Article2024

Intelligent manufacturing, auditor selection and audit quality

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Auditing, Earnings Management, Governance Accounting and Organizational Management Corporate Governance and Financial Management

Abstract

Purpose The purpose of this paper is to examine the influence of intelligent manufacturing on audit quality and its underlying mechanism as well as the variation in this influence across different types of organizations. Design/methodology/approach This research utilizes a difference-in-differences (DID) method to examine how enterprises that apply intelligent manufacturing choose auditors and impact their audit work. The study is based on 15,228 observations of Chinese-listed A-shares from 2011 to 2020. Findings (1) There is a strong correlation between intelligent manufacturing and audit quality. (2) This positive correlation is statistically significant only in state-owned enterprises (SOEs), those that have steady institutional investors and where the roles of the CEO and chairman are distinct. (3) Enterprises that have implemented intelligent manufacturing are more inclined to employ auditors who possess extensive industry expertise. The auditor's industry expertise plays a crucial role in ensuring audit quality. (4) The adoption of intelligent manufacturing also leads to higher audit fees and longer audit delay periods. Practical implications This paper validates the beneficial impact of intelligent manufacturing on improving corporate governance. In addition, it is recommended that managers prioritize the involvement of skilled auditors with specialized knowledge in the industry to ensure the high audit quality and the transparency of information in intelligent manufacturing enterprises. Originality/value This study builds upon previous research that has shown the importance of artificial intelligence in enhancing audit procedures. It contributes to the existing body of knowledge by examining how enterprise intelligent manufacturing systems (IMS) enhance audit quality. Additionally, this study provides valuable information on how to improve audit quality in the field of intelligent manufacturing by strategically selecting auditors based on resource dependency theory.

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References

1986Large Shareholders and Corporate Control 1994Politicians and Firms 2010Big Bad Banks? The Winners and Losers from Bank Deregulation in the United States 2014A review of archival auditing research 2018Robots at Work 1981Auditor independence, ‘low balling’, and disclosure regulation 2015The effect of institutional ownership on firm transparency and information production 2011A Framework for Understanding and Researching Audit Quality

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