{"title":"直接营销中的商品退货模型","authors":"James D. Hess , Glenn E. Mayhew","doi":"10.1002/(SICI)1522-7138(199721)11:2<20::AID-DIR4>3.0.CO;2-#","DOIUrl":null,"url":null,"abstract":"<div><p>Returns are a significant problem for many direct marketers. New models to more accurately explain and predict returns, as well as models that will allow accurate scoring of customers and merchandise for return propensity, would be useful in an industry where returns can exceed 20 percent of sales. We offer a split adjusted hazard model as an alternative to simple regression of return times. We explain why the hazard model is robust and offer an example of its estimation using data of actual returns from an apparel direct marketer.</p></div>","PeriodicalId":100774,"journal":{"name":"Journal of Direct Marketing","volume":"11 2","pages":"Pages 20-35"},"PeriodicalIF":0.0000,"publicationDate":"1997-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/(SICI)1522-7138(199721)11:2<20::AID-DIR4>3.0.CO;2-#","citationCount":"174","resultStr":"{\"title\":\"Modeling merchandise returns in direct marketing\",\"authors\":\"James D. Hess , Glenn E. Mayhew\",\"doi\":\"10.1002/(SICI)1522-7138(199721)11:2<20::AID-DIR4>3.0.CO;2-#\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Returns are a significant problem for many direct marketers. New models to more accurately explain and predict returns, as well as models that will allow accurate scoring of customers and merchandise for return propensity, would be useful in an industry where returns can exceed 20 percent of sales. We offer a split adjusted hazard model as an alternative to simple regression of return times. We explain why the hazard model is robust and offer an example of its estimation using data of actual returns from an apparel direct marketer.</p></div>\",\"PeriodicalId\":100774,\"journal\":{\"name\":\"Journal of Direct Marketing\",\"volume\":\"11 2\",\"pages\":\"Pages 20-35\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/(SICI)1522-7138(199721)11:2<20::AID-DIR4>3.0.CO;2-#\",\"citationCount\":\"174\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Direct Marketing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1094996897707370\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Direct Marketing","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1094996897707370","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Returns are a significant problem for many direct marketers. New models to more accurately explain and predict returns, as well as models that will allow accurate scoring of customers and merchandise for return propensity, would be useful in an industry where returns can exceed 20 percent of sales. We offer a split adjusted hazard model as an alternative to simple regression of return times. We explain why the hazard model is robust and offer an example of its estimation using data of actual returns from an apparel direct marketer.
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