Title :
Sensory Mapping Algorithm and Enhanced Product Development
Author :
Makov, Udi E. ; Ben-Assor ; Saguy, I. Sam
Author_Institution :
Dept. of Stat., Univ. of Haifa, Haifa
Abstract :
This article describes a sensory mapping algorithm based on the simultaneous application of data mining on two sets of data, corresponding to two processes governing customers´ preferences: The sensory process, which governs the acceptance of a product as a function of hedonic variables, and the analytical process, which relate the sensory responses to objective analytical properties of the product; data mining is carried out by the means of structural equation modeling, and the final algorithm allows the prediction of purchase intent of a new product given its sensory attributes and analytical composition.
Keywords :
customer satisfaction; data mining; product development; analytical composition; customer preferences; data mining; enhanced product development; hedonic variables; purchase intent; sensory attributes; sensory mapping algorithm; sensory responses; structural equation modeling; Algorithm design and analysis; Data mining; Equations; Food products; Numerical analysis; Power system modeling; Predictive models; Product development; Statistics; Time series analysis; Data Mining; Latent Variables; Product innovation; Sensory Mapping Algorithm;
Conference_Titel :
Computer Engineering and Technology, 2009. ICCET '09. International Conference on
Conference_Location :
Singapore
Print_ISBN :
978-1-4244-3334-6
DOI :
10.1109/ICCET.2009.227
