An Information Theoretic Framework for Exploratory Multivariate Market Segmentation Research *

An Information Theoretic Framework for Exploratory Multivariate Market Segmentation Research * State‐of‐the‐art market segmentation often involves simultaneous consideration of multiple and overlapping variables. These variables are studied to assess their relationships, select a subset of variables which best represent the subgroups (segments) within a market, and determine the likelihood of membership of a given individual in a particular segment. Such information, obtained in the exploratory phase of a multivariate market segmentation study, leads to the construction of more parsimonious models. These models have less stringent data requirements while facilitating substantive evaluation to aid marketing managers in formulating more effective targeting and positioning strategies within different market segments. This paper utilizes the information‐theoretic (IT) approach to address several issues in multivariate market segmentation studies. A marketing data set analyzed previously is employed to examine the suitability and usefulness of the proposed approach (12). Some useful extensions of the IT framework and its applications are also discussed. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Decision Sciences Wiley

An Information Theoretic Framework for Exploratory Multivariate Market Segmentation Research *

Loading next page...
 
/lp/wiley/an-information-theoretic-framework-for-exploratory-multivariate-market-5sRowR0d7z
Publisher
Wiley
Copyright
Copyright © 1991 Wiley Subscription Services, Inc., A Wiley Company
ISSN
0011-7315
eISSN
1540-5915
DOI
10.1111/j.1540-5915.1991.tb01289.x
Publisher site
See Article on Publisher Site

Abstract

State‐of‐the‐art market segmentation often involves simultaneous consideration of multiple and overlapping variables. These variables are studied to assess their relationships, select a subset of variables which best represent the subgroups (segments) within a market, and determine the likelihood of membership of a given individual in a particular segment. Such information, obtained in the exploratory phase of a multivariate market segmentation study, leads to the construction of more parsimonious models. These models have less stringent data requirements while facilitating substantive evaluation to aid marketing managers in formulating more effective targeting and positioning strategies within different market segments. This paper utilizes the information‐theoretic (IT) approach to address several issues in multivariate market segmentation studies. A marketing data set analyzed previously is employed to examine the suitability and usefulness of the proposed approach (12). Some useful extensions of the IT framework and its applications are also discussed.

Journal

Decision SciencesWiley

Published: Jul 1, 1991

References

  • The real and illusory virtues of entropy‐based measures for business and economic analysis
    Horowitz, Horowitz; Horowitz, Horowitz

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create folders to
organize your research

Export folders, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off