Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 1,312

The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.

Organizational Predictors of Women on Corporate Boards

Hillman, Amy J., Shropshire, Christine, Cannella, Albert A.·2007·Academy of Management Journal

Abstract

Women are increasing in number among corporations' boards of directors, yet their representation is far from uniform across firms. In this study, we adopted a resource dependence theory lens to identify organizational predictors of women on boards. We tested our hypotheses using panel data from the 1,000 U.S. firms that were largest in terms of sales between 1990 and 2003. We found that organizational size, industry type, firm diversification strategy, and network effects (linkages to other boards with women directors) significantly impact the likelihood of female representation on boards of directors.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.5465/amj.2007.26279222

Cites

76 of 76 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 76 references

Cited by

See all 1,312

Metadata

Authors
Hillman, A. J., Shropshire, C., & Cannella, A. A.
Venue
Academy of Management Journal
Published
2007-08
Volume
50
Issue
4
Pages
941-952
ISSN
  • 0001-4273 (ISSN-L)
  • 1948-0989
OpenAlex
W1970177130
Cited by
1,312
References
76
FWCI
31.23
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Organizational Predictors of Women on Corporate Boards. https://app.cochat.ai/papers/10.5465/amj.2007.26279222
The paper
Hillman, A. J., Shropshire, C., & Cannella, A. A. (2007). Organizational Predictors of Women on Corporate Boards. Academy of Management Journal. https://doi.org/10.5465/amj.2007.26279222

Data sources

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.