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Preference mapping of conjoint-based profiles: An INDSCAL approach

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Abstract

This article describes an approach in which conjoint methodology and multidimensional scaling can be fruitfully applied, in tandem, to the measurement and representation of preference data for factorially designed profiles. The approach is described and applied to an illustrative data set. We conclude the article with a brief discussion of possible extensions of the approach and additional research needs.

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References

  • Albers, S. and K. Brockhoff. 1977. “A Procedure for New Product Positioning in an Attribute Space.”European Journal of Operations Research 1: 230–281.

    Article  Google Scholar 

  • Bloxom, Bruce. 1978. “Constrained Multidimensional Scaling in N Space.”Psychometrika 43: 25–38.

    Article  Google Scholar 

  • Carroll, J. Douglas. 1980. “Models and Methods for Multidimensional Analyses of Preferential Choice (or Other Dominance) Data.” InSimilarity and Choice. Eds. E. D. Lantermann and H. Feger. Bern, Stuttgart, and Vienna: Hans Huber Publishers.

    Google Scholar 

  • — and J.J. Chang. 1970. “Analysis of Individual Differences in Multidimensional Scaling via an N-Way Generalization of ‘Eckart-Young’ Decomposition.’Psychometrika 35: 283–320.

    Article  Google Scholar 

  • Carroll, J. Douglas, Paul E. Green, and Frank J. Camone. 1976. “CANDELINC: A New Method for Multidimensional Analysis with Constrained Solutions.” Paper presented at the meeting of the International Congress of Psychology, Paris, France, July.

  • —, S. Pruzansky, and J.B. Kruskal. 1980. “CANDELINC: A General Approach to Multidimensional Analysis of Many-Way Arrays with Linear Constraints on Parameters.”Psychometrika 45 (March): 3–24.

    Article  Google Scholar 

  • — and Myron Wish. 1974. “Multidimensional Perceptual Models and Measurment Methods.” InHandbook of Perception (Vol. II): Psychophysical Judgment and Measurement. New York: Academic Press.

    Google Scholar 

  • Cooper, Lee G. 1983. “A Review of Multidimensional Scaling in Marketing Research.”Applied Psychological Measurement 7 (Fall): 427–450.

    Article  Google Scholar 

  • Day, D.L., Wayne S. DeSarbo, and T.A. Oliva. 1987. “Strategy Maps: A Spatial Representation of Intra-Industry Competitive Strategy.Management Science 33: 1543–1551.

    Google Scholar 

  • deLeeuw, J. and W. Heiser. 1980. “Multidimensional Scaling with Restrictions on the Configuration.” InMultivarate Analysis (Vol. V), Ed. P.R. Krishnaiah. Amsterdam: North Holland Press.

    Google Scholar 

  • DeSarbo, Wayne S., J. Douglas Carroll, D. Lehmann, and J. O’Shaughnessy. 1982. “Three-Way Multivariate Conjoint Analysis.”Marketing Science 1: 323–350.

    Article  Google Scholar 

  • —, and Vithala R. Rao. 1986. “A Constrained Unfolding Model for Product Positioning.”Marketing Science 5 (Spring): 1–19.

    Google Scholar 

  • — and-—. 1984. “GENFOLD2: A Set of Models and Algorithms for the General Unfolding Analysis of Preference/Dominance Data.”Journal of Classification 1: 147–186.

    Article  Google Scholar 

  • Gavish, B., D. Horsky, and K. Srikanth. 1983. “Optimal Positioning of a New Product.”Management Science 29 (November): 1277–1297.

    Article  Google Scholar 

  • Green, Paul E. 1975. “Marketing Applications of MDS: Assessment and Outlook.”Journal of Marketing 39 (January): 24–31.

    Article  Google Scholar 

  • — 1977. “A New Approach to Market Segmentation.”Business Horizons 20 (February) 61–73.

    Article  Google Scholar 

  • —, and Frank J. Camone. 1970.Multidimensional Scaling and Related Techniques in Marketing Analysis. Boston: Allyn and Bacon.

