Jason Acimovic, Francisco Erize, K. Hu, Douglas J. Thomas, Jan A. Van Mieghem
{"title":"产品生命周期数据集:个人电脑每周订单的原始和清理数据","authors":"Jason Acimovic, Francisco Erize, K. Hu, Douglas J. Thomas, Jan A. Van Mieghem","doi":"10.2139/ssrn.3042681","DOIUrl":null,"url":null,"abstract":"We provide and describe a data set of N=8935 weekly, normalized customer orders over the entire product life cycle for 170 Dell computer products sold in North America over a three and a half year period, from 2013-2016. Total orders for these products exceeded 4 million units and well over a billion dollars in revenue. While Dell is historically known for fulfilling customer demand with a build to-order approach, the products in this data set were designated as build-to-stock products. There are three elements in the data that, depending on the research application, researchers may want to identify or mitigate. First, some products have seemingly anomalous orders representing one-time purchases from large customers. Second, there are negative values for some products representing order cancellations. Third, end-of-life sales may be significantly influenced by management action. We present approaches for cleaning the data to address these issues.","PeriodicalId":433005,"journal":{"name":"Econometrics: Data Collection & Data Estimation Methodology eJournal","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Product Life Cycle Data-Set: Raw and Cleaned Data of Weekly Orders for Personal Computers\",\"authors\":\"Jason Acimovic, Francisco Erize, K. Hu, Douglas J. Thomas, Jan A. Van Mieghem\",\"doi\":\"10.2139/ssrn.3042681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We provide and describe a data set of N=8935 weekly, normalized customer orders over the entire product life cycle for 170 Dell computer products sold in North America over a three and a half year period, from 2013-2016. Total orders for these products exceeded 4 million units and well over a billion dollars in revenue. While Dell is historically known for fulfilling customer demand with a build to-order approach, the products in this data set were designated as build-to-stock products. There are three elements in the data that, depending on the research application, researchers may want to identify or mitigate. First, some products have seemingly anomalous orders representing one-time purchases from large customers. Second, there are negative values for some products representing order cancellations. Third, end-of-life sales may be significantly influenced by management action. We present approaches for cleaning the data to address these issues.\",\"PeriodicalId\":433005,\"journal\":{\"name\":\"Econometrics: Data Collection & Data Estimation Methodology eJournal\",\"volume\":\"2014 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Econometrics: Data Collection & Data Estimation Methodology eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3042681\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Econometrics: Data Collection & Data Estimation Methodology eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3042681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Product Life Cycle Data-Set: Raw and Cleaned Data of Weekly Orders for Personal Computers
We provide and describe a data set of N=8935 weekly, normalized customer orders over the entire product life cycle for 170 Dell computer products sold in North America over a three and a half year period, from 2013-2016. Total orders for these products exceeded 4 million units and well over a billion dollars in revenue. While Dell is historically known for fulfilling customer demand with a build to-order approach, the products in this data set were designated as build-to-stock products. There are three elements in the data that, depending on the research application, researchers may want to identify or mitigate. First, some products have seemingly anomalous orders representing one-time purchases from large customers. Second, there are negative values for some products representing order cancellations. Third, end-of-life sales may be significantly influenced by management action. We present approaches for cleaning the data to address these issues.