An empirical comparison of different implicit measures to predict consumer choice

Area of Science:

• Consumer Psychology
• Behavioral Economics
• Decision Science

Background:

• Implicit measures predict affectively driven behavior but not cognitively driven behavior.
• Previous research has not determined which implicit measures best predict behavior.

Purpose of the Study:

• To assess the predictive validity of explicit and implicit measures in a consumer context.
• To compare the predictive power of different implicit measures for consumer choices.
• To determine if explicit measures better predict affectively versus cognitively driven choices.

Main Methods:

• Implemented a consumer context experiment.
• Assessed two explicit measures: self-reported habit and tastiness.
• Evaluated three implicit measures: manikin task, affective priming, and ID-EAST.

Main Results:

• Explicit measures (habit, tastiness) strongly predicted consumer choice, regardless of affective or cognitive drivers.
• Implicit measures did not significantly predict consumer choice.
• Explicit measures demonstrated superior predictive validity compared to all implicit measures.

Conclusions:

• Self-reported explicit measures are more effective predictors of consumer choice than implicit measures.
• Findings have implications for understanding decision-making processes in consumer behavior.
• Limitations include the specific consumer context and measures used.