Identifying small market segments with mixture regression models

Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/9627

Autoria:	Brochado, A. Martins, F. V.
Data:	2014
Título próprio:	Identifying small market segments with mixture regression models
Volume:	4
Número:	4
Paginação:	812-820
ISSN:	2047-0916
Palavras-chave:	Market segmentation Niche markets Mixture regression models Experimental design
Resumo:	The purpose of this work is to determine howwell criteria designed to help the selection of theadequate number of market segments perform inrecovering small niche market segments, in mixtureregressions of normal data. As in real world data thetrue number of market segments is unknown, theresults of this study are based on experimental data.The simulation experiment compares 27 segmentretention criteria, comprising 14 information criteriaand 13 classification-based criteria. The results revealthat AIC3, AIC4, HQ, BIC, CAIC, ICLBIC andICOMPLBIC are the best criteria in recovering smallniche segments and encourage its use.
Arbitragem científica:	Sim
Acesso:	Acesso Aberto
Aparece nas coleções:	BRU-RI - Artigos em revistas científicas internacionais com arbitragem científica

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