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Big Data in the Tax Office: How Tax Enforcement Shapes Corporate Innovation

Liguang Zhang et al.

Journal of International Financial Management and Accounting2026https://doi.org/10.1111/jifm.70012article
AJG 2ABDC A
Weight
0.50

Abstract

While prior research has examined how tax policy affects corporate innovation, the impact of tax enforcement in a digital governance setting remains unclear. This study analyzes how tax enforcement shapes firm innovation by exploiting the rollout of the tax administration information system reform as a quasi‐natural experiment and applying a staggered difference‐in‐differences design to Chinese A‐share listed firms from 2007 to 2022. The results show that intensified tax enforcement is associated with a significant increase in corporate R&D investment, especially for firms subject to stronger governmental tax pressure, weaker external information environments, lower market competition, and stronger tax avoidance incentives. Mechanism analyses show that improved information transparency, which relaxes financing constraints and mitigates managerial career concerns, is the primary channel, rather than R&D manipulation. Overall, the findings enrich the literature on the economic consequences of tax enforcement, advance understanding of the institutional drivers of innovation, and highlight the role of information technology in modern tax administration and innovation‐oriented tax design.

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https://doi.org/https://doi.org/10.1111/jifm.70012

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@article{liguang2026,
  title        = {{Big Data in the Tax Office: How Tax Enforcement Shapes Corporate Innovation}},
  author       = {Liguang Zhang et al.},
  journal      = {Journal of International Financial Management and Accounting},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1111/jifm.70012},
}

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Big Data in the Tax Office: How Tax Enforcement Shapes Corporate Innovation

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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

† 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.