The Efficiency of Heuristic Identification of Noisy Variables (Hinov) in Data Mining

Frank J. Carmone, Ali Kara

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Significant efforts in marketing research have addressed the problem of classifying people or objects into homogeneous groups. By this, it is meant the delineation of groups of consumers who show similar behavior within segments and different behavior across segments with respect to some marketing variables, such as brand preferences, product class consumption, and so on. In market segmentation applications, a large number of different sets of variables - benefits sought, psychographics, demographics, self-concept measures - have been used as criteria for segmenting markets.

Original languageEnglish (US)
Title of host publicationDevelopments in Marketing Science
Subtitle of host publicationProceedings of the Academy of Marketing Science
PublisherSpringer Nature
Pages73
Number of pages1
DOIs
StatePublished - 2015

Publication series

NameDevelopments in Marketing Science: Proceedings of the Academy of Marketing Science
ISSN (Print)2363-6165
ISSN (Electronic)2363-6173

All Science Journal Classification (ASJC) codes

  • Marketing
  • Strategy and Management

Fingerprint

Dive into the research topics of 'The Efficiency of Heuristic Identification of Noisy Variables (Hinov) in Data Mining'. Together they form a unique fingerprint.

Cite this