{"title":"波动性模型在供应链预测中的应用:以台湾TFT-LCD产业为例","authors":"Y. Liang","doi":"10.1109/IEEM.2016.7797851","DOIUrl":null,"url":null,"abstract":"The bullwhip effect denotes that an augment in demand variability on the supply chain can enlarge its influences through an undertaking's supply chain. The question of forecasting is very important in upstream industrial background because the upstream partners look to be decreased from downstream consumer demand. The supply chain forecasting system must ponder the volatility of demand. The purpose of this study is to supply the volatility models for supply chain forecasting. This study uses the model for production forecasting of Taiwanese TFT-LCD industry. The results illustrate that the proposed volatility GARCH models a meliorate the prediction accuracy for production forecasting in the supply chain.","PeriodicalId":114906,"journal":{"name":"2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Applying the volatility models for supply chain forecasting: The case of the Taiwanese TFT-LCD industry\",\"authors\":\"Y. Liang\",\"doi\":\"10.1109/IEEM.2016.7797851\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The bullwhip effect denotes that an augment in demand variability on the supply chain can enlarge its influences through an undertaking's supply chain. The question of forecasting is very important in upstream industrial background because the upstream partners look to be decreased from downstream consumer demand. The supply chain forecasting system must ponder the volatility of demand. The purpose of this study is to supply the volatility models for supply chain forecasting. This study uses the model for production forecasting of Taiwanese TFT-LCD industry. The results illustrate that the proposed volatility GARCH models a meliorate the prediction accuracy for production forecasting in the supply chain.\",\"PeriodicalId\":114906,\"journal\":{\"name\":\"2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IEEM.2016.7797851\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IEEM.2016.7797851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Applying the volatility models for supply chain forecasting: The case of the Taiwanese TFT-LCD industry
The bullwhip effect denotes that an augment in demand variability on the supply chain can enlarge its influences through an undertaking's supply chain. The question of forecasting is very important in upstream industrial background because the upstream partners look to be decreased from downstream consumer demand. The supply chain forecasting system must ponder the volatility of demand. The purpose of this study is to supply the volatility models for supply chain forecasting. This study uses the model for production forecasting of Taiwanese TFT-LCD industry. The results illustrate that the proposed volatility GARCH models a meliorate the prediction accuracy for production forecasting in the supply chain.