EconPapers    
Economics at your fingertips  
 

Diversity, networks, and innovation: A text analytic approach to measuring expertise diversity

Alina Lungeanu, Ryan Whalen, Y. Jasmine Wu, Leslie A. DeChurch and Noshir S. Contractor

Network Science, 2023, vol. 11, issue 1, 36-64

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.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.cambridge.org/core/product/identifier/ ... type/journal_article link to article abstract page (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cup:netsci:v:11:y:2023:i:1:p:36-64_3

Access Statistics for this article

More articles in Network Science from Cambridge University Press Cambridge University Press, UPH, Shaftesbury Road, Cambridge CB2 8BS UK.
Bibliographic data for series maintained by Kirk Stebbing ().

 
Page updated 2025-03-19
Handle: RePEc:cup:netsci:v:11:y:2023:i:1:p:36-64_3