The Presentation of Changes in Preferences by Dynamic Scaling

Artur Zaborski

doi:10.18778/0208-6018.322.06

Authors

Artur Zaborski Wroclaw University of Economics, Department of Econometrics and Computer Science

DOI:

https://doi.org/10.18778/0208-6018.322.06

Keywords:

preference analysis, similarity matrix, dynamic scaling, Procrustes analysis

Abstract

Dynamic scaling is a set of methods in which the geometrical representation of the similarity data for T different time periods is made. This article presents the use of two-dynamic scaling methods for studying changes in the preferences. In the first method the location of points on the perceptual map is made on the basis of the super-dissimilarity matrix. In the second method multidimensional scaling for the respective periods is carried out and the obtained configurations are matched by transformations preserving the proportions of distances between points. The presentation of the methods is illustrated by an empirical example in which calculations were performed with use of SPSS and New MDSX packages.

Downloads

Download data is not yet available.

References

Borg I., Groenen P. (2005), Modern multidimensional scaling. Theory and applications. Second Edition, Springer-Verlag, New York.
Google Scholar

Chino N. (1978), A graphical technique for representing the asymmetric relationship between N objects, “Behaviometrika”, no. 5, pp. 23–40.
Google Scholar

Cox T.F., Cox M.A.A. (2001), Multidimensional Scaling. Second Edition, Chapman and Hall, London.
Google Scholar

DeSarbo W. S., Johnson M.D., Manrai A.K., Manrai L.A., Edward E.A. (1992), TSCALE: A New Multidimensional Scaling Procedure Based on Tversky’s Contrast Model, “Psychometrika”, 57, pp. 43–69.
Google Scholar

Harshman R.A., Green PP.E., Wind Y., Lundy M.E. (1982), A model for the analysis of asymmetric data in marketing research, “Marketing Science”, vol. I, no. 2, pp. 205–242.
Google Scholar

Holyoak K.J., Gordon PP.C. (1983), Social reference points, “Journal of Personality and Social Psychology”, no. 44, pp. 881–887.
Google Scholar

Okada A., Imaizumi T. (1997), Asymmetric multidimensional scaling of two-mode three-way proximities, “Journal of Classification”, no. 14, pp. 195–224.
Google Scholar

Okada A., Imaizumi T. (2007), Multidimensional scaling of asymmetric proximities with a dominance point, “Advances in Data Analysis Studies in Classification, Data Analysis, and Knowledge Organization”, (red.) R. Decker, H.J. Lenz, Springer-Verlag, Berlin, Heidelberg, pp. 307–318.
Google Scholar

Tversky A., Gati I. (1982), Features of similarity, “Psychological Review”, no. 89, pp. 123–154.
Google Scholar

Zaborski A. (2007), Przegląd wybranych modeli różnic indywidualnych w skalowaniu wielowymiarowym, Prace Naukowe Akademii Ekonomicznej we Wrocławiu, nr 1151, s. 9–18.
Google Scholar

Zielman B., Heiser W.J. (1996), Analysis of Asymmetry by a Slide-Vector, “Psychometrika”, 58, pp. 101–114.
Google Scholar