Similarity Analysis of Means-End Chain Models

Umut Asan*, Hatice Kocaman

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Özet

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.

Orijinal dilİngilizce
Ana bilgisayar yayını başlığıIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
EditörlerCengiz Kahraman, Irem Ucal Sari, Basar Oztaysi, Sezi Cevik Onar, Selcuk Cebi, A. Çağrı Tolga
YayınlayanSpringer Science and Business Media Deutschland GmbH
Sayfalar152-159
Sayfa sayısı8
ISBN (Basılı)9783031397738
DOI'lar
Yayın durumuYayınlandı - 2023
EtkinlikIntelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference - Istanbul, Turkey
Süre: 22 Ağu 202324 Ağu 2023

Yayın serisi

AdıLecture Notes in Networks and Systems
Hacim758 LNNS
ISSN (Basılı)2367-3370
ISSN (Elektronik)2367-3389

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???event.eventtypes.event.conference???Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference
Ülke/BölgeTurkey
ŞehirIstanbul
Periyot22/08/2324/08/23

Bibliyografik not

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

Finansman

Acknowledgements. This research was supported by Scientific Research Projects Department of Istanbul Technical University. Project Number: SGA-2022–44093.

FinansörlerFinansör numarası
Istanbul Teknik ÜniversitesiSGA-2022–44093

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