A Hybrid Choice Model that Uses Actual and Ordered Attribute Value Information
Published 8/1/2005
Author: Anand V. Bodapati and Aimee Drolet
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Executive Summary
Contrary to traditional assumptions, research shows that consumers frequently do not use information about products’ actual attribute values (e.g., the price difference between two considered products is $.10) when making choices but instead use information about products’ ordered values (e.g., Product A costs less than Product B). This article develops a choice model that enables consumers to choose using either actual or ordered value information. This hybrid choice model is estimated using supermarket scanner data. Results indicate that the hybrid model predicts choices better than do models that allow consumers to use only one type of attribute value information (actual or ordered). By incorporating results from behavioral decision research into a quantitative model, this research extends the classical multinomial logit model to accommodate choice making based on products’ ordered values.
Biography
Anand V. Bodapati is Assistant Professor in the Anderson Graduate School of Management at the University of California, Los Angeles. His research interests are retail management, marketing research, direct marketing, and customer relationship management. His has a doctoral degree from Stanford University.
Aimee Drolet is Associate Professor of Marketing in the Anderson Graduate School of Management at the University of California, Los Angeles.. She studies consumer decision making, particularly the decision processes (i.e., rules, heuristics, and strategies) that consumers use to construct their preferences to solve choice problems. In one area of research, she investigates consumers’ use of metarules. In a second area, she examines the effects of diminished cognitive resources on the complexity and quality of consumer decisions. In a third area, she focuses on the role of emotion in consumer decision making. She received her doctoral degree from Stanford University in 1997.
J Marketing Research, Volume 42, Number 3, August 2005
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