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A method for the detection and characterization of technology fronts: Analysis of the dynamics of technological change in 3D printing technology.


ABSTRACT: This paper presents a method for the identification of the "technology fronts"-core technological solutions-underlying a certain broad technology, and the characterization of their change dynamics. We propose an approach based on the Latent Dirichlet Allocation (LDA) model combined with patent data analysis and text mining techniques for the identification and dynamic characterization of the main fronts where actual technological solutions are put into practice. 3D printing technology has been selected to put our method into practice for its market emergence and multidisciplinarity. The results show two highly relevant and specialized fronts strongly related with mechanical design that evolve gradually, in our opinion acting as enabling technologies. On the other side, we detected three fronts undergoing significant changes, namely layer-by-layer multimaterial manufacturing, data processing and stereolithograpy techniques. Laser and electron-beam based technologies take shape in the latter years and show signs of becoming enabling technologies in the future. The technology fronts and data revealed by our method have been convincing to experts and coincident with many technology trends already pointed out in technical reports and scientific literature.

SUBMITTER: Garechana G 

PROVIDER: S-EPMC6322778 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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A method for the detection and characterization of technology fronts: Analysis of the dynamics of technological change in 3D printing technology.

Garechana Gaizka G   Río-Belver Rosa R   Bildosola Iñaki I   Cilleruelo-Carrasco Ernesto E  

PloS one 20190107 1


This paper presents a method for the identification of the "technology fronts"-core technological solutions-underlying a certain broad technology, and the characterization of their change dynamics. We propose an approach based on the Latent Dirichlet Allocation (LDA) model combined with patent data analysis and text mining techniques for the identification and dynamic characterization of the main fronts where actual technological solutions are put into practice. 3D printing technology has been s  ...[more]

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