Segmenting retail markets on store image using a consumer-based methodology

Various approaches to segmenting retail markets based on store image are reviewed, including methods that have not yet been applied to retailing problems. It is argued that a recently developed segmentation technique, fuzzy clusterwise regression analysis (FCR), holds high potential for store-image...

Full description

Saved in:
Bibliographic Details
Published in:Journal of retailing 1991-10, Vol.67 (3), p.300
Main Authors: Steenkamp, Jan-Benedict E.M, Wedel, Michel
Format: Article
Language:English
Subjects:
Consumer behavior
Leerstoelgroep Marktkunde en consumentengedrag
Market segmentation
Market share
Marketing
Marketing and Consumer Behaviour
Marktkunde en Consumentengedrag
Mathematical models
Methods
Regression analysis
Retail industry
Retail stores
Stores
Studies
Testing
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Various approaches to segmenting retail markets based on store image are reviewed, including methods that have not yet been applied to retailing problems. It is argued that a recently developed segmentation technique, fuzzy clusterwise regression analysis (FCR), holds high potential for store-image segmentation research. FCR clusters consumers into segments and simultaneously provides statistically derived store image attribute importances for each segment. Due to the simultaneous segmentation and estimation procedures, FCR can be used even in situations where the number of store image attributes exceeds the number of stores that are evaluated by a subject. FCR accommodates nonoverlapping, overlapping, and fuzzy clustering in an integrated consumer-based framework. The usefulness of FCR is empirically investigated in the context of store image for retailers selling meat in the Netherlands. FCR is also compared to a more traditional segmentation approach.
ISSN:0022-4359
1873-3271