Skip to main content

Advertisement

SpringerLink
Log in

Analysis of the global maritime transportation system as a layered network

  • Published:
Journal of Transportation Security Aims and scope Submit manuscript

Abstract

We model the global maritime transportation system as a multilayer network of sea routes and land routes that work together to deliver cargo on a global scale. The nodes of this network represent seaports and maritime chokepoints, and the arcs represent route segments at sea or on land, respectively. We construct our network using free, publicly available data from online sources, and we reverse engineer the global demand for container cargo transport. We use this layered network to identify important nodes from a connectivity standpoint. We also develop a flow-based model that directs the aggregate movement of goods between ports on the shortest and/or cheapest available route, and uses re-routing strategies if a route segment becomes impassable for container ships. We use this model to assess the impact of the loss of one or more container ports or maritime chokepoints. Using the base case of no disruptions, we measure the amount of goods that have to be re-routed in case of each disruption and the corresponding “cost” of doing so. Collectively, these results present a novel view of the security of transportation supply and set the stage for future work examining the global resilience of maritime transport systems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Ahuja RK, Magnanti TL, Orlin JB (1993) Network flows: theory, algorithms, and applications. Prentice Hall

  • Alderson D, Doyle J (2010) Contrasting views of complexity and their implications for network-centric infrastructures. IEEE Trans Sys Man Cybernetics A: Systems And Humans 40(4):839–852

    Article  Google Scholar 

  • Alderson DL (2008) Catching the “network science” bug: insight and opportunity for the operations researcher. Oper Res 56(5):1047–1065

    Article  Google Scholar 

  • Alderson DL, Brown GG, Carlyle WM (2014) Assessing and improving operational resilience of critical infrastructures and other systems. In: Newman A, Leung J (eds) Tutorials in Operations Research: Bridging Data and Decisions. INFORMS, 180–215

  • Alderson DL, Brown GG, Carlyle WM (2015) Operational models of infrastructure resilience. Risk Anal 35(4):562–586

    Article  Google Scholar 

  • Alderson DL, Brown GG, Carlyle WM, Cox LA (2013) Sometimes there is no “most vital” arc: assessing and improving the operational resilience of systems. Mil Oper Res 18(1):21–37

    Article  Google Scholar 

  • Basu P, Sundaram R, Dippel M (2015) Multiplex networks: a generative model and algorithmic complexity. Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015. ACM, 456–463

  • Bencomo LA (2009) Modeling the effects of a transportation security incident on the commercial transportation system. Master's thesis, Naval Postgraduate School, Monterey, California

  • Brin S, Page L (2012) Reprint of: the anatomy of a large-scale hypertextual web search engine. Comput Netw 56(18):3825–3833

    Article  Google Scholar 

  • Brown GG, Carlyle WM, Salmerón JS, Wood RK (2006) Defending critical infrastructure. Interfaces 36:530–544

    Article  Google Scholar 

  • Brown GG, Washburn AR (2017) Method and system for determining shortest oceanic routes. United States patent 9,541,401. Issued 10 January

  • Bruns S, Petretto K, Petrovic D (2013) Maritime Sicherheit [maritime security] . Springer-Verlag

  • Cardillo A, Zanin M, Gómez-Gardenes J, Romance M, del Amo AJ, Boccaletti S (2013) Modeling the multi-layer nature of the European air transport network: resilience and passengers re-scheduling under random failures. The European Physical Journal Special Topics 215(1):23–33

    Article  Google Scholar 

  • Central Intelligence Agency (2017) The world factbook. URL https://www.cia.gov/library/publications/the-world-factbook/. Accessed February 2017

  • Chen L, Miller-Hooks E (2012) Resilience: an indicator of recovery capability in intermodal freight transport. Transp Sci 46(1):109–123

    Article  Google Scholar 

  • Cohen SS (2002) Economic impact of a west coast dock shutdown. University of California at Berkeley 1

  • Cruz A (2016) Bankruptcy woes: Hanjin makes waves across the world. Global trade http://www.globaltrademag.com/global-logistics/bankruptcy-woes-hanjin-makes-waves-across-world. Accessed 4 Dec 2017

