The effect of enterprise digital transformation on audit efficiency—Evidence from China
Aolin Leng and
Yue Zhang
Technological Forecasting and Social Change, 2024, vol. 201, issue C
Abstract:
The digital transformation of enterprises is the key to conforming to the trends of the times and realizing reform and innovation. Digital transformation will change the enterprise risk and information environment, and also bring challenges to the audit business. This study takes China's Shanghai and Shenzhen A-share listed companies from 2011 to 2021 as a sample, starting from the perspective of audit delay, and empirically tests the impact of enterprise digital transformation on audit efficiency. The results of the study found that the higher the degree of enterprise digital transformation, the more serious the audit delay and the lower the audit efficiency. Further research found that in non-high-tech enterprises and when audited by non-international “Big 4” and accounting firms without digital expertise, the effect of enterprise digital transformation on reducing audit efficiency is more obvious. This study expands the research field of enterprise digital transformation and auditing and provides empirical evidence for improving auditing efficiency.
Keywords: Digital transformation; Audit efficiency; Audit delay; China (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0040162524000118
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:201:y:2024:i:c:s0040162524000118
DOI: 10.1016/j.techfore.2024.123215
Access Statistics for this article
Technological Forecasting and Social Change is currently edited by Fred Phillips
More articles in Technological Forecasting and Social Change from Elsevier
Bibliographic data for series maintained by Catherine Liu ().