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A Polarization Model for Describing Group Preferences

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  • Rao, Vithala R
  • Steckel, Joel H

Abstract

This article develops a model for describing the preferences of a group of its individual members. The model incorporates the empirically observed group-polarization phenomenon. It Is interesting that the resulting group preference evaluation is essentially a weighted linear model of individual preferences with the addition of an intercept term. The polarization model is empirically tested in two experimental contexts, faculty-candidate and restaurant selection. For both experimental situations, the polarization model performed better for the majority of groups tested in predicting a holdout sample than did either the more common weighted linear model without an intercept (with weights summing to one) or the multilinear model. Copyright 1991 by the University of Chicago.

Suggested Citation

  • Rao, Vithala R & Steckel, Joel H, 1991. " A Polarization Model for Describing Group Preferences," Journal of Consumer Research, Oxford University Press, vol. 18(1), pages 108-118, June.
  • Handle: RePEc:oup:jconrs:v:18:y:1991:i:1:p:108-18
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    File URL: http://dx.doi.org/10.1086/209245
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    Cited by:

    1. Vishal Narayan & Vithala R. Rao & Carolyne Saunders, 2011. "How Peer Influence Affects Attribute Preferences: A Bayesian Updating Mechanism," Marketing Science, INFORMS, vol. 30(2), pages 368-384, 03-04.
    2. Demont, Matty & Rutsaert, Pieter & Ndour, Maimouna & Verbeke, Wim & Seck, Papa Abdoulaye & Tollens, Eric, 2012. "Experimental auctions, collective induction and choice shift: Willingness-to-pay for rice quality in Senegal," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126861, International Association of Agricultural Economists.
    3. Nesha Beharry-Borg & David Hensher & Riccardo Scarpa, 2009. "An Analytical Framework for Joint vs Separate Decisions by Couples in Choice Experiments: The Case of Coastal Water Quality in Tobago," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 43(1), pages 95-117, May.
    4. Neeraj Arora & Ty Henderson & Qing Liu, 2011. "Noncompensatory Dyadic Choices," Marketing Science, INFORMS, vol. 30(6), pages 1028-1047, November.
    5. Demont, Matty & Zossou, Esperance & Van Mele, Paul, 2015. "Experimental Auctions with Exogenous and Endogenous Information Treatment: Willingness to Pay for Improved Parboiled Rice in Benin," 2015 Conference, August 9-14, 2015, Milan, Italy 229065, International Association of Agricultural Economists.
    6. Oded Netzer & Olivier Toubia & Eric Bradlow & Ely Dahan & Theodoros Evgeniou & Fred Feinberg & Eleanor Feit & Sam Hui & Joseph Johnson & John Liechty & James Orlin & Vithala Rao, 2008. "Beyond conjoint analysis: Advances in preference measurement," Marketing Letters, Springer, vol. 19(3), pages 337-354, December.
    7. Vikki O’Neill & Stephane Hess, 2014. "Heterogeneity assumptions in the specification of bargaining models: a study of household level trade-offs between commuting time and salary," Transportation, Springer, vol. 41(4), pages 745-763, July.
    8. Anocha Aribarg & Neeraj Arora & Moon Young Kang, 2010. "Predicting Joint Choice Using Individual Data," Marketing Science, INFORMS, vol. 29(1), pages 139-157, 01-02.
    9. Rajdeep Grewal & Gary Lilien & Sundar Bharadwaj & Pranav Jindal & Ujwal Kayande & Robert Lusch & Murali Mantrala & Robert Palmatier & Aric Rindfleisch & Lisa Scheer & Robert Spekman & Shrihari Sridhar, 2015. "Business-to-Business Buying: Challenges and Opportunities," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 2(3), pages 193-208, September.

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