Posted: Sep 15, 2023
The contemporary landscape of multinational corporate governance presents unprecedented challenges for auditing practices, necessitating innovative approaches to understanding the complex dynamics between internal and external auditing functions. Traditional auditing research has predominantly treated these two domains as separate entities operating under different mandates and constraints. However, this binary perspective fails to capture the intricate interdependencies and emergent properties that characterize modern corporate auditing ecosystems. This research introduces a novel computational framework that reconceptualizes auditing practices as interconnected networks operating within complex organizational systems. Our study addresses a significant gap in the literature by examining how internal and external auditing practices co-evolve and influence each other in multinational corporations. The multinational context introduces additional layers of complexity due to varying regulatory environments, cultural differences, and operational scales that transcend national boundaries. Previous research has largely focused on either internal or external auditing in isolation, with limited attention to their synergistic or antagonistic interactions. This paper bridges this gap through an interdisciplinary approach that combines network theory, machine learning, and organizational science.
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