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Marketing Letters

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01-03-2011

Deriving joint space positioning maps from consumer preference ratings

Authors: Wayne S. DeSarbo, Joonwook Park, Vithala R. Rao

Published in: Marketing Letters | Issue 1/2011

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Abstract

Joint space multidimensional scaling maps are often utilized for positioning analyses and are estimated on survey samples of consumer preferences, choices, considerations, or intentions so as to provide a concise spatial depiction of the competitive landscape including relevant dimensions or attributes, competing brands, and consumers in the same joint space representation. Care has to be given concerning the underlying scale properties of such survey data so as not to distort the resulting joint space positioning map. We present a new joint space multidimensional scaling procedure for positioning analyses for displaying the structure in such survey data when such common ordered successive category measurement scales such as Likert, Edwards, semantic differential, etc., are employed. We present the technical details of this stochastic ordered preference multidimensional scaling vector model as well as the maximum likelihood estimation-based algorithm devised for parameter estimation. Favorable comparisons are made with several existent multidimensional scaling methods in representing the internal structure for such data in marketing positioning studies. An actual commercial positioning application concerning large sports utility vehicles consideration to buy judgments is presented with predictive validation comparisons with other multidimensional scaling joint space procedures.

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This assumption is possible given the scalar product form of M _ij to be introduced has multiplicative scale indeterminacies (as well as others).

We specify a vector MDS model for two reasons. Unlike many unfolding MDS model solutions, vector model solutions do not typically result in degenerate solutions which are either uninterruptable or useless from a manager’s perspective. Unlike many correspondence analyses solutions, the solutions derived from our vector model allow the user to directly interpret geometric relationships between consumer and brand representations in the derived space.

We ran several simulations with synthetic data to test the performance of the estimation algorithm in recovering joint space configurations, alternative model selection criteria, and various comparisons with a host of alternative two-way joint space methods including MDPREF (Carroll 1980), CATPCA (Gifi 1990), PREFSCAL (Busing et al. 2005), ALSCAL (Takane et al. 1977query), and Correspondence analysis (queryBenzécri 1992). Significant improvement was witnessed with respect to both overall fit and configuration recovery in comparison to these alternative procedures. Interested readers can contact the authors for details.

Actually, the scale measured consideration to buy, lease, or finance the vehicle.

Note, running the data in ALSCAL as non-metric and row conditional failed to produce an unfolding MDS representation given the huge number of ties encountered in the data.

Interested readers can contact the authors for details.

Adams, E., & Messick, S. (1958). An axiomatic formulation and generalization of successive intervals scaling. Psychometrika, 23, 355–368.CrossRef

Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, 19, 716–723.CrossRef

Benzécri, J. P. (1992). Correspondence analysis handbook. New York: Marcel Dekker.

Borg, I., & Groenen, P. (2005). Modern multidimensional scaling: theory and application (2nd ed.). New York: Springer-Verlag.

Bozdogan, H. (1987). Model selection and Akaike’s information criterion (AIC): the general theory and its analytical extensions. Psychometrika, 52, 345–370.CrossRef

Busing, F. M. T. A., Groenen, P. J. F., & Heiser, W. (2005). Avoiding degeneracy in multidimensional unfolding by penalizing on the coefficient of variation. Psychometrika, 70, 71–98.CrossRef

Carroll, J. D. (1980). Models and methods for multidimensional analysis of preferential choice (or other dominance) data. In E. D. Lantermann & H. Feger (Eds.), Similarity and choice. Vienna: Hans Huber Publishers.

Chang, J., & Carroll, J. D. (1989). A short guide to MDPREF: multidimensional analysis of preference data. In P. E. Green, F. J. Carmone, & S. M. Smith (Eds.), Multidimensional scaling: concepts and applications. Newton, MA: Allyn and Bacon.

Cliff, N. (1973). Scaling. Annual Review of Psychology, 24, 473–506.CrossRef

Coombs, C. H., Dawes, R. M., & Tversky, A. (1970). Mathematical psychology. Englewood Cliff, New Jersey: Prentice Hall.

Crawford, M., & Di Benedetto, A. (2008). New products management (9th ed.). Boston, MA: McGraw Hill.

