TANAKA Takuma & KIKUCHI Kentaro, 2021. "Money Flow Network Among Firms' Accounts in a Regional Bank of Japan," Discussion papers 21005, Research Institute of Economy, Trade and Industry (RIETI).
    18. Kumar, Ashish & Chakrabarti, Anindya S. & Chakraborti, Anirban & Nandi, Tushar, 2021. "Distress propagation on production networks: Coarse-graining and modularity of linkages," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 568(C).
    19. Hiroyasu Inoue, 2015. "Analyses of Aggregate Fluctuations of Firm Network Based on the Self-Organized Criticality Model," Papers 1512.05066, arXiv.org, revised Apr 2016.
    20. Roy Cerqueti & Giulia Rotundo & Marcel Ausloos, 2021. "Tsallis entropy for cross-shareholding network configurations," Papers 2109.04214, arXiv.org.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2003.02343. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.