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Predicting Joint Choice Using Individual Data

Author

Listed:
  • Anocha Aribarg

    () (Stephen M. Ross School of Business, University of Michigan, Ann Arbor, Michigan 48109)

  • Neeraj Arora

    () (Wisconsin School of Business, University of Wisconsin–Madison, Madison, Wisconsin 53706)

  • Moon Young Kang

    () (Wisconsin School of Business, University of Wisconsin–Madison, Madison, Wisconsin 53706)

Abstract

Choice decisions in the marketplace are often made by a collection of individuals or a group. Examples include purchase decisions involving families and organizations. A particularly unique aspect of a joint choice is that the group's preference is very likely to diverge from preferences of the individuals that constitute the group. For a marketing researcher, the biggest hurdle in measuring group preference is that it is often infeasible or cost prohibitive to collect data at the group level. Our objective in this research is to propose a novel methodology to estimate joint preference without the need to collect joint data from the group members. Our methodology makes use of both stated and inferred preference measures, and merges experimental design, statistical modeling, and utility aggregation theories to capture the psychological processes of preference revision and concession that lead to the joint preference. Results based on a study involving a cell phone purchase for 214 parent-teen dyads demonstrate predictive validity of our proposed method.

Suggested Citation

  • 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.
  • Handle: RePEc:inm:ormksc:v:29:y:2010:i:1:p:139-157
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    File URL: http://dx.doi.org/10.1287/mksc.1090.0490
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    References listed on IDEAS

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    Cited by:

    1. repec:spr:custns:v:5:y:2018:i:1:d:10.1007_s40547-017-0071-1 is not listed on IDEAS
    2. Vij, Akshay, 2013. "Incorporating the Influence of Latent Modal Preferences in Travel Demand Models," University of California Transportation Center, Working Papers qt7ng2z24q, University of California Transportation Center.
    3. Benedict G. C. Dellaert & Joffre Swait & Wiktor L. Vic Adamowicz & Theo A. Arentze & Elizabeth E. Bruch & Elisabetta Cherchi & Caspar Chorus & Bas Donkers & Fred M. Feinberg & A. A. J. Marley & Linda , 2018. "Individuals’ Decisions in the Presence of Multiple Goals," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 51-64, March.
      • Dellaert, B.G.C. & Swait, J. & Adamowicz, W.L. & Arentze, T.A. & Bruch, E.E. & Cherchi, E. & Chorus, C.G. & Donkers, A.C.D. & Feinberg, F.M. & Marley, A.A.J. & Salisbury, L.C., 2017. "Individuals' Decisions in the Presence of Multiple Goals," ERIM Report Series Research in Management ERS-2017-007-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.
    4. Neeraj Arora & Ty Henderson & Qing Liu, 2011. "Noncompensatory Dyadic Choices," Marketing Science, INFORMS, vol. 30(6), pages 1028-1047, November.
    5. repec:eee:ijrema:v:28:y:2011:i:2:p:76-88 is not listed on IDEAS
    6. 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.
    7. Vij, Akshay, 2013. "Incorporating the Influence of Latent Modal Preferences in Travel Demand Models," University of California Transportation Center, Working Papers qt7nq9p0cv, University of California Transportation Center.
    8. repec:kap:regeco:v:52:y:2017:i:1:d:10.1007_s11149-017-9336-8 is not listed on IDEAS

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