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- W2894326390 abstract "Purpose- This study to predict the association between earnings management and EVA, evaluated it for accuracy. Methodology- This study through logistic regression model (excluding OLS regression model), S upport V ector M achines and R ough S et T heory Findings- Empirical results show that RST model exhibited the highest accuracy in China and Africa nations. SVM model exhibited the highest accuracy in Latin-America nations. Conclusion- Our results provide critical implications for managers, researchers, investors, and regulators. Managers should analyze whether EVA motivates managers to engage in earnings management behavior. For researchers, we adopted logit, SVM and RST model to predict e ffect of earnings management on economic value added; For investors, they can analyze the true value of enterprises, regardless of whether enterprises have adopted earnings management. Regulators (e.g., governments) should establish stricter security measures and laws or rules for listed firms to prevent earnings management following a financial tsunami and to encourage them to report their “real” true value." @default.
- W2894326390 created "2018-10-05" @default.
- W2894326390 creator A5075731977 @default.
- W2894326390 date "2018-09-30" @default.
- W2894326390 modified "2023-10-18" @default.
- W2894326390 title "Earnings management and economic value added in China, African and Latin-American markets: a study of logistics model, support vector machines and rough set theory" @default.
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- W2894326390 doi "https://doi.org/10.17261/pressacademia.2018.939" @default.
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