{"title":"基于ARMA模型的汽车后市场需求预测","authors":"Yun Chen, Heng Zhao, Li Yu","doi":"10.1109/ICMSS.2010.5577867","DOIUrl":null,"url":null,"abstract":"The rapid development of automobile industry in China promotes the fast growth of the automotive aftermarket. Facing the fierce market competition, it is necessary for a company to forecast the demand for auto spare parts. This paper proposes a method based on ARMA model to fulfill the important task. The accuracy and ease of use of the method is illustrated through the case study with the sales data of a 4s shop in Shanghai.","PeriodicalId":329390,"journal":{"name":"2010 International Conference on Management and Service Science","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Demand Forecasting in Automotive Aftermarket Based on ARMA Model\",\"authors\":\"Yun Chen, Heng Zhao, Li Yu\",\"doi\":\"10.1109/ICMSS.2010.5577867\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid development of automobile industry in China promotes the fast growth of the automotive aftermarket. Facing the fierce market competition, it is necessary for a company to forecast the demand for auto spare parts. This paper proposes a method based on ARMA model to fulfill the important task. The accuracy and ease of use of the method is illustrated through the case study with the sales data of a 4s shop in Shanghai.\",\"PeriodicalId\":329390,\"journal\":{\"name\":\"2010 International Conference on Management and Service Science\",\"volume\":\"20 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Management and Service Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICMSS.2010.5577867\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Management and Service Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICMSS.2010.5577867","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Demand Forecasting in Automotive Aftermarket Based on ARMA Model
The rapid development of automobile industry in China promotes the fast growth of the automotive aftermarket. Facing the fierce market competition, it is necessary for a company to forecast the demand for auto spare parts. This paper proposes a method based on ARMA model to fulfill the important task. The accuracy and ease of use of the method is illustrated through the case study with the sales data of a 4s shop in Shanghai.
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