Artikel
Risk governance and cybercrime: The hierarchical regression approach
This study examines the impact of risk governance on cybercrime of selected listed firms in the Nigerian financial institutions. To achieve this, a sample size of 50 listed companies from the Nigerian financial sector was selected for the years 2013-2017, resulting in 250 observations. The study employed the use of hierarchical regression analysis to test the impact of risk governance variables (Chief Risk Officer_centrality, Enterprise Risk Management_index, Chief Risk Officer_presence, Board Risk Committee_size, Board Risk Committee_activism, and Board Risk Committee_inde-pendence) and other control variables such as corporate governance variables (Board Size and Board of Directors_independence) and firm characteristics variables (Firm size and firm age) on cybercrime. The study observed from the findings that almost all the explanatory variables present a positive and significant relationship with cybercrime, except the Chief Risk Officer_presence, firm age and Board Risk Committee_size which revealed an insignificant relationship with cybercrime. The study concludes that risk governance variables and other variables are likely to reduce and minimize the impact of cybercrime on the sampled firms used in this study.
- Language
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Englisch
- Bibliographic citation
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Journal: Future Business Journal ; ISSN: 2314-7210 ; Volume: 6 ; Year: 2020 ; Issue: 1 ; Pages: 1-15 ; Heidelberg: Springer
- Classification
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Management
- Subject
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Cybercrime
Chief Risk Officer
Enterprise Risk Management
Financial loss
Nigerian financial sector
Risk governance
- Event
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Geistige Schöpfung
- (who)
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Erin, Olayinka Adedayo
Kolawole, Adebola Daniel
Noah, Abdurafiu Olaiya
- Event
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Veröffentlichung
- (who)
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Springer
- (where)
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Heidelberg
- (when)
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2020
- DOI
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doi:10.1186/s43093-020-00020-1
- Handle
- Last update
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10.03.2025, 11:43 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
- Erin, Olayinka Adedayo
- Kolawole, Adebola Daniel
- Noah, Abdurafiu Olaiya
- Springer
Time of origin
- 2020