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Integrating innovation and learning curve theory: an enabler for moving nanotechnologies and other emerging process technologies into production
Author(s) -
Linton Jonathan D.,
Walsh Steven T.
Publication year - 2004
Publication title -
randd management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.253
H-Index - 102
eISSN - 1467-9310
pISSN - 0033-6807
DOI - 10.1111/j.1467-9310.2004.00359.x
Subject(s) - enabling , learning curve , process (computing) , emerging technologies , emerging markets , selection (genetic algorithm) , production (economics) , computer science , engineering , business , economics , artificial intelligence , microeconomics , psychotherapist , operating system , psychology , finance
Process technology selection is biased against selection of emerging process technologies such as nanotechnologies, biotechnology and microtechnologies (MEMS), since these decisions are frequently based on assumptions that are only valid for mature sustaining process technologies. This is a great concern since emerging process technologies are drivers of economic growth, especially in developed economies. We consider the learning curve literature and integrate it with the literature on technological trajectories and innovation to develop a theory for modeling the learning curve for emerging process technologies.