Biases in Predicting Preferences For the Whole From Fragments

Tiebing Shi, Queen's School of Business
Jay M. Handelman, Queen's School of Business
Shenghui (Jerry) Zhao, Marketing Department, The Wharton School
Robert Meyer|Jin Han|Shenghui (Jerry) Zhao|Robert Meyer, Marketing Department, The Wharton School|Singapore Management University|Marketing Department, The Wharton School|Marketing Department, The Wharton School

Biases in Mental Extrapolation

 

Authors: Shenghui Zhao1

   Robert J. Meyer2

Affiliations: 1University of Miami, 2University of Pennsylvania

 

Abstract

Consumers often need to predict their liking of a product based on product fragments (e.g., choosing paint colors from tabs with different paint colors). We call this type of preference forecasting the mental extrapolation task. Drawing on research on affective forecasting and memory processes, we predicted that, compared to their actual product experience, 1) forecasted preferences based on fragments were more extreme; 2) predictions were excessively anchored by evaluations of the fragments per se; and 3) familiarity with the product fragments increased the magnitude of these forecasting errors. Two lab experiments using an Internet shirt-buying task found support for these predictions.

[ to cite ]:
Tiebing Shi, Jay M. Handelman, Shenghui (Jerry) Zhao, and Robert Meyer|Jin Han|Shenghui (Jerry) Zhao|Robert Meyer (2006) ,"Biases in Predicting Preferences For the Whole From Fragments", in NA - Advances in Consumer Research Volume 33, eds. Connie Pechmann and Linda Price, Duluth, MN : Association for Consumer Research.