Posted: Oct 12, 2023
The relationship between audit quality and corporate financial performance represents a fundamental question in accounting and corporate governance research. Traditional approaches have predominantly employed linear regression models to examine correlations between audit quality proxies and financial metrics, yielding mixed and often contradictory results. This research introduces a paradigm shift by conceptualizing audit quality as a complex system of interconnected signals rather than isolated variables. We propose that the conventional methodological framework fails to capture the multidimensional nature of how audit quality influences financial outcomes across different organizational contexts and temporal scales. Our research addresses several critical gaps in existing literature. First, we challenge the assumption of linear relationships between audit quality indicators and financial performance, proposing instead that these relationships exhibit threshold effects, network dependencies, and temporal dynamics that require sophisticated computational approaches. Second, we introduce methodologies from computer science domains, particularly network security and anomaly detection, to identify patterns in audit quality that traditional accounting research has overlooked. Third, we expand the definition of financial performance beyond conventional metrics to include stability indicators, risk-adjusted returns, and forward-looking measures derived from textual analysis of corporate communications.
Downloads: 96
Abstract Views: 2099
Rank: 464977