A Quantitative Study on Digital Transformation and Fiscal Policy in Enhancing Financial Management and Investment Efficiency

Abstract

This study examines the interrelationships among Financial Management and Liquidity, Data Analytics and Financial Models, Investment and Portfolio, and Financing and Financial Markets in influencing Fiscal Policy and Economic Governance to strengthen financial stability and performance. Using a quantitative design with Partial Least Squares–Structural Equation Modeling (PLS-SEM) and bootstrapping analysis through SmartPLS version 3.0, the findings demonstrate that effective financial management and liquidity control significantly enhance capital efficiency and organizational profitability. The integration of data analytics and advanced financial models supported by artificial intelligence (AI) improves risk prediction and supports evidence-based financial decisions. Investment and portfolio diversification, particularly through sustainable and green investment practices, increase rationality in decision-making and promote environmentally responsible growth. Furthermore, financing innovations such as peer-to-peer (P2P) lending and research-based investment contribute to inclusive access to capital and transparency in financial markets. At the macro level, adaptive fiscal policies—through progressive taxation and regional revenue optimization—foster equitable development and economic resilience. Overall, the results confirm that the synergy between micro-level financial efficiency and macro-level fiscal governance is pivotal for creating a resilient, transparent, and sustainable financial system. The study provides theoretical insights and practical implications for policymakers and financial institutions in developing adaptive, digital-based financial models and sustainable fiscal governance aligned with long-term economic transformation.