Abstract
Despite the importance of diverse expertise in helping solve difficult interdisciplinary problems, measuring it is challenging and often relies on proxy measures and presumptive correlates of actual knowledge and experience. To address this challenge, we propose a text-based measure that uses researcher's prior work to estimate their substantive expertise. These expertise estimates are then used to measure team-level expertise diversity by determining similarity or dissimilarity in members' prior knowledge and skills. Using this measure on 2.8 million team invented patents granted by the US Patent Office, we show evidence of trends in expertise diversity over time and across team sizes, as well as its relationship with the quality and impact of a team's innovation output.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 36-64 |
| Number of pages | 29 |
| Journal | Network Science |
| Volume | 11 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 15 2023 |
Funding
This work was supported by the National Science Foundation under award #1856090 and by the National Institutes of Health under award #R01GM1374100. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or the National Institutes of Health.
Keywords
- innovation
- inventor networks
- network science
- patent records
- team expertise diversity
- team science
- text analytics
ASJC Scopus subject areas
- Social Psychology
- Communication
- Sociology and Political Science