Export Publication

The publication can be exported in the following formats: APA (American Psychological Association) reference format, IEEE (Institute of Electrical and Electronics Engineers) reference format, BibTeX and RIS.

Export Reference (APA) 
Fonseca, J. R. S. & Cardoso, M. G. M. S. (2005). Retail clients latent segments. In Bento, C., Cardoso, A., and Dias, G. (Ed.), Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science. (pp. 348-358). Covilhã, Portugal: Springer.
Export Reference (IEEE) 
F. J.R.S. and M. M. Cardoso,  "Retail clients latent segments", in Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science, Bento, C., Cardoso, A., and Dias, G., Ed., Covilhã, Portugal, Springer, 2005, vol. 3808, pp. 348-358
Export BibTeX 
@inproceedings{j.r.s.2005_1716243071296,
	author = "Fonseca, J. R. S. and Cardoso, M. G. M. S.",
	title = "Retail clients latent segments",
	booktitle = "Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science",
	year = "2005",
	editor = "Bento, C., Cardoso, A., and Dias, G.",
	volume = "3808",
	number = "",
	series = "",
	doi = "10.1007/11595014_35",
	pages = "348-358",
	publisher = "Springer",
	address = "Covilhã, Portugal",
	organization = "",
	url = "https://link.springer.com/book/10.1007/11595014"
}
Export RIS 
TY  - CPAPER
TI  - Retail clients latent segments
T2  - Progress in Artificial Intelligence. EPIA 2005. Lecture Notes in Computer Science
VL  - 3808
AU  - Fonseca, J. R. S.
AU  - Cardoso, M. G. M. S.
PY  - 2005
SP  - 348-358
SN  - 0302-9743
DO  - 10.1007/11595014_35
CY  - Covilhã, Portugal
UR  - https://link.springer.com/book/10.1007/11595014
AB  - Latent Segments Models (LSM) are commonly used as an approach for market segmentation. When using LSM, several criteria are available to determine the number of segments. However, it is not established which criteria are more adequate when dealing with a specific application. Since most market segmentation problems involve the simultaneous use of categorical and continuous base variables, it is particularly useful to select the best criteria when dealing with LSM with mixed type base variables. We first present an empirical test, which provides the ranking of several information criteria for model selection based on ten mixed data sets. As a result, the ICL-BIC, BIC, CAIC and L criteria are selected as the best performing criteria in the estimation of mixed mixture models. We then present an application concerning a retail chain clients' segmentation. The best information criteria yield two segments: Preferential Clients and Occasional Clients.
ER  -