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Cited by 486

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Individual Centrality and Performance in Virtual R&D Groups: An Empirical Study

Ahuja, Manju K., Galletta, Dennis F., Carley, Kathleen M.·2003·Management Science
DOI 10.1287/mnsc.49.1.21.12756
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Abstract

Communication technologies support virtual R&D groups by enabling immediate and frequent interaction of their geographically-distributed members. Performance of members in such groups has yet to be studied longitudinally. A model proposes not only direct effects of functional role, status, and communication role on individual performance, but also indirect effects through individual centrality. Social network analysis was performed on e-mail samples from two time periods separated by four years. Analysis revealed both direct and indirect effects as hypothesized; however, the indirect effects were more consistent in both time periods. The clearest findings were that centrality mediates the effects of functional role, status, and communication role on individual performance. Interestingly, centrality was a stronger direct predictor of performance than the individual characteristics considered in this study. The study illustrates the usefulness of accounting for network effects for better understanding individual performance in virtual groups.

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Cited by

Metadata

Authors
Ahuja, M. K., Galletta, D. F., & Carley, K. M.
Venue
Management Science
Publisher
Institute for Operations Research and the Management Sciences (INFORMS)
Published
2003-01
Volume
49
Issue
1
Pages
21-38
ISSN
  • 0025-1909 (ISSN-L)
  • 1526-5501
DOI
10.1287/mnsc.49.1.21.12756
OpenAlex
W2155373282
Cited by
486
References
9
FWCI
15.81
Type
journal article
Language
en
Open access
closed

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

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.