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Identifying port maritime communities: application to the Spanish case
The aim of this paper is to detect port maritime communities sharing similar international trade patterns, by a modelisation of maritime traffic using a bipartite weighted network, providing decision-makers the tools to search for alliances or identify their competitors. Our bipartite weighted netwo...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8217790/ http://dx.doi.org/10.1186/s12544-021-00495-1 |
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author | García, Nicanor Adenso-Díaz, Belarmino Calzada-Infante, Laura |
author_facet | García, Nicanor Adenso-Díaz, Belarmino Calzada-Infante, Laura |
author_sort | García, Nicanor |
collection | PubMed |
description | The aim of this paper is to detect port maritime communities sharing similar international trade patterns, by a modelisation of maritime traffic using a bipartite weighted network, providing decision-makers the tools to search for alliances or identify their competitors. Our bipartite weighted network considers two different types of nodes: one represents the ports, while the other represents the countries where there are major import/export activity from each port. The freight traffic among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the Spanish case is considered, with the data segmented by each type of traffic for a fine tuning. A sort of link prediction is possible, finding for those communities with two or more ports, countries that are part of the same community but with which some ports do not have yet significant traffic. The evolution of the traffics is analyzed by comparing the communities in 2009 and 2019. The set of communities formed by the ports of the Spanish port system can be used to identify global similarities between them, comparing the membership of the different ports in communities for both periods and each type of traffic in particular. |
format | Online Article Text |
id | pubmed-8217790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-82177902021-06-23 Identifying port maritime communities: application to the Spanish case García, Nicanor Adenso-Díaz, Belarmino Calzada-Infante, Laura Eur. Transp. Res. Rev. Original Paper The aim of this paper is to detect port maritime communities sharing similar international trade patterns, by a modelisation of maritime traffic using a bipartite weighted network, providing decision-makers the tools to search for alliances or identify their competitors. Our bipartite weighted network considers two different types of nodes: one represents the ports, while the other represents the countries where there are major import/export activity from each port. The freight traffic among both types of nodes is modeled by weighting the volume of product transported. To illustrate the model, the Spanish case is considered, with the data segmented by each type of traffic for a fine tuning. A sort of link prediction is possible, finding for those communities with two or more ports, countries that are part of the same community but with which some ports do not have yet significant traffic. The evolution of the traffics is analyzed by comparing the communities in 2009 and 2019. The set of communities formed by the ports of the Spanish port system can be used to identify global similarities between them, comparing the membership of the different ports in communities for both periods and each type of traffic in particular. Springer International Publishing 2021-06-22 2021 /pmc/articles/PMC8217790/ http://dx.doi.org/10.1186/s12544-021-00495-1 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Original Paper García, Nicanor Adenso-Díaz, Belarmino Calzada-Infante, Laura Identifying port maritime communities: application to the Spanish case |
title | Identifying port maritime communities: application to the Spanish case |
title_full | Identifying port maritime communities: application to the Spanish case |
title_fullStr | Identifying port maritime communities: application to the Spanish case |
title_full_unstemmed | Identifying port maritime communities: application to the Spanish case |
title_short | Identifying port maritime communities: application to the Spanish case |
title_sort | identifying port maritime communities: application to the spanish case |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8217790/ http://dx.doi.org/10.1186/s12544-021-00495-1 |
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