Developing Marketing Strategies Based on Taste Analysis of Mineral Water
This research concerns with the development of marketing strategy of mineral water based on people’s taste preference by analyzing taste components of mineral water. A two-dimensional analysis has been used in classifying tastes’ data. The characteristics of data are recognized in tastes of mineral water by correlation analysis. A combination of Principal Component Analysis and Self-organizing Map is applied to classify the tastes of mineral water. Some marketing strategies are concluded after the evaluation.
KeywordsTaste analysis mineral water soft computing model SOM Kansei Engineering
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- 1.Abdi, H., Williams, L.J.: Principal Component Analysis, Wile Interdisciplinary Reviews. Computational Statistics 2(4), 433–459 (2010)Google Scholar
- 3.Beullens, K., Kirsanov, D., Irudayaraj, J., Rudnitskaya, A., Legin, A., Nicolai, B.M., Lammertyn, J.: The electronic tongue and ATR-FTIR for rapid detection of sugers and acids in tomatoes. Sensors and Actuators, 107–115 (2006)Google Scholar
- 4.Beullens, K., Meszaros, P., Vermeir, S., Kirsanov, D., Legin, A., Buysens, S., Cap, N., Nicolaı, B.M., Lammertyn, J.: Analysis of tomato taste using two types of electronic tongues. Sensors and Actuators, 10–17 (2008)Google Scholar
- 6.He, W., Hu, X., Zhao, L., Liao, X., Zhang, Y., Zhang, M., Wu, J.: Evaluation of Chinese tea by the electronic tongue: Correlation with sensory properties and classification according to geographical origin and grade level. Food Research International, 1462–1467 (2009)Google Scholar
- 7.Kara, D.: Evaluation of trace metal concentrations in some herbs and herbal teas by principal component analysis. Food Chemistry, 347–354 (2009)Google Scholar
- 8.Knox, S., de Chernatory, L.: The application of multi-attribute modeling techniques to the mineral water market. The Quarterly Review of Marketing, School Working Paper SWP 35/ 89Google Scholar
- 10.Ultsch, A.: U*-Matrix: a Tool to visualize Clusters in high dimensional Data. Technical Report 36, CS Department, Philipps-University Marburg, Germany (2004)Google Scholar
- 12.Watada, J., Le, Y., Ogura, M., Shibata, M., Fukuda, T.: Building the Marketing Strategies Based on Kansei of Tastes. In: Proceedings of Kansei Engineering Conference at Tokyo, September 3-5 (2011) (in Japanese)Google Scholar
- 13.Taste & Aroma Strategic Research Institute (December 1, 2011), http://www.mikaku.jp
- 14.The Mineral Water Association of Japan (January 26, 2012), http://minekyo.net/index.php