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Research Papers

On the Suitability of Econometric Demand Models in Design for Market Systems

[+] Author and Article Information
Bart D. Frischknecht1

Centre for the Study of Choice, University of Technology Sydney, Sydney, New South Wales 2007, Australiabart.frischknecht@uts.edu.au

Katie Whitefoot

Design Science, University of Michigan, Ann Arbor, MI 48109kwhitefoot@umich.edu

Panos Y. Papalambros

Mechanical Engineering and Design Science, University of Michigan, Ann Arbor, MI 48109pyp@umich.edu

1

Corresponding author.

J. Mech. Des 132(12), 121007 (Dec 07, 2010) (11 pages) doi:10.1115/1.4002941 History: Received October 30, 2009; Revised October 28, 2010; Published December 07, 2010; Online December 07, 2010

A goal of design for market systems research is to predict demand for differentiated products so that counterfactual experiments can be performed based on design changes. We review conventional methods and propose an additional method to evaluate the suitability of econometric demand models estimated from revealed preference data for use in product design studies. We evaluate one demand model form from literature and two newly constructed forms for new vehicle demand along existing metrics of fit and predictive validity as well as a newly developed metric of proportional substitution sensitivity. We show that a model that includes horizontally differentiated preferences for size performs better under metrics of fit and predictive validity but that no model relaxes the IIA property satisfactorily to avoid exploitation by design optimization. We conduct design studies separately, applying each demand model form assuming the automotive market is in Bertrand–Nash price equilibrium. Results illustrate that the influence of the demand model form on the optimum in terms of design variables and expected firm profit is significant.

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Copyright © 2010 by American Society of Mechanical Engineers
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Figures

Grahic Jump Location
Figure 1

Distribution of ideal vehicle size implied by footprint parameters in model 2

Grahic Jump Location
Figure 2

Predicted shares versus actual shares. Left: BLP; center: model 1; right: model 2

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