Omker Mahalanobish, Souraj Mishra, Amlan Das, S. Misra
{"title":"Capturing Demand Transference in Retail - A Statistical Approach","authors":"Omker Mahalanobish, Souraj Mishra, Amlan Das, S. Misra","doi":"10.2139/ssrn.3227753","DOIUrl":null,"url":null,"abstract":"While an item substitution measure provides for the direction, demand transference quantifies the magnitude of demand that may get transferred to an item a) When its substitute is deleted b) When it is introduced in a store and cannibalizes on similar items. This, hence, is an important input into assortment optimization. If an item is predicted to exhibit a good extent of transference then we may be more certain of deleting it (provided, it is less than an average performer in terms of sales). Conversely, we should be careful of deleting a very incremental item (with low demand transference) – since we’ll be losing on a bulk of its demand. Note that transference is not explicitly observed, it’s latent. Our methodology explains how we capture it.","PeriodicalId":239853,"journal":{"name":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERN: Other Econometrics: Econometric & Statistical Methods - Special Topics (Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3227753","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
While an item substitution measure provides for the direction, demand transference quantifies the magnitude of demand that may get transferred to an item a) When its substitute is deleted b) When it is introduced in a store and cannibalizes on similar items. This, hence, is an important input into assortment optimization. If an item is predicted to exhibit a good extent of transference then we may be more certain of deleting it (provided, it is less than an average performer in terms of sales). Conversely, we should be careful of deleting a very incremental item (with low demand transference) – since we’ll be losing on a bulk of its demand. Note that transference is not explicitly observed, it’s latent. Our methodology explains how we capture it.