DeSarbo, W. S., & Rao, V. R. (1986). A constrained unfolding methodology for product positioning. Marketing Science, 5, 1–19.CrossRef

DeSarbo, W. S., Park, J., & Scott, C. (2008). A model-based approach for visualizing the dimensional structure of ordered successive categories data. Psychometrika, 73, 1–20.CrossRef

DeSarbo, W. S., Grewal, R., & Scott, C. (2008). A clusterwise bilinear multidimensional scaling methodology for simultaneous segmentation and positioning. Journal of Marketing Research, 45, 280–292.CrossRef

Doyle, P. (1975). Brand positioning using multidimensional scaling. European Journal of Marketing, 9, 20–34.CrossRef

Galanter, E., & Messick, S. (1961). The relation between category and magnitude scales of loudness. Psychological Review, 68, 363–372.CrossRef

Gifi, A. (1990). Nonlinear multivariate analysis. New York: Wiley.

Gilbert, J., & Nocedal, J. (1992). Global convergence properties of conjugate gradient methods for optimization. SIAM Journal on Optimization, 2, 21–42.CrossRef

Greene, W. H. (2003). Econometric analysis (5th ed.). Upper Saddle River, NJ: Prentice Hall.

Hooley, G. J., Piercy, N. F., & Nicoulaud, B. (2008). Market strategy and competitive positioning (4th ed.). London, UK: Pearson Education.

J. D. Power and Associates (2003). Sales report: Highligths. Available at http://www.jdpa.com/library/publications/srSample/index.htm.

Keller, K. L. (2008). Strategic brand management: building, measuring and managing brand equity (3rd ed.). Upper Saddle, N.J: Pearson Prentice Hall.

Kotler, P., & Keller, K. L. (2009). Marketing management (13th ed.). Upper Saddle River, N.J: Prentice Hall.

Kumar, V., & Leone, R. (1991). Nonlinear mapping: an alternative to multidimensional scaling for product positioning. Journal of the Academy of Marketing Science, 19, 165–176.CrossRef

Luce, R. D., & Edwards, W. (1958). The derivation of subjective scales from just noticeable differences. Psychological Review, 65, 227–237.CrossRef

Maurin, M. (1983). Another least-squares solution for the successive intervals following Adams and Messick. 3rd European meeting of the Psychometric Society. Jouy-en-Josas.

Messick, S. J. (1956). An empirical evaluation of multidimensional successive categories. Psychometrika, 21, 367–375.CrossRef

Myers, J. H. (1996). Segmentation and positioning for strategic marketing decisions. Chicago, IL: American Marketing Association.

Natter, M., Mild, A., Wagner, U., & Taudes, A. (2008). Planning new tariffs at tele.ring: the application and impact of an integrated segmentation, targeting, and positioning tool. Marketing Science, 27, 600–609.CrossRef

Nocedal, J., & Wright, S. J. (1999). Numerical optimization. New York: Springer.CrossRef

Rust, R. T., Simester, D., Brodie, R., & Nilikant, V. (1995). Model selection criteria: An investigation of relative accuracy, posterior probabilities, and combinations of criteria. Management Science, 41, 222–233.CrossRef

Schönemann, P. H., & Tucker, L. R. (1967). A maximum likelihood solution for the method of successive intervals allowing for unequal stimulus dispersions. Psychometrika, 32, 403–418.CrossRef

Stevens, S. S. (1966). A metric for the social consensus. Science, 151, 530–541.CrossRef

Stevens, S. S. (1971). Issues in psychophysics. Psychological Review, 78, 426–450.CrossRef

Takane, Y. (1981). Multidimensional successive categories scaling: a maximum likelihood method. Psychometrika, 46, 9–28.CrossRef

Takane, Y., & Carroll, J. D. (1981). Maximum likelihood multidimensional scaling from directional rankings of similarities. Psychometrika, 46, 389–406.CrossRef

Torgerson, W. S. (1952). Multidimensional scaling: I. Theory and method. Psychometrika, 17, 401–419.CrossRef

Torgerson, W. S. (1958). Theory and methods of scaling. New York: Wiley.

Urban, G. L., & Hauser, J. R. (1993). Design and marketing of new products (2nd ed.). NJ: Prentice Hall.

Wind, Y. (1980). Product policy. Boston, MA: Addison-Wesley.

Zinnes, J. L., & Wolff, R. P. (1977). Single and multidimensional same-different judgments. Journal of Mathematical Psychology, 16, 30–50.CrossRef

Title: Deriving joint space positioning maps from consumer preference ratings
Authors: Wayne S. DeSarbo
Joonwook Park
Vithala R. Rao
Publication date: 01-03-2011
Publisher: Springer US
Published in: Marketing Letters / Issue 1/2011
Print ISSN: 0923-0645
Electronic ISSN: 1573-059X
DOI: https://doi.org/10.1007/s11002-009-9100-7

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