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- A. Almaqtari, Faozi, et al.
(author)
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Earning management estimation and prediction using machine learning: A systematic review of processing methods and synthesis for future research
- 2021
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In: 2021 International Conference on Technological Advancements and Innovations (ICTAI). - : IEEE. - 9781665420884 - 9781665420877 ; , s. 291-298
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Conference paper (peer-reviewed)abstract
- The present study highlights earning management optimization possibilities to constrain the events of earning management and financial fraud. Our study investigates the existing stock of knowledge and strand literature available on earning management and fraud detection. It aims to review systematically the methods and techniques used by prior research to determine earning management and fraud detection. The results indicate that prior research in earning management optimization is diverged among several techniques and none of these techniques has provided an ideal optimization for earning management. Further, the results reveal that earning management determinants are complex based on the type and size of business entities which complicate the optimization possibilities. The current research brings useful insights for predicting and optimization of earnings management and financial fraud. The present study has significant implications for policymakers, stock markets, auditors, investors, analysts, and professionals.
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| 2. |
- Elsheikh, Tamer, et al.
(author)
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Governance and sustainability: The role of environmental disclosures and board characteristics in environmental, social, and governance reporting
- 2024
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In: Journal of Governance and Regulation. - 2220-9352 .- 2306-6784. ; 13:3, s. 162-176
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Journal article (peer-reviewed)abstract
- The purpose of the study is to investigate how environmental disclosure affects environmental, social, and governance (ESG) reporting, specifically in relation to emissions, innovation, use of resources, environmental controversy, and environmental products. It also looks at how specific firm attributes and board characteristics affect ESG reporting in three different industries. The analysis uses data for 8094 enterprises sampled from Asia and Europe between 2016 and 2021 that was gathered from secondary sources and taken from the Refinitiv Eikon database. According to the findings, proactive environmental investments, fines, and environmental expenses associated with ESG reporting are positively correlated. The findings also show that European businesses disclose environmental information at a higher degree than Asian businesses, which benefits their sustainability initiatives. Furthermore, sustainability indices have an adverse relationship with ESG reporting in Asia but a positive relationship with ESG reporting in Europe. Crucially, the findings show that various industries have varied relationships between sustainability reporting and environmental indicators. The study provides valuable insights for policymakers by highlighting the extent to which enterprises disclose their emissions, innovations, and resource use. Additionally, the study offers evidence on the role of corporate board members and how certain board characteristics as important mechanisms can improve the quality of ESG reporting making environmental disclosures useful and relevant.
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