Skip navigation
Logo
User training | Reference and search service

Library catalog

Retrievo
EDS
b-on
More
resources
Content aggregators
Please use this identifier to cite or link to this item:

acessibilidade

http://hdl.handle.net/10071/9627
acessibilidade
Title: Identifying small market segments with mixture regression models
Authors: Brochado, A.
Martins, F. V.
Keywords: Market segmentation
Niche markets
Mixture regression models
Experimental design
Issue Date: 2014
Publisher: ExcellingTech Publisher
Abstract: 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.
Peer reviewed: Sim
URI: https://ciencia.iscte-iul.pt/public/pub/id/21931
http://hdl.handle.net/10071/9627
ISSN: 2047-0916
Publisher version: http://ojs.excelingtech.co.uk/index.php/IJLTFES/article/view/812/615
Appears in Collections:BRU-RI - Artigo em revista científica internacional com arbitragem científica

Files in This Item:
acessibilidade
File Description SizeFormat 
publisher_version_1045_3708_1_PB.pdf287.21 kBAdobe PDFView/Open


FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpace
Formato BibTex MendeleyEndnote Currículo DeGóis 

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.