    Google Scholar 

  • Green, Paul E., Frank J. Carmone, and Prashant Vankudre. 1985. “Bootstrapped Confidence Intervals for Conjoint-Based Simulations.” American Marketing Association Winter Educators’ Conference Proceedings: 296–299.

  • —, J. Douglas Carroll, and Frank J. Carmone. 1976. “Superordinate Factorial Designs in the Analysis of Consumer Judgments.”Journal of Business Research 4: 281–295.

    Article  Google Scholar 

  • — and Wayne S. DeSarbo. 1979. “Componential Segmentation in the Analysis of Consumer Tradeoffs.”Journal of Marketing 43 (Fall): 83–91.

    Article  Google Scholar 

  • Green, Paul E. and Abba M. Krieger. 1988. “A Decision Support System for Market Share Estimation and Optimal Pricing.” Working Paper. Wharton School, University of Pennsylvania, February.

  • ——, and J. Douglas Carroll. 1987. “Conjoint Analysis and Multidimensional Scaling: A Complementary Approach.”Journal of Advertising Research 27 (October/November): 21–27.

    Google Scholar 

  • ——, and Robert N. Zelnio. 1989. “A Componential Segmentation Model with Optimal Product Design Features.”Decision Sciences 20 (Spring), 221–238.

    Article  Google Scholar 

  • — and Vithala R. Rao. 1972.Applied Multidimensional Scaling: A Comparison of Approaches and Algorithms, New York: Holt, Rinehart and Winston.

    Google Scholar 

  • — and Yoram Wind. 1973.Multiattribute Decisions in Marketing. Winsdale, IL: Dryden Press.

    Google Scholar 

  • Hauser, John R. and Patricia Simmie. 1981. “Profit Maximizing Perceptual Positions: An Integrated Theory for the Selection of Product Features and Price.”Management Science 17 (January): 33–56.

    Google Scholar 

  • Holbrook, Morris B. and William L. Moore. 1981. “Feature Interactions in Consumer Judgments of Verbal Versus Pictorial Presentation.”Journal of Consumer Research 8 (June): 103–113.

    Article  Google Scholar 

  • ——, Garry N. Dodgen, and William J. Havelena. 1985. “Nonisomorphism, Shadow Features and Imputed Preferences.”Marketing Science 4 (Summer): 215–233.

    Google Scholar 

  • Lin, S. and B. Kemighan. 1973. “An Effective Heuristic Algorithm for the Traveling Salesman Problem.”Operations Research 21: 489–516.

    Google Scholar 

  • Oliva, T.A., D.L. Day, and Wayne S. DeSarbo. 1987. “Selecting Competitive Tactics: Try a Strategy Map.”Sloan Management Review 28: 5–15.

    Google Scholar 

  • Plackett, R.L. and J.P. Burman. 1946. “The Design of Optimum Multifactorial Experiments.”Biometrika 33: 305–325.

    Article  Google Scholar 

  • Shocker, Allan D. and V. Srinivasan. 1974. “Consumer-Based Methodology for Identification of New Products.”Management Science 20 (February): 921–937.

    Google Scholar 

  • Takane, Yoshio, F.W. Young, and J. deLeeuw. 1977. “Nonmetric Individual Differences in Multidimensional Scaling: An Altemating Least Squares Method with Optimal Scaling Features.”Psychometrika 42: 7–67.

    Article  Google Scholar 

  • Wish, Myron. 1975. “Subjects’ Expectations About Their Own Interpersonal Communication: A Multidimensional Approach.”Personality and Social Psychology Bulletin 1: 501–504.

    Article  Google Scholar 

  • Zufryden, F.S. 1979. “ZIPMAP—A Zero-One Integer Progamming Model for Market Segmentation and Product Positioning.”Journal of the Operational Research Society 30: 63–70.

    Article  Google Scholar 

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AT&T Bell Laboratories

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Carroll, J.D., Green, P.E. & Kim, J. Preference mapping of conjoint-based profiles: An INDSCAL approach. JAMS 17, 273–281 (1989). https://doi.org/10.1007/BF02726638

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