Similarity Analysis of Means-End Chain Models

Umut Asan*, Hatice Kocaman

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The Means-End Chain Theory is a commonly used approach in marketing that aims to understand how consumers make decisions about marketing offerings by examining their thought processes. The theory is built on a three-level hierarchical structure that encompasses the attributes of a product or service, the benefits derived from these attributes, and the values associated with these benefits. Since the Means-End Chain Theory reflects the personal views of consumers, researchers need to combine and/or compare individuals’ hierarchical value maps to gain a better understanding of the market. The main issue here is how to measure the similarity of consumers’ means-end chain models and consequently how to compare them. There are a limited number of studies in the literature that address this issue, however they have notable shortcomings. In this study, a new method is proposed that considers all possible combinations of direct and indirect relationships between the abstraction levels (attributes, benefits, and values) and the weights of these combinations to calculate the distances (i.e. dissimilarities) between consumers’ hierarchical value maps. The applicability and effectiveness of the proposed method is demonstrated by an example.

Original languageEnglish
Title of host publicationIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
EditorsCengiz Kahraman, Irem Ucal Sari, Basar Oztaysi, Sezi Cevik Onar, Selcuk Cebi, A. Çağrı Tolga
PublisherSpringer Science and Business Media Deutschland GmbH
Pages152-159
Number of pages8
ISBN (Print)9783031397738
DOIs
Publication statusPublished - 2023
EventIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference - Istanbul, Turkey
Duration: 22 Aug 202324 Aug 2023

Publication series

NameLecture Notes in Networks and Systems
Volume758 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389

Conference

ConferenceIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Country/TerritoryTurkey
CityIstanbul
Period22/08/2324/08/23

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Keywords

  • Hierarchical Value Map
  • Indirect Relationship Analysis
  • Means-End Chain Theory
  • Similarity Analysis
  • Weighting

Fingerprint

Dive into the research topics of 'Similarity Analysis of Means-End Chain Models'. Together they form a unique fingerprint.

Cite this