{"title":"生产网络拓扑阈值灵敏度","authors":"Eszter Molnár, Dénes Csala","doi":"10.1007/s41109-023-00599-8","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":37010,"journal":{"name":"Applied Network Science","volume":"80 1","pages":"0"},"PeriodicalIF":1.3000,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Threshold sensitivity of the production network topology\",\"authors\":\"Eszter Molnár, Dénes Csala\",\"doi\":\"10.1007/s41109-023-00599-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":37010,\"journal\":{\"name\":\"Applied Network Science\",\"volume\":\"80 1\",\"pages\":\"0\"},\"PeriodicalIF\":1.3000,\"publicationDate\":\"2023-10-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applied Network Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s41109-023-00599-8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Network Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41109-023-00599-8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
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.