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Richard GonzalezRichard Gonzalez

Center Director, Research Center for Group Dynamics, Institute for Social Research
Director, BioSocial Methods Collaborative, RCGD
Amos N Tversky Collegiate Professor, Psychology and Statistics, LSA
Professor of Marketing, Stephen M Ross School of Business
Professor of Integrative Systems and Design, College of Engineering

 

E-mail: Email Richard Gonzalez
Address: Research Center for Group Dynamics
Institute for Social Research
University of Michigan
426 Thompson Street
Ann Arbor, Michigan 48106
Phone: 734-647-6785

How can behavioral decision theory contribute to product design?

Mar 16, 2011 | Decision Making, Design Science

The field of engineering design have been making use of some standard consumer decision making findings and models, such as discrete choice models. We review the notion of constructed preferences from the behavioral literature and work through some implications for engineering design models, including designing for sustainability in a way that is sensitive to preference inconsistency in consumers. We provide interpretations of some of our own studies along these lines.

MacDonald, E., Gonzalez, R. & Papalambros, P. (2009). Preference inconsistency in multidisciplinary design decision making. Journal of Mechanical Design, 131, 1-13. doi:10.1115/1.3066526 (PDF)

Abstract

A common implicit assumption in engineering design is that user preferences exist a priori. However, research from behavioral psychology and experimental economics suggests that individuals construct preferences on a case-by-case basis when called to make a decision rather than referring to an existing preference structure. Thus, across different contexts, preference elicitation methods used in design decision making can lead to preference inconsistencies. This paper offers a framework for understanding preference inconsistencies, giving three examples of preference inconsistencies that demonstrate the implications of unnoticed inconsistencies, and also discusses the design benefits of testing for inconsistencies. Three common engineering and marketing design methods are discussed: discrete choice analysis, modeling stated versus revealed preferences, and the Kano method. In these examples, we discuss perceived relationships between product attributes, identify market opportunities for a “green” product, and show how people find it is easier to imagine delight rather than necessity of product attributes. Understanding preference inconsistencies offers new insights into the relationship between user and product design.