Errors in Estimating Patent and Class Action Damages

57 Pages Posted: 24 Aug 2019 Last revised: 30 Aug 2019

See all articles by Suneal Bedi

Suneal Bedi

Indiana University - Kelley School of Business

David Reibstein

Marketing Science Institute; University of Pennsylvania - Marketing Department

Date Written: August 21, 2019

Abstract

How much are consumers willing to pay for the rounded edges of an iPhone? How much more are consumers willing to pay for a soap that kills 99% of bacteria as opposed to 90%? Answering these questions is at the heart of estimating damage awards for patent infringement and false advertising class action lawsuits respectively. But these questions are difficult and often require the use of social science experts. These experts use complicated empirical black box methodologies to introduce opinions leading to billions of dollars of damages.

One such method that has gained much traction in federal courts is “choice based conjoint.” This method seeks to answer how much consumers are willing to pay for various features of products. Although a powerful and widely accepted method outside of the law, it is currently being misused in its application to patent infringement and false advertising lawsuits. Experts have been applying the method incorrectly and judges, lawyers, and litigants are not adequately policing the use of the method.

In this article, we explain how the method applies to the legal context and open up the proverbial black box so that legal practitioners can be savvy consumers of the method. More importantly, we empirically show through our novel experimental design and using Hierarchical Bayes estimation, how the method often has been inappropriately applied in the legal context and used to validate unjust, excessive, and unrealistic damage awards.

Keywords: patent, class action, consumer protection, marketing, empirical, law

Suggested Citation

Bedi, Suneal and Reibstein, David, Errors in Estimating Patent and Class Action Damages (August 21, 2019). Available at SSRN: https://ssrn.com/abstract=3440817 or http://dx.doi.org/10.2139/ssrn.3440817

Suneal Bedi (Contact Author)

Indiana University - Kelley School of Business ( email )

1309 East Tenth Street
Indianapolis, IN 47405-1701
United States

David Reibstein

Marketing Science Institute ( email )

1000 Massachusetts Ave.
Cambridge, MA 02138-5396
United States

University of Pennsylvania - Marketing Department

700 Jon M. Huntsman Hall
3730 Walnut Street
Philadelphia, PA 19104-6340
United States

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