Evaluating the Impact of Robotic Process Automation on Earnings Management

H.-M. Chou Y.-L. Huang K.-L. Lai & Sheng-Feng Hsieh

Journal of Information Systems2025https://doi.org/10.2308/isys-2024-032article
AJG 1ABDC A
Weight
0.44

Abstract

This study examines the impact of robotic process automation (RPA) on earnings management (EM) by analyzing 86 Taiwanese companies that adopted RPA, compared to a matched control group. Using the modified Jones model to assess discretionary accruals and proxies for real activities manipulation, we find a significant increase in both accrual-based and real activities EM strategies following RPA implementation. The results suggest that although RPA enhances operational efficiency and decision-making, it also creates additional opportunities for managers to engage in EM, likely due to the absence of robust control standards and risk management frameworks during its initial adoption. These findings contribute to the growing literature on the influence of automation technologies on financial reporting, underscoring the need for stronger governance structures to mitigate the risk of EM in the digital era. JEL Classifications: M41.

3 citations

Open via your library →

Cite this paper

https://doi.org/https://doi.org/10.2308/isys-2024-032

Or copy a formatted citation

@article{h.-m.2025,
  title        = {{Evaluating the Impact of Robotic Process Automation on Earnings Management}},
  author       = {H.-M. Chou Y.-L. Huang K.-L. Lai & Sheng-Feng Hsieh},
  journal      = {Journal of Information Systems},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.2308/isys-2024-032},
}

Paste directly into BibTeX, Zotero, or your reference manager.

Flag this paper

Evaluating the Impact of Robotic Process Automation on Earnings Management

Flags are reviewed by the Arbiter methodology team within 5 business days.


Evidence weight

0.44

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.32 × 0.4 = 0.13
M · momentum0.57 × 0.15 = 0.09
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.