AI Adoption, Reporting Quality, and Romanian Listed Firms' Market Value: Artificial Neural Networks Approach
Keywords:
Artificial Intelligence Adoption, Financial Reporting Quality, Market Value, Bucharest Stock Exchange, Discretionary Accruals, Multi-layer PerceptronAbstract
This study examines the impact of corporate Artificial Intelligence (AI) adoption on Financial Reporting Quality (FRQ) and Market Value for technology firms listed on the Bucharest Stock Exchange (2020–2024). Using 150 firm-year observations, the research pairs linear Ordinary Least Squares (OLS) regressions with a non-linear Multi-layer Artificial Neural Network (ANN). OLS results indicate that higher AI disclosure improves FRQ by reducing discretionary accruals, while both AI adoption and enhanced FRQ positively signal market value (Tobin’s Q). Crucially, the ANN framework radically outpaces the linear model (R² = 0.91 vs. 0.64), proving that technological innovation valuation is fundamentally non-linear. Feature importance profiling identified AI disclosure as the primary market value predictor (28.5% weight). Consequently, AI integration acts as a potent corporate governance tool and value driver, justifying regulatory calls for standardized digital disclosure mandates.
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