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.

当今的各行各业紧密相连，需要以系统的视角来理解关系的复杂性。文献利用网络科学构建密集的生产网络来应对这一挑战。然而，处理如此高的密度需要仔细选择修剪级别以保留尽可能多的信息。然而，当前的研究缺乏对数据删除在网络结构中产生的扭曲程度的全面了解。我们的论文旨在研究这种广泛使用的阈值方法如何改变生产网络的拓扑。我们通过研究源自美国投入产出账户的行业间网络的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着重塑网络的结构。作为枢纽的核心产业也受到影响。因此，使用生产网络框架来解释局部冲击和扰动的传播的研究还应该考虑到，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。