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Cited by 1,613

The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.

Networks, Diversity, and Productivity: The Social Capital of Corporate R&D Teams

Reagans, Ray, Zuckerman, Ezra W.·2001·Organization Science
DOI 10.1287/orsc.12.4.502.10637
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Abstract

We argue that the debate regarding the performance implications of demographic diversity can be usefully reframed in terms of the network variables that reflect distinct forms of social capital. Scholars who are pessimistic about the performance of diverse teams base their view on the hypothesis that decreased network density—the average strength of the relationship among team members—lowers a team's capacity for coordination. The optimistic view is founded on the hypothesis that teams that are characterized by high network heterogeneity, whereby relationships on the team cut across salient demographic boundaries, enjoy an enhanced learning capability. We test each of these hypotheses directly and thereby avoid the problematic assumption that they contradict one another. Our analysis of data on the social networks, organizational tenure, and productivity of 224 corporate R…D teams indicates that both network variables help account for team productivity. These findings support a recasting of the diversity-performance debate in terms of the network processes that are more proximate to outcomes of interest.

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Citations

Cites

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Cited by

Metadata

Authors
Reagans, R., & Zuckerman, E. W.
Venue
Organization Science
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Published
2001-08
Volume
12
Issue
4
Pages
502-517
ISSN
  • 1047-7039 (ISSN-L)
  • 1526-5455
DOI
10.1287/orsc.12.4.502.10637
OpenAlex
W1998933571
Cited by
1,613
References
14
FWCI
24.46
Type
journal article
Language
en
Open access
closed

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.