Digital transformation and earnings opacity:Evidence from China
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DOI: 10.1016/j.frl.2024.106024
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References listed on IDEAS
- Yang Bao & Bin Ke & Bin Li & Y. Julia Yu & Jie Zhang, 2020. "Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 199-235, March.
- Jeremy Bertomeu & Edwige Cheynel & Eric Floyd & Wenqiang Pan, 2021. "Using machine learning to detect misstatements," Review of Accounting Studies, Springer, vol. 26(2), pages 468-519, June.
- Bhattacharya, Utpal & Daouk, Hazem & Welker, Michael, 2003. "The World Price of Earnings Opacity," Working Papers 127185, Cornell University, Department of Applied Economics and Management.
- Ball, Ray & Robin, Ashok & Wu, Joanna Shuang, 2003. "Incentives versus standards: properties of accounting income in four East Asian countries," Journal of Accounting and Economics, Elsevier, vol. 36(1-3), pages 235-270, December.
- Kexing Ding & Baruch Lev & Xuan Peng & Ting Sun & Miklos A. Vasarhelyi, 2020. "Machine learning improves accounting estimates: evidence from insurance payments," Review of Accounting Studies, Springer, vol. 25(3), pages 1098-1134, September.
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Cited by:
- Xu, Zhan & Wang, Solomon & Ye, Junchen, 2024. "The effect of digitization on corporate fraud detection evidence from China," International Review of Financial Analysis, Elsevier, vol. 96(PB).
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More about this item
Keywords
Digital transformation; Earnings opacity; Earnings aggressiveness; Earnings smoothing;All these keywords.
JEL classification:
- D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
- M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
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