Paper Info
Title
Product portfolio identification based on association rule mining
Abstract
It has been well recognized that product portfolio planning has far-reaching impact on the company's business success in competition. In general, product portfolio planning involves two main stages, namely portfolio identification and portfolio evaluation and selection. The former aims to capture and understand customer needs effectively and accordingly to transform them into specifications of product offerings. The latter concerns how to determine an optimal configuration of these identified offerings with the objective of achieving best profit performance. Current research and industrial practice have mainly focused on the economic justification of a given product portfolio, whereas the portfolio identification issue has been received only limited attention. This article intends to develop explicit decision support to improve product portfolio identification by efficient knowledge discovery from past sales and product records. As one of the important applications of data mining, association rule mining lends itself to the discovery of useful patterns associated with requirement analysis enacted among customers, marketing folks, and designers. An association rule mining system (ARMS) is proposed for effective product portfolio identification. Based on a scrutiny into the product definition process, the article studies the fundamental issues underlying product portfolio identification. The ARMS differentiates the customer needs from functional requirements involved in the respective customer and functional domains. Product portfolio identification entails the identification of functional requirement clusters in conjunction with the mappings from customer needs to these clusters. While clusters of functional requirements are identified based on fuzzy clustering analysis, the mapping mechanism between the customer and functional domains is incarnated in association rules. The ARMS architecture and implementation issues are discussed in detail. An application of the proposed methodology and system in a consumer electronics company to generate a vibration motor portfolio for mobile phones is also presented.
Year
DOI
Venue
2005
10.1016/j.cad.2004.05.006
Computer-Aided Design
Keywords
Field
DocType
Data mining,Mass customization,Product portfolio,Association rules,Variety,Requirement management,Customer satisfaction,Product definition
Functional requirement,Customer satisfaction,Application portfolio management,Systems engineering,Mechanical engineering,Requirements analysis,Portfolio,Association rule learning,Product management,Engineering,Process management,New product development
Journal
Volume
Issue
ISSN
37
2
0010-4485
Citations 
PageRank 
References 
49
2.25
16
Authors
2
Name
Order
Citations
PageRank
Jianxin (Roger) Jiao161745.62
Yiyang Zhang21718.77