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Inventors' explorations across technology domains

Jeff Alstott, Giorgio Triulzi*, Bowen Yan, Jianxi Luo

*Corresponding author for this work

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

7 Downloads (CityUHK Scholars)

Abstract

Technologies are created through the collective efforts of individual inventors. Understanding inventors' behaviors may thus enable predicting invention, guiding design efforts or improving technology policy. We examined data from 2.8 million inventors' 3.9 million patents and found that most patents are created by 'explorers': inventors who move between different technology domains during their careers. We mapped the space of latent relatedness between technology domains and found explorers were 250 times more likely to enter technology domains that were highly related to the domains of their previous patents, compared to an unrelated domain. The great regularity of inventors' behavior enabled accurate prediction of individual inventors' future movements: a model trained on just 5 years of data predicted inventors' explorations 30 years later with a log-loss below 0.01. Inventors entering their most related domains were associated with patenting up to 40% more in the new domain, but with reduced citations per patent. These findings may be instructive for inventors exploring design directions, and useful for organizations or governments in forecasting or directing technological change. Copyright © The Author(s) 2017 Distributed as Open Access under a CC-BY 4.0 license.
Original languageEnglish
Article numbere20
JournalDesign Science
Volume3
DOIs
Publication statusPublished - 2017
Externally publishedYes

Bibliographical note

Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].

Research Keywords

  • Design domains
  • Networks
  • Performance
  • Prediction
  • Technology relatedness

Publisher's Copyright Statement

  • This full text is made available under CC-BY 4.0. https://creativecommons.org/licenses/by/4.0/

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