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Threshold sensitivity of the production network topology

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Threshold sensitivity of the production network topology. / Molnár, Eszter; Csala, Dénes.
In: Applied Network Science, Vol. 8, No. 1, 71, 05.10.2023.

Research output: Contribution to Journal/Magazine › Journal article › peer-review

Harvard

Molnár, E & Csala, D 2023, 'Threshold sensitivity of the production network topology', Applied Network Science, vol. 8, no. 1, 71. https://doi.org/10.1007/s41109-023-00599-8

APA

Molnár, E., & Csala, D. (2023). Threshold sensitivity of the production network topology. Applied Network Science, 8(1), Article 71. https://doi.org/10.1007/s41109-023-00599-8

Vancouver

Molnár E, Csala D. Threshold sensitivity of the production network topology. Applied Network Science. 2023 Oct 5;8(1):71. doi: 10.1007/s41109-023-00599-8

Author

Molnár, Eszter ; Csala, Dénes. / Threshold sensitivity of the production network topology. In: Applied Network Science. 2023 ; Vol. 8, No. 1.

Bibtex

@article{e6f2c889c06b44aa8965a495d035916e,
title = "Threshold sensitivity of the production network topology",
abstract = "Industries today are tightly interconnected, necessitating a systematic perspective in understanding the complexity of relations. Employing network science, the literature constructs dense production networks to address this challenge. However, handling this high density involves carefully choosing the level of pruning to retain as much information as possible. Yet, current research lacks comprehensive insight into the extent of distortion the data removal produces in the network structure. Our paper aims to examine how this widespread thresholding method changes the production network{\textquoteright}s topology. We do this by studying the network topology and centrality metrics under various thresholds on inter-industry networks derived from the US input-output accounts. We find that altering even minor threshold values significantly reshapes the network{\textquoteright}s structure. Core industries serving as hubs are also affected. Hence, research using the production network framework to explain the propagation of local shocks and disturbances should also take into account that even low-value monetary transactions contribute to the interrelatedness and complexity of production networks.",
keywords = "Network science, Monetary transactions, Production network, Threshold, Input-output analysis",
author = "Eszter Moln{\'a}r and D{\'e}nes Csala",
year = "2023",
month = oct,
day = "5",
doi = "10.1007/s41109-023-00599-8",
language = "English",
volume = "8",
journal = "Applied Network Science",
issn = "2364-8228",
publisher = "SpringerOpen",
number = "1",

}

RIS

TY - JOUR

T1 - Threshold sensitivity of the production network topology

AU - Molnár, Eszter

AU - Csala, Dénes

PY - 2023/10/5

Y1 - 2023/10/5

N2 - Industries today are tightly interconnected, necessitating a systematic perspective in understanding the complexity of relations. Employing network science, the literature constructs dense production networks to address this challenge. However, handling this high density involves carefully choosing the level of pruning to retain as much information as possible. Yet, current research lacks comprehensive insight into the extent of distortion the data removal produces in the network structure. Our paper aims to examine how this widespread thresholding method changes the production network’s topology. We do this by studying the network topology and centrality metrics under various thresholds on inter-industry networks derived from the US input-output accounts. We find that altering even minor threshold values significantly reshapes the network’s structure. Core industries serving as hubs are also affected. Hence, research using the production network framework to explain the propagation of local shocks and disturbances should also take into account that even low-value monetary transactions contribute to the interrelatedness and complexity of production networks.

AB - Industries today are tightly interconnected, necessitating a systematic perspective in understanding the complexity of relations. Employing network science, the literature constructs dense production networks to address this challenge. However, handling this high density involves carefully choosing the level of pruning to retain as much information as possible. Yet, current research lacks comprehensive insight into the extent of distortion the data removal produces in the network structure. Our paper aims to examine how this widespread thresholding method changes the production network’s topology. We do this by studying the network topology and centrality metrics under various thresholds on inter-industry networks derived from the US input-output accounts. We find that altering even minor threshold values significantly reshapes the network’s structure. Core industries serving as hubs are also affected. Hence, research using the production network framework to explain the propagation of local shocks and disturbances should also take into account that even low-value monetary transactions contribute to the interrelatedness and complexity of production networks.

KW - Network science

KW - Monetary transactions

KW - Production network

KW - Threshold

KW - Input-output analysis

U2 - 10.1007/s41109-023-00599-8

DO - 10.1007/s41109-023-00599-8

M3 - Journal article

VL - 8

JO - Applied Network Science

JF - Applied Network Science

SN - 2364-8228

IS - 1

M1 - 71

ER -