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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 850-864 |
| Number of pages | 15 |
| Journal | Journal of Consumer Research |
| Volume | 34 |
| Issue number | 6 |
| DOIs | |
| State | Published - Apr 2008 |
| Externally published | Yes |
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ASJC Scopus subject areas
- Business and International Management
- Marketing
- Economics and Econometrics
Cite this
Protection of prior learning in complex consumer learning environments. / Cunha, Marcus; Janiszewski, Chris; Laran, Juliano.
In: Journal of Consumer Research, Vol. 34, No. 6, 04.2008, p. 850-864.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Protection of prior learning in complex consumer learning environments
AU - Cunha, Marcus
AU - Janiszewski, Chris
AU - Laran, Juliano
PY - 2008/4
Y1 - 2008/4
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=42549101855&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=42549101855&partnerID=8YFLogxK
U2 - 10.1086/523293
DO - 10.1086/523293
M3 - Article
AN - SCOPUS:42549101855
VL - 34
SP - 850
EP - 864
JO - Journal of Consumer Research
JF - Journal of Consumer Research
SN - 0093-5301
IS - 6
ER -