Application of Fuzzy Logic in Modeling Market Brand Value
American Journal of Mathematical and Computer Modelling
Volume 4, Issue 1, March 2019, Pages: 1-15
Received: Dec. 10, 2018; Accepted: Feb. 7, 2019; Published: Feb. 28, 2019
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Author
Nenad Stojanovic, Faculty of Agriculture, University of Banja Luka, Banja Luka, Bosnia and Herzegovina
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Abstract
Dominant group of factors that influence the brand market value, according to Aaker are: customer loyalty to the brand, perceived brand quality, brand familiarity and brand associations in comparison to competitors. Functional dependence between these factors and market brand value is not expressed in exact way, although these factors are quantitatively expressed with suitable index [17]. Modern technique of fuzzy logic and fuzzy sets implementation for problem solving in areas of finance and management is based on FLC (fuzzy logic control) process. Implementation of FLC process In this paper is represented in order to determine brand market value that is mathematical model is constructed using fuzzy numbers and fuzzy logic, which is used to quantitatively determine brand market value. Brand market value TV=f (L, P, K, A) is expressed depending on customer loyalty (L) towards the brand, perceived brand quality (K), brand familiarity (P) and brand association (A) received from the customers, where the measurement rates are evaluated using by fuzzy numbers.
Keywords
FLC Process, Fuzzy Logic, Mathematic Modeling, Market Brand Value
To cite this article
Nenad Stojanovic, Application of Fuzzy Logic in Modeling Market Brand Value, American Journal of Mathematical and Computer Modelling. Vol. 4, No. 1, 2019, pp. 1-15. doi: 10.11648/j.ajmcm.20190401.11
Copyright
Copyright © 2019 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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