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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

The nested structural organization of the worldwide trade multi-layer network

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Author(s):
Alves, Luiz G. A. [1] ; Mangioni, Giuseppe [2] ; Cingolani, Isabella [3] ; Rodrigues, Francisco Aparecido [1, 4, 5] ; Panzarasa, Pietro [6] ; Moreno, Yamir [7, 8, 9]
Total Authors: 6
Affiliation:
[1] Univ Sao Paulo, Inst Math & Comp Sci, BR-13566590 Sao Carlos, SP - Brazil
[2] Univ Catania, Dipartimento Ingn Elettr Elettron & Informat, I-95125 Catania - Italy
[3] Imperial Coll London, Dept Surg & Canc, Big Data & Analyt Unit, London SW7 2AZ - England
[4] Univ Warwick, Ctr Complex Sci, Coventry CV4 7AL, W Midlands - England
[5] Univ Warwick, Math Inst, Gibbet Hill Rd, Coventry CV4 7AL, W Midlands - England
[6] Queen Mary Univ London, Sch Business & Management, London E1 4NS - England
[7] ISI Fdn, I-10126 Turin - Italy
[8] Univ Zaragoza, Dept Theoret Phys, Zaragoza 50009 - Spain
[9] Univ Zaragoza, Inst Biocomputat & Phys Complex Syst, Zaragoza 50009 - Spain
Total Affiliations: 9
Document type: Journal article
Source: SCIENTIFIC REPORTS; v. 9, FEB 27 2019.
Web of Science Citations: 2
Abstract

Nestedness has traditionally been used to detect assembly patterns in meta-communities and networks of interacting species. Attempts have also been made to uncover nested structures in international trade, typically represented as bipartite networks in which connections can be established between countries (exporters or importers) and industries. A bipartite representation of trade, however, inevitably neglects transactions between industries. To fully capture the organization of the global value chain, we draw on the World Input-Output Database and construct a multi-layer network in which the nodes are the countries, the layers are the industries, and links can be established from sellers to buyers within and across industries. We define the buyers' and sellers' participation matrices in which the rows are the countries and the columns are all possible pairs of industries, and then compute nestedness based on buyers' and sellers' involvement in transactions between and within industries. Drawing on appropriate null models that preserve the countries' or layers' degree distributions in the original multi-layer network, we uncover variations of country-and transaction-based nestedness over time, and identify the countries and industries that most contributed to nestedness. We discuss the implications of our findings for the study of the international production network and other real-world systems. (AU)

FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 16/16987-7 - A complex system approach to urban planning and development
Grantee:Luiz Gustavo de Andrade Alves
Support Opportunities: Scholarships in Brazil - Post-Doctoral
FAPESP's process: 16/25682-5 - Information spreading in complex networks
Grantee:Francisco Aparecido Rodrigues
Support Opportunities: Regular Research Grants