Public company audits are not homogenous. Varying audit partner attributes, including gender, age, location, and expertise, play important roles in explaining audit outcome disparities. The extant literature underscores the influence of firm-level and office-level differences, in areas such as size, culture, and industry expertise, in shaping audit outcomes. Commonwealth countries, such as the U.K., Australia, New Zealand, and Continental European countries, along with Asian economic entities, mandate the disclosure of audit partner names. Consequently, significant research efforts have been devoted to investigating the impact of audit partner characteristics on audit outcomes in these jurisdictions. With the adoption of Public Company Accounting Oversight Board (PCAOB) Rule 3211, mandating disclosure of audit engagement partner details for U.S.-registered public accounting firms on Form AP, there has been a surge in U.S. firm research exploring the significance of audit partner characteristics on audit outcomes in recent years. This paper outlines research that considers audit partner attributes’ influence on audit partner selection and audit quality across different economic entities. This entry contributes by synthesizing findings from recent research across diverse economic contexts, including the recently available insights from U.S.-based audits. The analysis of this entry not only provides insights into the current state of audit partner research but also delineates avenues for future research on this topic.

Information cascades refer to a type of learning behavior in social networks where individuals make decisions by observing the actions of others, rather than relying solely on their own private information. Network centrality, which measures the relative importance or influence of a node within a network, plays a significant role in initiating and shaping information cascades across four key dimensions. First, nodes with high degree centrality often initiate information cascades due to their large number of direct connections to other nodes. Second, nodes with high betweenness centrality serve as bridges between different parts of the network, thereby controlling the flow of cascading information. Third, nodes with high closeness centrality can access and disseminate information more quickly, accelerating the spread of cascades throughout the network. Fourth, nodes with high eigenvector centrality augment the impact of information cascades through their visibility and connections to other influential nodes. Synthesizing research findings on executive and director networks from management, finance, and accounting, this entry provides insights into emerging trends in corporate governance by highlighting the interaction between network structure and information dissemination.

Information cascades refer to a type of learning behavior in social networks where individuals make decisions by observing the actions of others, rather than relying solely on their own private information. Network centrality, which measures the relative importance or influence of a node within a network, plays a significant role in initiating and shaping information cascades across four key dimensions. First, nodes with high degree centrality often initiate information cascades due to their large number of direct connections to other nodes. Second, nodes with high betweenness centrality serve as bridges between different parts of the network, thereby controlling the flow of cascading information. Third, nodes with high closeness centrality can access and disseminate information more quickly, accelerating the spread of cascades throughout the network. Fourth, nodes with high eigenvector centrality augment the impact of information cascades through their visibility and connections to other influential nodes. Synthesizing research findings on executive and director networks from management, finance, and accounting, this entry provides insights into emerging trends in corporate governance by highlighting the interaction between network structure and information dissemination.

Public company audits are not homogenous. Varying audit partner attributes, including gender, age, location, and expertise, play important roles in explaining audit outcome disparities. The extant literature underscores the influence of firm-level and office-level differences, in areas such as size, culture, and industry expertise, in shaping audit outcomes. Commonwealth countries, such as the U.K., Australia, New Zealand, and Continental European countries, along with Asian economic entities, mandate the disclosure of audit partner names. Consequently, significant research efforts have been devoted to investigating the impact of audit partner characteristics on audit outcomes in these jurisdictions. With the adoption of Public Company Accounting Oversight Board (PCAOB) Rule 3211, mandating disclosure of audit engagement partner details for U.S.-registered public accounting firms on Form AP, there has been a surge in U.S. firm research exploring the significance of audit partner characteristics on audit outcomes in recent years. This paper outlines research that considers audit partner attributes’ influence on audit partner selection and audit quality across different economic entities. This entry contributes by synthesizing findings from recent research across diverse economic contexts, including the recently available insights from U.S.-based audits. The analysis of this entry not only provides insights into the current state of audit partner research but also delineates avenues for future research on this topic.

Artificial intelligence (AI), data analytics, cloud-based systems, and other digital technologies are increasingly integrated into audit practice, creating new opportunities for audit effectiveness while also changing the relationships and resources on which auditors depend. Drawing on Resource Dependence Theory, we develop a conceptual framework examining both the potential benefits and independence risks associated with this dependence. Technology may support auditor objectivity by reducing certain forms of human judgment bias, improving analytical accuracy, and promoting more consistent audit procedures. At the same time, reliance on client and third-party systems, limited transparency into technology-generated outputs, shared technological infrastructure, and self-review concerns may create new challenges for auditor autonomy and professional judgment. We further consider potential safeguards, including auditor control over critical audit processes, appropriate human oversight of technology-assisted judgments, and governance and regulatory monitoring of material technology dependencies. By extending auditor independence beyond the traditional auditor–client relationship to consider the technological environment, this paper identifies implications for auditor independence and assurance quality and develops avenues for future research as audit practice continues to evolve. The framework differentiates economic, operational, and informational dependence and develops propositions linking these dimensions to auditor autonomy, independence in fact, independence in appearance, professional skepticism, and assurance quality.