Mining Customer Requirement From Helpful Online Reviews

被引：7
|
作者：
Zhang, Zhenping [1 ]
Qi, Jiayin [1 ]
Zhu, Ge [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Econ & Management, Beijing, Peoples R China
来源：
2014 SECOND INTERNATIONAL CONFERENCE ON ENTERPRISE SYSTEMS (ES) | 2014年
关键词：
online review; helpfulness; product design; conjoint analysis; Kano model; brand;
D O I：
10.1109/ES.2014.38
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
Today there are a huge quantity of online reviews available across different categories of products. The key question is how to select helpful online reviews and what can we learn from the abundant reviews. In this paper, we first conclude five categories of features to predict reviews' helpfulness from the perspective of a product designer and then present an approach based on conjoint analysis to measure customer requirement. The suggested approach are demonstrated using product data from a popular Chinese mobile phone market.
引用
收藏
页码：249 / 254
页数：6
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