American Journal of Mathematical and Computer Modelling

| Peer-Reviewed |

Application of Fuzzy Logic in Modeling Market Brand Value

Received: 10 December 2018    Accepted: 07 February 2019    Published: 28 February 2019
Views:       Downloads:

Share This Article

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.

DOI 10.11648/j.ajmcm.20190401.11
Published in American Journal of Mathematical and Computer Modelling (Volume 4, Issue 1, March 2019)
Page(s) 1-15
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

FLC Process, Fuzzy Logic, Mathematic Modeling, Market Brand Value

References
[1] Poliščuk, E., J., (2004) Ekspertni sistemi, ETF, Podgorica.
[2] M. Čupić, B. D. Bašić, M. Golub, (2013), Neizrazito, evolucijsko i neuroračunarstvo, Zagreb.
[3] Z. Kovačević S. Bogdan, (2000), Inteligentno upravljanje sustavima, Fakultet elektrotehnike i računarstva, Univerzitet u Zagrebu, Zagreb.
[4] Z. Ma, F. Zhang, L. Yan, J. Cheng, Fuzzy Knowledge Management for the Semantic Web, XI, 275 p. 67, Springer-Verlag Berlin Heidelberg, 2014.
[5] M. Hans, (2005), Applied fuzzy aritmetican intraduction with engineering applications, Springer.
[6] A. L. Zadeh, (1973) The concept of a lingustic variable and its application to aproximate reasoning, American Elsevire Publishing Company.
[7] E. H. Mamdani, Application of fuzzy logic to approximative reasoning using linguistic systems, IEEE Transc Computer, 26 (1987) pp. 1189-1191.
[8] F. Bouslama, A. Ichikawa, Fuzzy control rules and their natural control laws. Fuzzy sets and systems, 48, 1992, 65-86.
[9] M. Braee, D. A. Rutherford, Theoretical and Linguistic Aspects of the Fuzzy Logic Controller, Automatica, Vol. 15. 1979, pp. 553-577.
[10] P. Kotler, V. Wong, J. Saunders, G. Amstrong, Osnovi marketinga, Zagreb, 2006.
[11] B. Grbac, Načela marketinga, Ekonomski fakultet, Rijeka, 2007.
[12] K. L. Keller, Strategic Brand Menagement, Building-Measuring and Managing Brand Equity, Pearson Education Limited, 2013.
[13] R. T. Rust, A. J. Zahornik, T. I. Keinigham, Returnon quality (ROQ): Making service quality financially accountable measurement, Journal of Marceting, April 1995.
[14] T. Vranešević, Upravljanje markama, Zagreb, Accent, 2007.
[15] S. F. Slater, E. M. Olson, V. K. Reddy, Strategy-Based Performance Measurement, Business Horizons, July-August, 1997, pp. 37-43.
[16] B. D. Krstić, Satisfakcija potrošača: od kvalitativnog ka kvantitativnom mjerenju, Zbornik radova "Razvoj marketinga–nove tendencije”, Ekonomski fakultet u Nišu, Novembar 2001, str. 187-198.
[17] T. Vranešević, M. Marušić, Mjerenje vrijednosti marke, Zbornik Ekonomskog fakulteta u Zagrebu, No1, 2003, pp. 129-148.
[18] A. D. Aaker, Building strong brands, New York, The Free Press, 1996.
[19] M. V. Serdar, M. (1977), Udžbenik statistike, Školska knjiga, Zagreb.
[20] N. S. Sivanandam, S. Sumathi, N. S. Deepa, (2007) Introducion to Fuzzy Logic using MATLAB, Springer/ Verlag Berlin Heidelberg.
Author Information
  • Faculty of Agriculture, University of Banja Luka, Banja Luka, Bosnia and Herzegovina

Cite This Article
  • APA Style

    Nenad Stojanovic. (2019). Application of Fuzzy Logic in Modeling Market Brand Value. American Journal of Mathematical and Computer Modelling, 4(1), 1-15. https://doi.org/10.11648/j.ajmcm.20190401.11

    Copy | Download

    ACS Style

    Nenad Stojanovic. Application of Fuzzy Logic in Modeling Market Brand Value. Am. J. Math. Comput. Model. 2019, 4(1), 1-15. doi: 10.11648/j.ajmcm.20190401.11

    Copy | Download

    AMA Style

    Nenad Stojanovic. Application of Fuzzy Logic in Modeling Market Brand Value. Am J Math Comput Model. 2019;4(1):1-15. doi: 10.11648/j.ajmcm.20190401.11

    Copy | Download

  • @article{10.11648/j.ajmcm.20190401.11,
      author = {Nenad Stojanovic},
      title = {Application of Fuzzy Logic in Modeling Market Brand Value},
      journal = {American Journal of Mathematical and Computer Modelling},
      volume = {4},
      number = {1},
      pages = {1-15},
      doi = {10.11648/j.ajmcm.20190401.11},
      url = {https://doi.org/10.11648/j.ajmcm.20190401.11},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ajmcm.20190401.11},
      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.},
     year = {2019}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - Application of Fuzzy Logic in Modeling Market Brand Value
    AU  - Nenad Stojanovic
    Y1  - 2019/02/28
    PY  - 2019
    N1  - https://doi.org/10.11648/j.ajmcm.20190401.11
    DO  - 10.11648/j.ajmcm.20190401.11
    T2  - American Journal of Mathematical and Computer Modelling
    JF  - American Journal of Mathematical and Computer Modelling
    JO  - American Journal of Mathematical and Computer Modelling
    SP  - 1
    EP  - 15
    PB  - Science Publishing Group
    SN  - 2578-8280
    UR  - https://doi.org/10.11648/j.ajmcm.20190401.11
    AB  - 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.
    VL  - 4
    IS  - 1
    ER  - 

    Copy | Download

  • Sections