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Protection of Prior Learning in Complex Consumer Learning Environments

Author

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  • Marcus Cunha Jr.
  • Chris Janiszewski
  • Juliano Laran

Abstract

As a product category evolves, consumers have the opportunity to learn a series of feature-benefit associations. Initially, consumers learn that some features predict a critical benefit, whereas other features do not. Subsequently, consumers have the opportunity to assess if previously predictive features, or novel features, predict new product benefits. Surprisingly, later learning is characterized by attenuated learning about previously predictive features relative to novel features. This tendency to ignore previously predictive features is consistent with a desire to protect prior learning. (c) 2007 by JOURNAL OF CONSUMER RESEARCH, Inc..

Suggested Citation

  • Marcus Cunha Jr. & Chris Janiszewski & Juliano Laran, 2008. "Protection of Prior Learning in Complex Consumer Learning Environments," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 34(6), pages 850-864, October.
    • Handle: RePEc:oup:jconrs:v:34:y:2008:i:6:p:850-864
    DOI: 10.1086/523293
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    Cited by:

    1. Miljkovic, Dragan & Gong, Jian & Lehrke, Linda, 2009. "The Effects of Trivial Attributes on Choice of Food Products," Agricultural and Resource Economics Review, Northeastern Agricultural and Resource Economics Association, vol. 38(2), pages 1-11, October.

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