TY - GEN
T1 - Performance of a Multi-layer Commodity Flow Network in the United States Under Disturbance
AU - Garcia, Susana
AU - Rajtmajer, Sarah
AU - Grady, Caitlin
AU - Mohammadpour, Paniz
AU - Mejia, Alfonso
N1 - Funding Information:
Authors would like to acknowledge Venkat Ashish Kumar Simhachalam for assistance with Fig. 1 and Tasnuva Mahjabin for assistance with Fig. 4. Drs. Rajtmajer and Grady gratefully acknowledge seed funding from the Rock Ethics Institute at The Pennsylvania State University.
Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Network-based analyses have furthered global understanding of supply chain and commodity trade networks between countries. Much of the previous work in this area has focused on analyzing economic sectors separately, aggregating sectors neglecting inter-sectoral connectivity, or representing trade at a national scale losing intrastate connections and impact. We further previous work by constructing and analyzing the intrastate input-output multi-layer network of the United States commodity and service sectors. We subject the network to perturbations and find that the government services sector represents the most influential sector as it generates the most impact when shocked. Taking this sector as exemplar, we showcase how impact varies differentially across regions, and how impact compares to other measures of resilience.
AB - Network-based analyses have furthered global understanding of supply chain and commodity trade networks between countries. Much of the previous work in this area has focused on analyzing economic sectors separately, aggregating sectors neglecting inter-sectoral connectivity, or representing trade at a national scale losing intrastate connections and impact. We further previous work by constructing and analyzing the intrastate input-output multi-layer network of the United States commodity and service sectors. We subject the network to perturbations and find that the government services sector represents the most influential sector as it generates the most impact when shocked. Taking this sector as exemplar, we showcase how impact varies differentially across regions, and how impact compares to other measures of resilience.
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U2 - 10.1007/978-3-030-36683-4_52
DO - 10.1007/978-3-030-36683-4_52
M3 - Conference contribution
AN - SCOPUS:85087864232
SN - 9783030366827
T3 - Studies in Computational Intelligence
SP - 645
EP - 655
BT - Complex Networks and Their Applications VIII - Volume 2 Proceedings of the 8th International Conference on Complex Networks and Their Applications COMPLEX NETWORKS 2019
A2 - Cherifi, Hocine
A2 - Gaito, Sabrina
A2 - Mendes, José Fernendo
A2 - Moro, Esteban
A2 - Rocha, Luis Mateus
PB - Springer
T2 - 8th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2019
Y2 - 10 December 2019 through 12 December 2019
ER -