Project EDV-TEK
Research
Abstract
The EDV-TEK project investigates four key dimensions of technology research — identification, emergence, diffusion, and exploitation — in the context of climate change mitigation technologies.
In terms of identification, the project utilizes artificial intelligence techniques to train neural networks that automate patent classification. This field of research is relatively new, and results from different studies are often not comparable.
In the context of emergence, the project explores the role of science in technological development, with a focus on measuring scientific influence by examining citations from patents to scientific publications.
Relating to diffusion, the project uses patent citations as a measure of knowledge flow and recombination, with a focus on the interrelatedness of diffusion, impact, and novelty.
As for exploitation, the project focuses on the commercialization of technologies, using technology startups as the unit of study. Research has shown that patents positively influence startup performance, yet there is limited knowledge about the specific technologies and their novelty levels. EDV-TEK addresses this gap by utilizing machine-learning neural networks to analyze the underlying phenomena.
Funding
