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Perceptual mapping of mulitiple variable batteries by plotting supplementary variables in correspondence analysis of rating data

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  • Torres, A.
  • van de Velden, M.

Abstract

In this paper we consider the use of correspondence analysis (CA) of rating data. CA of rating data allows a joint representation of the rated items (e.g. attributes or products) and individuals. However, as the number of individuals increases, the interpretation of the CA map becomes difficult. To overcome this problem, we propose a method that allows the depiction of additional variables, for example, background characteristics that may be of interest in identifying consumer segments, in the CA map. The idea we use is based on the representation of supplementary variables in ordinary CA. However, as the format of the additional variables is typically different from the rating data, a recoding is required. We illustrate our new method by means of an application to data of a product perception study for five cream soups.

Suggested Citation

  • Torres, A. & van de Velden, M., 2005. "Perceptual mapping of mulitiple variable batteries by plotting supplementary variables in correspondence analysis of rating data," Econometric Institute Research Papers EI 2005-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:1913
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    References listed on IDEAS

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    1. Carl Eckart & Gale Young, 1936. "The approximation of one matrix by another of lower rank," Psychometrika, Springer;The Psychometric Society, vol. 1(3), pages 211-218, September.
    2. Michel Velden, 2004. "Optimal Scaling of Paired Comparison Data," Journal of Classification, Springer;The Classification Society, vol. 21(1), pages 89-109, March.
    3. Dillon, William R & Frederick, Donald G & Tangpanichdee, Vanchai, 1985. "Decision Issues in Building Perceptual Product Spaces with Multi-attribute Rating Data," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 12(1), pages 47-63, June.
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