Dynamic customer preference analysis for product portfolio identification using sequential pattern mining | |
Yu, Li1; Zhang, Zaifang2; Shen, Jin3 | |
刊名 | INDUSTRIAL MANAGEMENT & DATA SYSTEMS
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2017 | |
卷号 | 117期号:2页码:365-381 |
关键词 | Customer need Product family design Product portfolio identification Product specification Sequential pattern mining |
ISSN号 | 0263-5577 |
DOI | 10.1108/IMDS-12-2015-0496 |
英文摘要 | Purpose - In the initial stage of product design, product portfolio identification (PPI) aims to translate customer needs (CNs) into product specifications (PSs). This is an essential task, since understanding what customers really want is at the center of product design. However, design information is incomplete and design knowledge is minimal during this stage. Furthermore, PPI is often a confusing and frustrating task, especially when customer preferences are changing rapidly. To facilitate the task, the purpose of this paper is to capture the time-sensitive mapping relationship between CNs and PSs. |
WOS研究方向 | Computer Science ; Engineering |
语种 | 英语 |
出版者 | EMERALD GROUP PUBLISHING LTD |
WOS记录号 | WOS:000399073200007 |
内容类型 | 期刊论文 |
源URL | [http://10.2.47.112/handle/2XS4QKH4/1114] ![]() |
专题 | 上海财经大学 |
通讯作者 | Yu, Li |
作者单位 | 1.Shanghai Univ Finance & Econ, Shanghai Key Lab Financial Informat Technol, Shanghai, Peoples R China; 2.Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai, Peoples R China; 3.Shanghai Dianji Univ, Sch Business, Shanghai, Peoples R China |
推荐引用方式 GB/T 7714 | Yu, Li,Zhang, Zaifang,Shen, Jin. Dynamic customer preference analysis for product portfolio identification using sequential pattern mining[J]. INDUSTRIAL MANAGEMENT & DATA SYSTEMS,2017,117(2):365-381. |
APA | Yu, Li,Zhang, Zaifang,&Shen, Jin.(2017).Dynamic customer preference analysis for product portfolio identification using sequential pattern mining.INDUSTRIAL MANAGEMENT & DATA SYSTEMS,117(2),365-381. |
MLA | Yu, Li,et al."Dynamic customer preference analysis for product portfolio identification using sequential pattern mining".INDUSTRIAL MANAGEMENT & DATA SYSTEMS 117.2(2017):365-381. |
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