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The Spatial Representation of Heterogeneous Consideration Sets

Author

Listed:
  • Wayne S. Desarbo

    (The University of Michigan)

  • Kamel Jedidi

    (Columbia University)

Abstract

Consideration sets have been the recent focus of a large volume of research in marketing. The primary orientation of this stream of research has been toward consideration set composition, measurement, and the theoretical formation process itself. This paper proposes a new multidimensional scaling methodology (MDS) devised to spatially represent preference intensity collected over consumers' consideration sets. Predictions concerning the probability of consideration set membership, as well as the degree of preference intensity of these brands within a consideration set, are possible from such a model. In addition, consumer heterogeneity is accommodated vis á vis latent market segment level estimation. The technical details of the proposed MDS methodology are presented. Two actual commercial applications of the procedure are provided in the modeling of consideration sets and respective preference intensity for “intenders” for mid-size and luxury automobiles. Finally, limitations and directions for future research in this area are discussed.

Suggested Citation

  • Wayne S. Desarbo & Kamel Jedidi, 1995. "The Spatial Representation of Heterogeneous Consideration Sets," Marketing Science, INFORMS, vol. 14(3), pages 326-342.
    • Handle: RePEc:inm:ormksc:v:14:y:1995:i:3:p:326-342
    DOI: 10.1287/mksc.14.3.326
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    Citations

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    Cited by:

    1. Hicks, Robert L. & Holland, Daniel S. & Kuriyama, Peter T. & Schnier, Kurt E., 2020. "Choice sets for spatial discrete choice models in data rich environments," Resource and Energy Economics, Elsevier, vol. 60(C).
    2. Tammo H.A. Bijmolt & Michel Wedel & Wayne S. DeSarbo, 2021. "Adaptive Multidimensional Scaling: Brand Positioning Based on Decision Sets and Dissimilarity Judgments," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 8(1), pages 1-15, June.
    3. Faure, Corinne & Natter, Martin, 2010. "New metrics for evaluating preference maps," International Journal of Research in Marketing, Elsevier, vol. 27(3), pages 261-270.
    4. Daniel M. Ringel & Bernd Skiera, 2016. "Visualizing Asymmetric Competition Among More Than 1,000 Products Using Big Search Data," Marketing Science, INFORMS, vol. 35(3), pages 511-534, May.
    5. Bijmolt, T.H.A. & Wedel, M. & DeSarbo, W.S., 2002. "Adaptive Multidimensional Scaling : The Spatial Representation of Brand Consideration and Dissimilarity Judgments," Discussion Paper 2002-82, Tilburg University, Center for Economic Research.
    6. Bijmolt, T.H.A. & Wedel, M. & DeSarbo, W.S., 2002. "Adaptive Multidimensional Scaling : The Spatial Representation of Brand Consideration and Dissimilarity Judgments," Other publications TiSEM 26b65f04-0d5f-42d6-8a85-8, Tilburg University, School of Economics and Management.
    7. Manash Pratim Kashyap, 2011. "Brand Categorization Process for Staple Goods: Comparison between Rural and Urban Customers," Information Management and Business Review, AMH International, vol. 2(4), pages 162-172.
    8. Tobias Reckmann, 2017. "Verwendung von Word of Mouth-Daten zur Identifikation von Asymmetrie im Wettbewerb: Eine textbasierte Analyse am Beispiel deutscher Automobilmarken [Identification of asymmetric competition by usin," Schmalenbach Journal of Business Research, Springer, vol. 69(2), pages 173-201, June.
    9. 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.
    10. Peter Ebbes & Rajdeep Grewal & Wayne DeSarbo, 2010. "Modeling strategic group dynamics: A hidden Markov approach," Quantitative Marketing and Economics (QME), Springer, vol. 8(2), pages 241-274, June.
    11. Vishal Bindroo & Xin He & Raj Echambadi, 2016. "Satisfaction—Repurchase Intentions Relationship: Exploring the Contingent Roles of Consideration Set Size and Price Consciousness," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(3), pages 115-125, December.
    12. Elisabeth Honka & Pradeep Chintagunta, 2017. "Simultaneous or Sequential? Search Strategies in the U.S. Auto Insurance Industry," Marketing Science, INFORMS, vol. 36(1), pages 21-42, January.

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