Diversity, Networks, and Innovation: A Text Analytic Approach to Measuring Expertise Diversity (WP-23-11)
Alina Lungeanu, Ryan Whalen, Y. Jasmine Wu, Leslie DeChurch, and Noshir Contractor
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, the researchers 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, the authors 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.
This paper is published in Network Science.