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A Constrained Unfolding Methodology for Product Positioning

Author

Listed:
  • Wayne DeSarbo

    (The Wharton School, University of Pennsylvania)

  • Vithala R. Rao

    (The Johnson School, Cornell University)

Abstract

This paper presents a recently developed unfolding methodology for analyzing preferential/dominance data that addresses the product positioning/repositioning decision problem of product (re)design and targeting by relating brand and consumer characteristics explicitly to perceptual brand locations and ideal points respectively. The methodology and associated algorithm are applied to a set of preference data for twelve models of residential communication devices. Various managerial implications of the model for product positioning and optimal product design are illustrated and discussed.

Suggested Citation

  • Wayne DeSarbo & Vithala R. Rao, 1986. "A Constrained Unfolding Methodology for Product Positioning," Marketing Science, INFORMS, vol. 5(1), pages 1-19.
    • Handle: RePEc:inm:ormksc:v:5:y:1986:i:1:p:1-19
    DOI: 10.1287/mksc.5.1.1
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    Citations

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    Cited by:

    1. Rick L. Andrews & Ajay K. Manrai, 1999. "MDS Maps for Product Attributes and Market Response: An Application to Scanner Panel Data," Marketing Science, INFORMS, vol. 18(4), pages 584-604.
    2. Joonwook Park & Priyali Rajagopal & Wayne DeSarbo, 2012. "A New Heterogeneous Multidimensional Unfolding Procedure," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 263-287, April.
    3. Duncan Fong & Wayne DeSarbo & Zhe Chen & Zhuying Xu, 2015. "A Bayesian Vector Multidimensional Scaling Procedure Incorporating Dimension Reparameterization with Variable Selection," Psychometrika, Springer;The Psychometric Society, vol. 80(4), pages 1043-1065, December.
    4. Junghyun Park & Minki Kim & Pradeep K Chintagunta, 2022. "Mapping Consumers’ Context-Dependent Consumption Preferences: A Multidimensional Unfolding Approach [An Empirical Comparison of Logit Choice Models with Discrete versus Continuous Representations o," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 49(2), pages 202-228.
    5. Marks, Ulf G. & Albers, Sönke, 1995. "Experiments in competitive product positioning: An equilibrium analysis," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 364, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    6. Hobbs, Lonnie & Shanoyan, Aleksan, 2018. "Analysis of Consumer Perception of Product Attributes in Pet Food: Implications for Marketing and Brand Strategy," 2018 Annual Meeting, August 5-7, Washington, D.C. 274070, Agricultural and Applied Economics Association.
    7. Wayne DeSarbo & Michael Johnson & Ajay Manrai & Lalita Manrai & Elizabeth Edwards, 1992. "Tscale: A new multidimensional scaling procedure based on tversky's contrast model," Psychometrika, Springer;The Psychometric Society, vol. 57(1), pages 43-69, March.
    8. Joonwook Park & Wayne DeSarbo & John Liechty, 2008. "A Hierarchical Bayesian Multidimensional Scaling Methodology for Accommodating Both Structural and Preference Heterogeneity," Psychometrika, Springer;The Psychometric Society, vol. 73(3), pages 451-472, September.
    9. Ho, Ying & Chung, Yuho & Lau, Kin-nam, 2010. "Unfolding large-scale marketing data," International Journal of Research in Marketing, Elsevier, vol. 27(2), pages 119-132.
    10. Baier, Daniel & Gaul, Wolfgang, 1998. "Optimal product positioning based on paired comparison data," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 365-392, November.
    11. Buechel, Berno & Klein, Jan, 2014. "Do Consumers' Preferences Really Matter? - A Note on Spatial Competition with Restricted Strategies," MPRA Paper 55288, University Library of Munich, Germany.
    12. Wayne DeSarbo & Joonwook Park & Vithala Rao, 2011. "Deriving joint space positioning maps from consumer preference ratings," Marketing Letters, Springer, vol. 22(1), pages 1-14, March.
    13. Kamel Jedidi & Wayne DeSarbo, 1991. "A stochastic multidimensional scaling procedure for the spatial representation of three-mode, three-way pick any/J data," Psychometrika, Springer;The Psychometric Society, vol. 56(3), pages 471-494, September.
    14. Elrod, Terry & Keane, Michael, 1995. "A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data," MPRA Paper 52434, University Library of Munich, Germany.
    15. Gower, J.C. & Groenen, P.J.F. & van de Velden, M. & Vines, K., 2010. "Perceptual maps: the good, the bad and the ugly," ERIM Report Series Research in Management ERS-2010-011-MKT, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam.
    16. Wayne DeSarbo & Joonwook Park & Crystal Scott, 2008. "A Model-Based Approach for Visualizing the Dimensional Structure of Ordered Successive Categories Preference Data," Psychometrika, Springer;The Psychometric Society, vol. 73(1), pages 1-20, March.

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