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A Normative Model of Consumer Information Processing

Author

Listed:
  • Michael R. Hagerty

    (University of California, Berkeley)

  • David A. Aaker

    (University of California, Berkeley)

Abstract

A model of information search is proposed which assumes that a consumer chooses the next piece of information so as to maximize his expected value of sample information. The cost of processing, the perceived correlation between attributes, and the perceived importance of attributes would all affect information choice. Three sets of propositions are derived. The model is also estimated and tested for subjects performing an information display board task.

Suggested Citation

  • Michael R. Hagerty & David A. Aaker, 1984. "A Normative Model of Consumer Information Processing," Marketing Science, INFORMS, vol. 3(3), pages 227-246.
    • Handle: RePEc:inm:ormksc:v:3:y:1984:i:3:p:227-246
    DOI: 10.1287/mksc.3.3.227
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    Citations

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    Cited by:

    1. Anocha Aribarg & Thomas Otter & Daniel Zantedeschi & Greg M. Allenby & Taylor Bentley & David J. Curry & Marc Dotson & Ty Henderson & Elisabeth Honka & Rajeev Kohli & Kamel Jedidi & Stephan Seiler & X, 2018. "Advancing Non-compensatory Choice Models in Marketing," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 5(1), pages 82-92, March.
    2. Bingxiao Wu, 2014. "Information Presentation and Consumer Choice: Evidence from Assisted Reproductive Technology (ART) Success Rates Reports," Departmental Working Papers 201410, Rutgers University, Department of Economics.
    3. Theo A. Arentze & Benedict G. C. Dellaert & Caspar G. Chorus, 2015. "Incorporating Mental Representations in Discrete Choice Models of Travel Behavior: Modeling Approach and Empirical Application," Transportation Science, INFORMS, vol. 49(3), pages 577-590, August.
    4. DeSarbo, Wayne S. & Choi, Jungwhan, 1998. "A latent structure double hurdle regression model for exploring heterogeneity in consumer search patterns," Journal of Econometrics, Elsevier, vol. 89(1-2), pages 423-455, November.
    5. Gilbride, Timothy J. & Currim, Imran S. & Mintz, Ofer & Siddarth, S., 2016. "A Model for Inferring Market Preferences from Online Retail Product Information Matrices," Journal of Retailing, Elsevier, vol. 92(4), pages 470-485.

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