Business-finance integration, tax avoidance and tax risk—empirical evidence based on firm recruitment data

Yitong Zhao et al.

China Journal of Accounting Studies2025https://doi.org/10.1080/21697213.2025.2520220article
AJG 1ABDC B
Weight
0.50

Abstract

The advancement of digital transformation in tax administration and the rise of novel business models make firms increasingly recognise the strategic importance of integrating business and finance departments (referred to as ‘business-finance integration (BFI)’) in tax management. Our study analyzes recruitment data from Chinese A-share listed firms between 2014 and 2021 based on machine learning methods to identify the shift towards BFI and evaluate its impact on corporate tax management. We find that BFI significantly reduces tax avoidance. However, this effect is more pronounced in firms facing higher potential tax risks, such as those with complex organisational structures or greater exposure to tax audits. Additionally, BFI can reduce corporate tax risks. The conclusions indicate that BFI curbs corporate tax avoidance by reducing tax risks, thereby enhancing tax management efficiency. The findings provide significant theoretical and practical insights for promoting interdepartmental collaboration, advancing financial management, and improving tax management within firms.

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https://doi.org/https://doi.org/10.1080/21697213.2025.2520220

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@article{yitong2025,
  title        = {{Business-finance integration, tax avoidance and tax risk—empirical evidence based on firm recruitment data}},
  author       = {Yitong Zhao et al.},
  journal      = {China Journal of Accounting Studies},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/21697213.2025.2520220},
}

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Business-finance integration, tax avoidance and tax risk—empirical evidence based on firm recruitment data

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Evidence weight

0.50

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

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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