  • De Domenico M, Lancichinetti A, Arenas A, Rosvall M (2015) Identifying modular flows on multilayer networks reveals highly overlapping organization in interconnected systems. Physical Review X 5(1):011027

    Article  Google Scholar 

  • De la Cruz CF (2011) Defending the maritime transport of cargo for the Hawaiian islands. Master's thesis, Naval Postgraduate School, Monterey, CA

  • Drake JM, Lodge DM (2007) Hull fouling is a risk factor for intercontinental species exchange in aquatic ecosystems. Aquat Invasions (2)

  • Ducruet C, Notteboom T (2012) The worldwide maritime network of container shipping: spatial structure and regional dynamics. Global networks 12(3):395–423

    Article  Google Scholar 

  • Faturechi R, Miller-Hooks E (2014) Measuring the performance of transportation infrastructure systems in disasters: a comprehensive review. J Infrastruct Syst 21(1):04014025

    Article  Google Scholar 

  • Flynn SE, Holmes J, Burke S (2017) A new international framework for bolstering global supply system security and resilience. Tech. rep., Global Resilience Institute, Northeastern University, Boston, MA

  • Freeman LC (1977) A set of measures of centrality based on betweenness. Sociometry 35-41

  • Funk D (2017) Analysis of the global maritime transportation system and its resilience. Master's thesis, Naval Postgraduate School, Monterey, CA

  • Garcia Olalla OR (2012) Assessing the resilience of global sea routes. Master's thesis, Naval Postgraduate School, Monterey, CA

  • Google (2017) Google Maps. URL http://www.maps.google.com/. Accessed December 04, 2017

  • Guimerá R, Amaral LAN (2004) Modeling the world-wide airport network. The European Physical Journal B 38(2):381–385

    Article  Google Scholar 

  • Guimerá R, Mossa S, Turtschi A, Amaral LAN (2005) The worldwide air transportation network: anomalous centrality, community structure, and cities' global roles. Proc Natl Acad Sci 102(22):7794–7799

    Article  Google Scholar 

  • Hirsch JE (2005) An index to quantify an individual's scientific research output. Proc Natl Acad Sci U S A 102(46):16569

    Article  Google Scholar 

  • Huber T (2014) "Global Ports" in der maritimen Transportwirtschaft. Akteursbasierende Bewertung des weltweiten Netzwerks von Hafenstandorten ["global ports" in the maritime transport sector, a player based assessment of the global network of port locations]. Ph.D. thesis, Fakultt fr Philosphie, Kunst-, Geschichts- und Gesellschaftswissenschaften der Universitt Regensburg, Regensburg, Germany

  • Jiang J, Lee LH, Chew EP, Gan CC (2015) Port connectivity study: an analysis framework from a global container liner shipping network perspective. Transportation Research Part E: Logistics and Transportation Review 73:47–64

    Article  Google Scholar 

  • Kaluza P, Klzsch A, Gastner MT, Blasius B (2010) The complex network of global cargo ship movements. J R Soc Interface 7(48):1093–1103

    Article  Google Scholar 

  • Katz L (1953) A new status index derived from sociometric analysis. Psychometrika 18(1):39–43

    Article  Google Scholar 

  • Khouri A (2015) West coast ports facing shutdown in labor dispute. Los Angeles Times https://www.latimes.com/business/la-fi-port-shutdown-20150207-story.html. Accessed 29 May 2017

  • Komiss W, Huntzinger L (2011) The economic implications of disruptions to maritime oil chokepoints. Center for Naval Analysis

  • Madhusudan C, Ganapathy GP (2011) Disaster resilience of transportation infrastructure and ports: an overview. International Journal of Geomatics and Geosciences 2(2):443

    Google Scholar 

  • Martagan TG, Eksioglu B, Eksioglu SD, Greenwood AG (2009) A simulation model of port operations during crisis conditions. Proceedings of the 2009 Winter Simulation Conference (WSC), 2832–2843

  • Microsoft Corporation (2017) Bing Maps. http://www.bing.com/maps. Accessed December 04, 2017

  • Miller-Hooks E, Zhang X, Faturechi R (2012) Measuring and maximizing resilience of freight transportation networks. Comput Oper Res 39(7):1633–1643

    Article  Google Scholar 

  • Mintzer DS (2014) Optimizing the resilience of containerized cargo transportation infrastructure in the port of Los Angeles. Master's thesis, Naval Postgraduate School, Monterey, CA

  • Mitchell R (2015) Web scraping with Python: collecting data from the modern web. O'Reilly Media, Inc.

