{"title":"汽车行业供应网络中上游和下游配置驱动因素的比较:使用 ERGMs 的探索性研究","authors":"Chulsoon Park","doi":"10.32956/kopoms.2024.35.1.21","DOIUrl":null,"url":null,"abstract":"Modern industry is a competition between supply networks. Knowing and managing the supply network well is an essential survival requirement for a company. There is a difference in orientation between the upstream and downstream of the supply network, which causes structural differences between the upstream and downstream. This study aims to reveal the differences in the configuration drivers of the upstream and downstream automotive supply networks. Using transaction data from the automotive industry, we compared the drivers that constitute supply networks and create upstream and downstream links. The Exponential Random Graph Models (ERGMs) were used to evaluate the significance of configuration drivers, including company attributes, dyadic attributes, and structural characteristics. As a result, the age of supplier, size of the purchaser, sales of the purchaser, asset of the purchaser, transitivity, and activity were found to be common drivers of upstream and downstream. On the other hand, the age of the purchaser, the difference in sales between the two companies, and popularity were found to be significant drivers only in the downstream network. These research results are the first to empirically compare the upstream and downstream supply networks, and have academic contribution as the first step in finding the cause of the differences in network structure between the upstream and downstream networks.","PeriodicalId":436415,"journal":{"name":"Korean Production and Operations Management Society","volume":"37 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of Upstream and Downstream Configuration Drivers in Automotive Industry Supply Networks: An Exploratory Study Using ERGMs\",\"authors\":\"Chulsoon Park\",\"doi\":\"10.32956/kopoms.2024.35.1.21\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Modern industry is a competition between supply networks. Knowing and managing the supply network well is an essential survival requirement for a company. There is a difference in orientation between the upstream and downstream of the supply network, which causes structural differences between the upstream and downstream. This study aims to reveal the differences in the configuration drivers of the upstream and downstream automotive supply networks. Using transaction data from the automotive industry, we compared the drivers that constitute supply networks and create upstream and downstream links. The Exponential Random Graph Models (ERGMs) were used to evaluate the significance of configuration drivers, including company attributes, dyadic attributes, and structural characteristics. As a result, the age of supplier, size of the purchaser, sales of the purchaser, asset of the purchaser, transitivity, and activity were found to be common drivers of upstream and downstream. On the other hand, the age of the purchaser, the difference in sales between the two companies, and popularity were found to be significant drivers only in the downstream network. These research results are the first to empirically compare the upstream and downstream supply networks, and have academic contribution as the first step in finding the cause of the differences in network structure between the upstream and downstream networks.\",\"PeriodicalId\":436415,\"journal\":{\"name\":\"Korean Production and Operations Management Society\",\"volume\":\"37 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Korean Production and Operations Management Society\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.32956/kopoms.2024.35.1.21\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Korean Production and Operations Management Society","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32956/kopoms.2024.35.1.21","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Comparison of Upstream and Downstream Configuration Drivers in Automotive Industry Supply Networks: An Exploratory Study Using ERGMs
Modern industry is a competition between supply networks. Knowing and managing the supply network well is an essential survival requirement for a company. There is a difference in orientation between the upstream and downstream of the supply network, which causes structural differences between the upstream and downstream. This study aims to reveal the differences in the configuration drivers of the upstream and downstream automotive supply networks. Using transaction data from the automotive industry, we compared the drivers that constitute supply networks and create upstream and downstream links. The Exponential Random Graph Models (ERGMs) were used to evaluate the significance of configuration drivers, including company attributes, dyadic attributes, and structural characteristics. As a result, the age of supplier, size of the purchaser, sales of the purchaser, asset of the purchaser, transitivity, and activity were found to be common drivers of upstream and downstream. On the other hand, the age of the purchaser, the difference in sales between the two companies, and popularity were found to be significant drivers only in the downstream network. These research results are the first to empirically compare the upstream and downstream supply networks, and have academic contribution as the first step in finding the cause of the differences in network structure between the upstream and downstream networks.