Theoretical Analysis of the Quality of Corporate Financial Information under the New Revenue Standard
From the Perspective of Accounting Conservatism
DOI:
https://doi.org/10.62051/ijgem.v8n3.12Keywords:
New Revenue Standard, Accounting Conservatism, Quality of Financial InformationAbstract
The deepening of global economic integration has promoted the gradual convergence of accounting standard systems across countries, particularly regarding reforms in the critical field of revenue recognition. International Financial Reporting Standards (IFRS) have undergone continuous revisions and been widely adopted worldwide. China’s accounting standards have gradually converged with international standards over the past few years. Notably, in 2017, the Ministry of Finance issued Accounting Standard for Business Enterprises No. 14 - Revenue, which has been implemented since 2018. The introduction of this new revenue standard marks a major transformation of China’s accounting system. This study aims to explore how the new revenue standard affects the quality of corporate financial information. Specifically, from the perspective of accounting conservatism, it analyzes how enterprises balance flexibility and conservatism while complying with the new standard to ensure the reliability and relevance of financial information. This research holds significant theoretical and practical value for improving the theory of revenue recognition, enhancing the transparency of corporate financial reports, and providing policy recommendations for regulatory authorities.
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[1] Wei, X. B. (2025). Strategies for improving the quality of corporate financial accounting information from the perspective of ESG. Brand Marketing of Time-Honored Brands, (17), 127-129.
[2] Guo, S. S. (2025). On how to effectively improve the quality of corporate financial accounting information in the era of big data. Guide to Township Enterprises, (16), 120-122.
[3] Mu, K. F. (2025). The impact of accounting information quality on corporate financial decision-making under digital transformation. Financial News, (16), 179-181.
[4] Wang, H. R., Li, T. Y., Tang, S. Y., et al. (2025). A method for evaluating the quality of corporate financial information combining machine learning and expert experience—from the perspective of bank wealth management companies. Fiscal Supervision, (15), 98-104.
[5] Zhang, X. Y. (2025). A study on the relationship between corporate financial risk management and control and accounting information quality. Financial News, (12), 155-157.
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