  • Nagurney A (2006) Supply chain network economics: dynamics of prices, flows and profits. Edward Elgar Publishing

  • Newman M (2010) Networks: an introduction. Oxford University Press, Oxford

  • Noer JH, Gregory D (1996) Chokepoints: maritime economic concerns in Southeast Asia. Tech. rep. DTIC Document

  • Onuska JJ (2012) Defending the Pittsburgh waterways against catastrophic disruption. Master's thesis, Naval Postgraduate School, Monterey, CA

  • Pidgeon ED (2008) Modeling the effects of a transportation security incident upon the marine transportation system. Master's thesis, Naval Postgraduate School, Monterey, CA

  • Rodrigue J-P, Comtois C, Slack B (2017) The geography of transport systems (4th Ed.). Taylor & Francis

  • Ruiz GM, Rawlings TK, Dobbs FC, Drake LA, Mullady T, Huq A, Colwell RR (2000) Global spread of microorganisms by ships. Nature 408(6808):49–50

    Article  Google Scholar 

  • Sabidussi G (1966) The centrality index of a graph. Psychometrika 31(4):581–603

    Article  Google Scholar 

  • SeaRates LP (2017) SeaRates.com: Digital Broker & Freight Forwarder. URL http://www.searates.com. Last accessed December 04, 2017

  • Shaw ME (1954) Some effects of unequal distribution of information upon group performance in various communication nets. The journal of abnormal and social psychology 49 (4p1) 547

  • Stephenson K, Zelen M (1989) Rethinking centrality: methods and examples. Soc Networks 11(1):1–37

    Article  Google Scholar 

  • The Tioga Group, Inc (2010) Container port capacity study. Report submitted to the US Army Corps of Engineers. Institute for Water Resources, Alexandria

    Google Scholar 

  • Wang C, Wang J (2011) Spatial pattern of the global shipping network and its hub-and-spoke system. Res Transp Econ 32(1):54–63

    Article  Google Scholar 

  • Wang Y, Cullinane K (2016) Determinants of port centrality in maritime container transportation. Transportation Research Part E: Logistics and Transportation Review 95:326–340

    Article  Google Scholar 

  • Wenke W (2015) Assessing the operational resilience of the port of Anchorage: recommendations for investment and implications for policy. Master's thesis, Naval Postgraduate School, Monterey, CA

  • World Trade Organization (2007) World trade report. World Trade Organization

  • Zeihan P (2014) The accidental superpower: the next generation of American preeminence and the coming global disorder. Twelve, New York

Download references

Acknowledgments

This manuscript is adapted from the thesis by one of the authors (Funk 2017), and portions of this work have appeared there. The authors would like to thank Stephen Flynn for ongoing conversations about the security and resilience of the maritime transport system. This research was funded in part by the Office of Naval Research and the Defense Threat Reduction Agency.

Author information

Authors and Affiliations

  1. Naval Postgraduate School, Monterey, CA, USA

    David L. Alderson

  2. German Army, Oldenburg, Germany

    Daniel Funk

  3. Naval Postgraduate School, Monterey, CA, USA

    Ralucca Gera

Authors
  1. David L. Alderson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Daniel Funk
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ralucca Gera
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David L. Alderson.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix. Additional Data Tables

Appendix. Additional Data Tables

Table 10 Exports and imports of the countries of the model. Source: Central intelligence Agency (2017)
Full size table
Table 11 Main export and import partners of the countries. Source: Central Intelligence Agency (2017)
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Alderson, D.L., Funk, D. & Gera, R. Analysis of the global maritime transportation system as a layered network. J Transp Secur 13, 291–325 (2020). https://doi.org/10.1007/s12198-019-00204-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12198-019-00204-z

Keywords

Search

Navigation