Sensory analysis in the food industry as a tool for marketing decisions
AbstractIn the food industry, sensory analysis can be useful to direct marketing decisions concerning not only products, for example product positioning with respect to competitors, but also market segmentation, customer relationship management, advertising strategies and price policies. In this paper we show how interesting information useful for marketing management can be obtained by combining the results from cub models and algorithmic data mining techniques (specifically, variable importance measurements from Random Forest). A case study on sensory evaluation of different varieties of Italian espresso is presented. Copyright Springer-Verlag Berlin Heidelberg 2012
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Bibliographic InfoArticle provided by Springer in its journal Advances in Data Analysis and Classification.
Volume (Year): 6 (2012)
Issue (Month): 4 (December)
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Web page: http://www.springer.com/statistics/statistical+theory+and+methods/journal/11634
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- Cicia, Gianni & Corduas, Marcella & Del Giudice, Teresa & Piccolo, Domenico, 2010.
"Valuing Consumer Preferences with the CUB Model: A Case Study of Fair Trade Coffee,"
International Journal on Food System Dynamics,
International Center for Management, Communication, and Research, vol. 1(1).
- Cicia, Gianni & Corduas, Marcella & Del Giudice, Teresa & Piccolo, Domenico, 2009. "Valuing Consumer Preferences with the CUB Model: A Case Study of Fairtrade Coffee," 2009 International European Forum, February 15-20, 2009, Innsbruck-Igls, Austria 59209, International European Forum on System Dynamics and Innovation in Food Networks.
- D'Elia, Angela & Piccolo, Domenico, 2005. "A mixture model for preferences data analysis," Computational Statistics & Data Analysis, Elsevier, vol. 49(3), pages 917-934, June.
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