The DOI matches its Crossref record; 107 of the 107 references it cites were found in a registry or an index.
Gender Diversity and Securities Fraud
Open accessAbstract
We formulate theory on the effect of board of director gender diversity on the broad spectrum of securities fraud, and generate three key insights. First, based on ethicality, risk aversion, and diversity, we hypothesize that gender diversity on boards can operate as a significant moderator for the frequency of fraud. Second, we advance that the stock market response to fraud from a more gender-diverse board is significantly less pronounced. Third, we posit that women are more effective in male-dominated industries in reducing both the frequency and severity of fraud. Results of our novel empirical tests, based on data from a large sample of Chinese firms that committed securities fraud, are largely consistent with each of these hypotheses.
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Upper Echelons: The Organization as a Reflection of Its Top Managers
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The Econometrics of Financial Markets
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Women in the boardroom and their impact on governance and performance☆
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Boys will be Boys: Gender, Overconfidence, and Common Stock Investment
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Cited by
The role of board gender and foreign ownership in the CSR performance of Chinese listed firms
McGuinness, P. B., Vieito, J. P., & Wang, M. (2017) · Journal of Corporate Finance · doi:10.1016/j.jcorpfin.2016.11.001 · Cited by 939
Jeong, S.-H., & Harrison, D. A. (2017) · Academy of Management Journal · doi:10.5465/amj.2014.0716 · Cited by 429
Shi, W., Connelly, B. L., & Hoskisson, R. E. (2017) · Strategic Management Journal · doi:10.1002/smj.2560 · Cited by 299
Metadata
- Authors
- Cumming, D., Leung, T. Y., & Rui, O.
- Venue
- Academy of Management Journal
- Publisher
- Academy of Management
- Published
- 2015-10
- Volume
- 58
- Issue
- 5
- Pages
- 1572-1593
- ISSN
- 0001-4273 (ISSN-L)
- 1948-0989
- OpenAlex
- W3124618612
- Cited by
- 770
- References
- 107
- FWCI
- 55.22
- Type
- journal article
- Language
- en
- Open access
- green
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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.