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Cited by 864

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The Linear Model of Innovation: The Historical Construction of an Analytical Framework

Godin, Benoît·2006·Science, Technology, & Human Values

Abstract

One of the first (conceptual) frameworks developed for understanding the relation of science and technology to the economy has been the linear model of innovation. The model postulated that innovation starts with basic research, is followed by applied research and development, and ends with production and diffusion. The precise source of the model remains nebulous, having never been documented. Several authors who have used, improved, or criticized the model in the past fifty years rarely acknowledged or cited any original source. The model usually was taken for granted. According to others, however, it comes directly from V. Bush’s Science: The Endless Frontier ([1945] 1995). This article traces the history of the linear model, suggesting that it developed in three steps corresponding to three scientific communities looking at science analytically. The article argues that statistics is a main reason the model is still alive despite criticisms, alternatives, and having been proclaimed dead.

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Metadata

Authors
Godin, B.
Venue
Science, Technology, & Human Values
Published
2006-11
Volume
31
Issue
6
Pages
639-667
ISSN
  • 0162-2439 (ISSN-L)
  • 1552-8251
OpenAlex
W2147649479
Cited by
864
References
0
FWCI
47.23
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: The Linear Model of Innovation: The Historical Construction of an Analytical Framework. https://app.cochat.ai/papers/10.1177/0162243906291865
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Godin, B. (2006). The Linear Model of Innovation: The Historical Construction of an Analytical Framework. Science, Technology, & Human Values. https://doi.org/10.1177/0162243906291865

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.