This study primarily aims to contribute to the auditing, more specifically business risk audit literature by examining the opportunities and challenges that auditors face when processing and integrating ESG risk with financial information, as well as their inherent impact on audit quality (AQ).

The objective of this project is to support audit firms in managing auditors’ process of personal and professional adaptation to AI in ways that ensure the realization of the potential associated with AI.

The overarching goal of this research project is to better understand whether and how the organizational setting of Big 4 and mid-sized audit firms differs, and whether these differences impact audit quality.

This project will especially focus on quantifying the relationship between social learning from errors and audit quality, considering the role that a firm’s error management climate (EMC) plays in fostering learning behaviors in individual auditors, addressing three key gaps in extant research.

The overall purpose of this project is to investigate how the characteristics of decision support systems (DSS) drive auditors’ reliance on these systems.

Investment in technology on audit engagements has increased in recent years and is expected to continue to do so.