Abstract
Technology is essential to innovation and economic prosperity. Understanding technological changes can guide innovators to find new directions of design innovation and thus make breakthroughs. In this work, we construct a technology fitness landscape via deep neural embeddings of patent data. The landscape consists of 1,757 technology domains and their respective improvement rates. In the landscape, we found a high hill related to information and communication technologies (ICT) and a vast low plain of the remaining domains. The landscape presents a bird's-eye view of the structure of the total technology space, providing a new way for innovators to interpret technology evolution with a biological analogy, and a biologically-inspired inference to the next innovation. © 2022 Informa UK Limited, trading as Taylor & Francis Group.
| Original language | English |
|---|---|
| Pages (from-to) | 716-727 |
| Journal | Journal of Engineering Design |
| Volume | 33 |
| Issue number | 10 |
| Online published | 11 Nov 2022 |
| DOIs | |
| Publication status | Published - 2022 |
| Externally published | Yes |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 8 Decent Work and Economic Growth
Research Keywords
- deep learning
- design innovation
- neural embedding
- patent
- technology fitness landscape
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