Posted: Jan 18, 2023
Economic uncertainty represents one of the most significant challenges facing contemporary corporate financial planning and budgeting processes. The traditional approaches to financial planning, which predominantly rely on linear extrapolation and deterministic forecasting models, have demonstrated considerable limitations when confronted with the complex, dynamic nature of modern economic environments. The global financial crisis of 2008, the COVID-19 pandemic, and subsequent geopolitical tensions have highlighted the inadequacy of conventional budgeting methodologies in capturing the profound impacts of systemic economic shocks. This research addresses this critical gap by developing and validating an innovative computational framework that fundamentally reimagines how corporations approach financial planning under conditions of extreme uncertainty. The novelty of our approach lies in its integration of computational intelligence techniques with behavioral economic principles, creating a hybrid methodology that transcends traditional disciplinary boundaries.
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