Dynamic Commercialization Strategies for Disruptive Technologies: Evidence from the Speech Recognition Industry

37 Pages Posted: 20 Dec 2013 Last revised: 13 Mar 2015

See all articles by Matt Marx

Matt Marx

Boston University - Questrom School of Business

Joshua S. Gans

University of Toronto - Rotman School of Management; NBER

David H. Hsu

University of Pennsylvania - Management Department

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Date Written: December 2013

Abstract

When startup innovation involves a potentially disruptive technology - initially lagging in the predominant performance metric, but with a potentially favorable trajectory of improvement - incumbents may be wary of engaging in cooperative commercialization with the startup. While the prevailing theory of disruptive innovation suggests that this will lead to (exclusively) competitive commercialization and the eventual replacement of incumbents, we consider a dynamic strategy involving product market entry before switching to a cooperative commercialization strategy. Empirical evidence from the automated speech recognition industry from 1952-2010 confirms the main prediction of the model.

Suggested Citation

Marx, Matt and Gans, Joshua S. and Hsu, David H., Dynamic Commercialization Strategies for Disruptive Technologies: Evidence from the Speech Recognition Industry (December 2013). NBER Working Paper No. w19764, Available at SSRN: https://ssrn.com/abstract=2370220

Matt Marx (Contact Author)

Boston University - Questrom School of Business ( email )

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Joshua S. Gans

University of Toronto - Rotman School of Management ( email )

Canada

HOME PAGE: http://www.joshuagans.com

NBER ( email )

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David H. Hsu

University of Pennsylvania - Management Department ( email )

The Wharton School
Philadelphia, PA 19104-6370
United States
215-746-0125 (Phone)
215-898-0401 (Fax)

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