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Cited by 2,502

The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.

TAKING STOCK OF NETWORKS AND ORGANIZATIONS: A MULTILEVEL PERSPECTIVE.

Brass, D. J., Galaskiewicz, J., Greve, H. R.·2004·Academy of Management Journal

Abstract

The central argument of network research is that actors are embedded in networks of interconnected social relationships that offer opportunities for and constraints on behavior. We review research on the antecedents and consequences of networks at the interpersonal, interunit, and interorganizational levels of analysis, evaluate recent theoretical and empirical trends, and give directions for future research, highlighting the importance of investigating cross-level network phenomena. The order of authorship is alphabetical, reflecting equal contributions from the four authors. We thank all reviewers and authors who helped make this special research forum possible, and above all we thank Tom Lee for his strong support throughout this process. A quarter century of social network research in management journals has resulted in the accumulation of many findings in recent years (see, for example, Borgatti and Foster [2003] for a recent

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Metadata

Authors
Brass, D. J., Galaskiewicz, J., & Greve, H. R.
Venue
Academy of Management Journal
Published
2004-12-01
Volume
47
Issue
6
Pages
795-817
ISSN
  • 0001-4273 (ISSN-L)
  • 1948-0989
OpenAlex
W2119353660
Cited by
2,502
References
17
FWCI
85.36
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: TAKING STOCK OF NETWORKS AND ORGANIZATIONS: A MULTILEVEL PERSPECTIVE. https://app.cochat.ai/papers/10.2307/20159624
The paper
Brass, D. J., Galaskiewicz, J., & Greve, H. R. (2004). TAKING STOCK OF NETWORKS AND ORGANIZATIONS: A MULTILEVEL PERSPECTIVE. Academy of Management Journal. https://doi.org/10.2307/20159624

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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.