生产网络拓扑阈值灵敏度

IF 1.3 Q3 COMPUTER SCIENCE, THEORY & METHODS
Eszter Molnár, Dénes Csala
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引用次数: 0

摘要

今天的工业是紧密相连的,需要一个系统的角度来理解关系的复杂性。运用网络科学,本文构建了密集的生产网络来应对这一挑战。然而,处理这种高密度需要仔细选择修剪的级别,以保留尽可能多的信息。然而,目前的研究缺乏对数据去除在网络结构中产生的扭曲程度的全面认识。我们的论文旨在研究这种广泛的阈值方法如何改变生产网络的拓扑结构。我们通过研究来自美国投入产出账户的跨行业网络在不同阈值下的网络拓扑和中心性指标来做到这一点。我们发现,即使改变很小的阈值,也会显著地重塑网络的结构。作为枢纽的核心产业也受到了影响。因此,使用生产网络框架来解释局部冲击和干扰传播的研究也应该考虑到,即使是低价值的货币交易也会导致生产网络的相互关联性和复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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’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.
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来源期刊
Applied Network Science
Applied Network Science Multidisciplinary-Multidisciplinary
CiteScore
4.60
自引率
4.50%
发文量
74
审稿时长
5 weeks
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