Network Connectedness and the Convergence of Audit Styles

• In Event: Auditor Networks

Abstract

Viewing audit teams as social groups of auditors, we utilize network analysis algorithm “n-clans” to identify clustering of individual auditors, i.e., audit teams, based on individual collaboration history. Drawing upon social learning theory, we argue that team network connectedness, specifically network density and closeness, shapes the similarity in the audit style and audit pricing among team members. Exploiting a fixed-effect approach, we first validate the team construct by revealing the existence of team styles, which affect audited financial statements, audit reporting as well as audit fees in a significant manner. Using the dispersion of discretionary accrual, audit reporting aggressiveness, and audit fee premium as inverse measures of audit style and audit pricing similarity, we find that more closely connected teams exhibit lower within-team variation in audit outcomes and audit fees. This result is mainly driven by team connectedness between dissimilar auditors instead of between similar auditors. Further, the role of network connectedness for the within-team convergency of audit style and audit pricing is more pronounced for non-Big 4 firms where firm-level quality control is less robust, for teams with junior auditors who likely benefit more from social learning, and for teams with more divergent clients. The main finding is robust to tests based on exogenous increases in network connectedness following audit firm mergers and acquisitions. Network density and closeness also strengthen the relation between audit team style and the audit outcomes and audit pricing of team members. We extend prior literature by identifying audit team as a relevant unit of the analysis for audit production and revealing the importance of network connectedness for achieving more consistent audit outcomes within an audit team.

Authors

• Lin Wang, Central University of Finance and Economics

• Donghui Wu, The Chinese University of Hong Kong

• Yuping Zhao, University of Houston