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Dynamic commercialization strategies for disruptive technologies : evidence from the Speech Recognition Industry

Autore: Matt Marx; Joshua Gans; David H Hsu; National Bureau of Economic Research.
Editore: Cambridge, Mass. : National Bureau of Economic Research, 2013.
Serie: Working paper series (National Bureau of Economic Research), no. 19764.
Edizione/Formato:   eBook : Document : EnglishVedi tutte le edizioni e i formati
Banca dati:WorldCat
Sommario:
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  Per saperne di più…
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Tipo materiale: Document, Risorsa internet
Tipo documento: Internet Resource, Computer File
Tutti gli autori / Collaboratori: Matt Marx; Joshua Gans; David H Hsu; National Bureau of Economic Research.
Numero OCLC: 868158921
Note: Title from http://www.nber.org/papers/19764 viewed January 15, 2014.
"December 2013."
Descrizione: 1 online resource (36 p.) : ill.
Titolo della serie: Working paper series (National Bureau of Economic Research), no. 19764.
Responsabilità: Matt Marx, Joshua S. Gans, David H. Hsu.

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.

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