重新定位与通用产品推荐:什么时候提供重新定位推荐是有价值的?

IF 5 3区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE
Xiang (Shawn) Wan, Anuj Kumar, Xitong Li
{"title":"重新定位与通用产品推荐:什么时候提供重新定位推荐是有价值的?","authors":"Xiang (Shawn) Wan, Anuj Kumar, Xitong Li","doi":"10.1287/isre.2020.0560","DOIUrl":null,"url":null,"abstract":"Practitioner’s Abstract Online platforms/retailers widely use collaborative filtering (CF)-based generic product recommendations to improve sales. These systems recommend products to a consumer based on the product co-views and co-purchases by other consumers on the website but do not leverage the consumer’s browsing data. Based on a field study on a U.S. fashion apparel and home goods retailer’s website, we show that informing generic CF recommendations to individual consumers’ browsing history can generate substantial additional sales. Specifically, we show that it is optimal to offer generic CF recommendations to a consumer if the consumer has not carted a product and recommend products he or she has seen in the previous sessions (retargeted recommendations) if he or she has carted a product. Our simulation results show that such recommendations could result in a 3% increase in total sales compared with conventional generic CF recommendations. Online platforms/retailers with detailed consumer browsing data can implement such recommendations to achieve higher sales.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"18 1","pages":"0"},"PeriodicalIF":5.0000,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Retargeted Versus Generic Product Recommendations: When is it Valuable to Present Retargeted Recommendations?\",\"authors\":\"Xiang (Shawn) Wan, Anuj Kumar, Xitong Li\",\"doi\":\"10.1287/isre.2020.0560\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Practitioner’s Abstract Online platforms/retailers widely use collaborative filtering (CF)-based generic product recommendations to improve sales. These systems recommend products to a consumer based on the product co-views and co-purchases by other consumers on the website but do not leverage the consumer’s browsing data. Based on a field study on a U.S. fashion apparel and home goods retailer’s website, we show that informing generic CF recommendations to individual consumers’ browsing history can generate substantial additional sales. Specifically, we show that it is optimal to offer generic CF recommendations to a consumer if the consumer has not carted a product and recommend products he or she has seen in the previous sessions (retargeted recommendations) if he or she has carted a product. Our simulation results show that such recommendations could result in a 3% increase in total sales compared with conventional generic CF recommendations. Online platforms/retailers with detailed consumer browsing data can implement such recommendations to achieve higher sales.\",\"PeriodicalId\":48411,\"journal\":{\"name\":\"Information Systems Research\",\"volume\":\"18 1\",\"pages\":\"0\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2023-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Systems Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1287/isre.2020.0560\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/isre.2020.0560","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0

摘要

在线平台/零售商广泛使用基于协同过滤(CF)的通用产品推荐来提高销售。这些系统根据其他消费者在网站上共同浏览和共同购买的产品向消费者推荐产品,但不利用消费者的浏览数据。基于对美国时尚服装和家居用品零售商网站的实地研究,我们表明,将通用CF推荐告知个人消费者的浏览历史可以产生大量的额外销售。具体来说,我们表明,如果消费者没有购买过产品,向其提供通用CF推荐是最优的,如果他或她购买过产品,则推荐他或她在之前的会议中看过的产品(重新定向推荐)。我们的模拟结果表明,与传统的通用CF推荐相比,此类推荐可能导致总销售额增加3%。拥有详细消费者浏览数据的在线平台/零售商可以实施此类推荐,以实现更高的销售额。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Retargeted Versus Generic Product Recommendations: When is it Valuable to Present Retargeted Recommendations?
Practitioner’s Abstract Online platforms/retailers widely use collaborative filtering (CF)-based generic product recommendations to improve sales. These systems recommend products to a consumer based on the product co-views and co-purchases by other consumers on the website but do not leverage the consumer’s browsing data. Based on a field study on a U.S. fashion apparel and home goods retailer’s website, we show that informing generic CF recommendations to individual consumers’ browsing history can generate substantial additional sales. Specifically, we show that it is optimal to offer generic CF recommendations to a consumer if the consumer has not carted a product and recommend products he or she has seen in the previous sessions (retargeted recommendations) if he or she has carted a product. Our simulation results show that such recommendations could result in a 3% increase in total sales compared with conventional generic CF recommendations. Online platforms/retailers with detailed consumer browsing data can implement such recommendations to achieve higher sales.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
9.10
自引率
8.20%
发文量
120
期刊介绍: ISR (Information Systems Research) is a journal of INFORMS, the Institute for Operations Research and the Management Sciences. Information Systems Research is a leading international journal of theory, research, and intellectual development, focused on information systems in organizations, institutions, the economy, and society.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信