Finding and explaining clusters of consumers using the CLV approach

被引：17

作者：

Vigneau, Evelyne ^{[1
,2
,3
]}

Endrizzi, Isabella ^{[4
]}

Qannari, El Mostafa ^{[1
,2
,3
]}

机构：

[1] USC Sensometr & Chemometr Lab, ONIRIS, F-44322 Nantes, France

[2] INRA, F-44316 Nantes, France

[3] Univ Nantes, Le Mans, France

[4] IASMA Res & Innovat Ctr, Fdn Edmund Mach, Food Qual & Nutr Area, I-38010 S Michele, Italy

来源：

FOOD QUALITY AND PREFERENCE | 2011年 / 22卷 / 08期

关键词：

Cluster analysis; Segmentation of consumers; L-structured data; L-PLSR; VARIABLES;

D O I：

10.1016/j.foodqual.2011.01.004

中图分类号：

TS2 [食品工业];

学科分类号：

0832 ;

摘要：

In consumer studies, liking scores for a set of products are usually collected from a panel of consumers. When additional information is available both on products and consumers, the data can be organized in an L-shaped structure. The CLV (Clustering around Latent Variables) approach which was originally designed to identify segments of consumers according to their preferences is extended in order to take account of product characteristics data or/and consumer background information. (C) 2011 Elsevier Ltd. All rights reserved.

引用

页码：705 / 713

页数：9

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