Artikel
Board structure and the likelihood of financial statement fraud. Does audit fee matter? Evidence from manufacturing firms in the East Africa community
This study examines the moderating effect of audit fee on the relation-ship between board structure and the likelihood of financial statements fraud (LFSF). The study uses the logistic regression and a sample of 15 manufacturing firms listed within the East African Community partner states from 2007 to 2021. The Beneish M-Score is used a proxy measure of the likelihood of financial state-ments fraud. The findings of this paper revealed that board gender diversity, board financial expertise, board independence, frequency of board meetings, audit fee are significant variable in reducing the likelihood of financial statements fraud. The result further demonstrated that the impact of board structure on LFSF is signifi-cantly influenced by audit fee. The findings of this study provide valuable informa-tion for investors and regulators in the EAC and other regions with similar legal and institutional environment on the nexus between board structure, audit fee and LFSF. The current study contributes to the board structure and LFSF literature by asses-sing whether audit fee moderates the relationship among listed manufacturing firms in the EAC. Like prior studies on financial statements fraud, the main limita-tions of this study is the measurement of LFS. Hence, the study wholly inherited the limitations of the Beneish M-Score.
- Language
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Englisch
- Bibliographic citation
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Journal: Cogent Business & Management ; ISSN: 2331-1975 ; Volume: 10 ; Year: 2023 ; Issue: 2 ; Pages: 1-23
- Classification
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Management
- Subject
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Likelihood of financial statement fraud
board structure
audit fee
East Africa community
- Event
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Geistige Schöpfung
- (who)
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Kaituko, Lucas Ekiru
Githaiga, Peter Nderitu
Chelogoi, Stephen Kimutai
- Event
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Veröffentlichung
- (who)
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Taylor & Francis
- (where)
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Abingdon
- (when)
-
2023
- DOI
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doi:10.1080/23311975.2023.2218175
- Last update
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10.03.2025, 11:44 AM CET
Data provider
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Artikel
Associated
- Kaituko, Lucas Ekiru
- Githaiga, Peter Nderitu
- Chelogoi, Stephen Kimutai
- Taylor & Francis
Time of origin
- 2023
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