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.
Vigneau, E.; Endrizzi, I.; Qannari, E.M. (2011). Finding and explaining clusters of consumers using the CLV approach. FOOD QUALITY AND PREFERENCE, 22 (8): 705-713. doi: 10.1016/j.foodqual.2011.01.004 handle: http://hdl.handle.net/10449/20434
Finding and explaining clusters of consumers using the CLV approach
Endrizzi, Isabella;
2011-01-01
Abstract
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.
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