{"title":"通过预测顾客的在线购买来缩短交货时间:时尚行业的案例研究","authors":"J. Weingarten, S. Spinler","doi":"10.1080/10580530.2020.1814459","DOIUrl":null,"url":null,"abstract":"ABSTRACT Limited research exists that investigates how big data can be used to optimize delivery times for customers. The goal of this paper is to develop a prediction model for anticipatory shipping, which predicts customers’ online purchases with the aim of shipping products in advance, and subsequently minimizing delivery times. Results indicate that customer purchases are, to a certain extent, predictable, but anticipatory shipping comes at a high cost due to wrongly sent products.","PeriodicalId":56289,"journal":{"name":"Information Systems Management","volume":"38 1","pages":"287 - 308"},"PeriodicalIF":3.0000,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1080/10580530.2020.1814459","citationCount":"4","resultStr":"{\"title\":\"Shortening Delivery Times by Predicting Customers’ Online Purchases: A Case Study in the Fashion Industry\",\"authors\":\"J. Weingarten, S. Spinler\",\"doi\":\"10.1080/10580530.2020.1814459\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Limited research exists that investigates how big data can be used to optimize delivery times for customers. The goal of this paper is to develop a prediction model for anticipatory shipping, which predicts customers’ online purchases with the aim of shipping products in advance, and subsequently minimizing delivery times. Results indicate that customer purchases are, to a certain extent, predictable, but anticipatory shipping comes at a high cost due to wrongly sent products.\",\"PeriodicalId\":56289,\"journal\":{\"name\":\"Information Systems Management\",\"volume\":\"38 1\",\"pages\":\"287 - 308\"},\"PeriodicalIF\":3.0000,\"publicationDate\":\"2020-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1080/10580530.2020.1814459\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Information Systems Management\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1080/10580530.2020.1814459\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems Management","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1080/10580530.2020.1814459","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Shortening Delivery Times by Predicting Customers’ Online Purchases: A Case Study in the Fashion Industry
ABSTRACT Limited research exists that investigates how big data can be used to optimize delivery times for customers. The goal of this paper is to develop a prediction model for anticipatory shipping, which predicts customers’ online purchases with the aim of shipping products in advance, and subsequently minimizing delivery times. Results indicate that customer purchases are, to a certain extent, predictable, but anticipatory shipping comes at a high cost due to wrongly sent products.
期刊介绍：
Information Systems Management (ISM) is the on-going exchange of academic research, best practices, and insights based on managerial experience. The journal’s goal is to advance the practice of information systems management through this exchange.
To meet this goal, ISM features themed papers examining a particular topic. In addition to themed papers, the journal regularly publishes on the following topics in IS management.
Achieving Strategic IT Alignment and Capabilities
IT Governance
CIO and IT Leadership Roles
IT Sourcing
Planning and Managing an Enterprise Infrastructure
IT Security
Selecting and Delivering Application Solutions
Portfolio Management
Managing Complex IT Projects
E-Business Technologies
Supporting Knowledge Work
The target readership includes both academics and practitioners. Hence, submissions integrating research and practice, and providing implications for both, are encouraged.
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