000078827 001__ 78827
000078827 005__ 20200716101419.0
000078827 0247_ $$2doi$$a10.1038/s41598-019-39340-w
000078827 0248_ $$2sideral$$a111153
000078827 037__ $$aART-2019-111153
000078827 041__ $$aeng
000078827 100__ $$aAlves, L.G.A.
000078827 245__ $$aThe nested structural organization of the worldwide trade multi-layer network
000078827 260__ $$c2019
000078827 5060_ $$aAccess copy available to the general public$$fUnrestricted
000078827 5203_ $$aNestedness 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.
000078827 536__ $$9info:eu-repo/grantAgreement/ES/MINECO-FEDER/FIS2014-55867-P$$9This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 640772-DOLFINS$$9info:eu-repo/grantAgreement/EC/H2020/640772/EU/Distributed Global Financial Systems for Society/DOLFINS$$9info:eu-repo/grantAgreement/ES/DGA/E36-17R
000078827 540__ $$9info:eu-repo/semantics/openAccess$$aby$$uhttp://creativecommons.org/licenses/by/3.0/es/
000078827 590__ $$a3.998$$b2019
000078827 592__ $$a1.341$$b2019
000078827 591__ $$aMULTIDISCIPLINARY SCIENCES$$b17 / 71 = 0.239$$c2019$$dQ1$$eT1
000078827 593__ $$aMultidisciplinary$$c2019$$dQ1
000078827 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000078827 700__ $$aMangioni, G.
000078827 700__ $$aCingolani, I.
000078827 700__ $$aRodrigues, F.A.
000078827 700__ $$aPanzarasa, P.
000078827 700__ $$0(orcid)0000-0002-0895-1893$$aMoreno, Y.$$uUniversidad de Zaragoza
000078827 7102_ $$12004$$2405$$aUniversidad de Zaragoza$$bDpto. Física Teórica$$cÁrea Física Teórica
000078827 773__ $$g9, 1 (2019), 2866 [14 pp]$$pSci. rep.$$tScientific Reports$$x2045-2322
000078827 8564_ $$s2497248$$uhttps://zaguan.unizar.es/record/78827/files/texto_completo.pdf$$yVersión publicada
000078827 8564_ $$s116312$$uhttps://zaguan.unizar.es/record/78827/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000078827 909CO $$ooai:zaguan.unizar.es:78827$$particulos$$pdriver
000078827 951__ $$a2020-07-16-08:39:40
000078827 980__ $$aARTICLE