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Global oil traffic network and diffusion of influence among ports using real time data

  • CAS - Institute of Geographical Sciences and Natural Resources Research
  • University of Chinese Academy of Sciences
  • Fuzhou University
  • Nanjing Normal University

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

This paper seeks to shed light on how ports spread their influence through propagatory activation of other ports in the global oil traffic network from 2009 to 2016. Using a modified linear threshold model, the paper does not attempt to identify a few fixed ports that served as “seeds” for propagation and influence maximization. Instead it identifies active seed port hubs via their diffusion patterns and the number of ports in the networks that become influenced as a result. The computations show that diffusion is highly uneven but Rotterdam, Antwerp and Singapore emerged as the three most influential seed ports particularly in 2013 and 2016. Whereas over half of the ports in the networks were able to influence just one other port, Rotterdam and Antwerp influenced ports in the entire network. Singapore's spread of influence is smaller but its activation rate is more rapid because the port-city's influence tends to be much more regionally confined. Rotterdam's propagation occurs in fewer stages than Antwerp's suggesting that information and innovation spread more readily from the former city-port. Taken together, the analysis points to the above three city-ports as the most effective hubs for dissemination of information in the oil, including tanker, industry.

Original languageEnglish
Pages (from-to)333-342
Number of pages10
JournalEnergy
Volume172
DOIs
StatePublished - Apr 1 2019

Keywords

  • Automatic identification system
  • Global oil traffic networks
  • Influence diffusion
  • Modified liner threshold model
  • Ports

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