An affective approach to developing marketing strategies of mineral water

Junzo Watada, Le Yu, Munenori Shibata, Marzuki Khalid

    Research output: Contribution to journalArticle

    1 Citation (Scopus)

    Abstract

    This study is concerned with the development of marketing strategies for mineral water based on consumers' taste preferences, by analyzing the taste components of mineral water. In this study, we used a twodimensional analysis to classify taste data. We conducted a correlation analysis to identify the characteristics of taste data. We applied a combination of principal component analysis and self-organizing map to classify mineral water tastes. Based on this evaluation, we identified some marketing strategies in the conclusion. According to this study, the taste of mineral water is not determined by the origin and is not influenced by the hardness of the water.

    Original languageEnglish
    Pages (from-to)514-520
    Number of pages7
    JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
    Volume16
    Issue number4
    Publication statusPublished - 2012 Jun

    Fingerprint

    Marketing
    Minerals
    Water
    Self organizing maps
    Principal component analysis
    Hardness

    Keywords

    • Kansei engineering
    • Mineral water
    • Soft computing model
    • SOM
    • Taste analysis

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computer Vision and Pattern Recognition
    • Human-Computer Interaction

    Cite this

    An affective approach to developing marketing strategies of mineral water. / Watada, Junzo; Yu, Le; Shibata, Munenori; Khalid, Marzuki.

    In: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol. 16, No. 4, 06.2012, p. 514-520.

    Research output: Contribution to journalArticle

    Watada, Junzo ; Yu, Le ; Shibata, Munenori ; Khalid, Marzuki. / An affective approach to developing marketing strategies of mineral water. In: Journal of Advanced Computational Intelligence and Intelligent Informatics. 2012 ; Vol. 16, No. 4. pp. 514-520.
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