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RETRACTED ARTICLE: Enhancing Economic Resilience Through Multi-source Information Fusion in Financial Inclusion: A Big Data Analysis Approach

  • Tzung-Feng Hu,
  • Fu-Sheng Tsai

摘要

In an era marked by economic volatility and complex global dynamics, assessing and enhancing economic resilience are of paramount importance. This research paper, submitted to the Journal of the Knowledge Economy, introduces a comprehensive approach to understanding and improving economic resilience through the lens of financial inclusion. As the global economy faces unprecedented challenges, financial inclusion, which extends financial services to the general public, becomes a vital indicator of economic stability and resilience. This study employs a cutting-edge big data analysis method that leverages multi-source information fusion. By integrating data from diverse sources, including user profiling, risk assessment, financial product design, and financial operation information, our approach provides a real-time assessment of economic resilience. Through the application of this method, economies can gain a deeper understanding of their economic situation and resilience, aiding policymakers in decision-making and fostering social stability. The paper delves into the impact of financial inclusion on economic resilience, emphasizing the role of digital inclusive finance in improving economic structure and stability. It also presents experimental results, demonstrating the superiority of the proposed method over existing spatio-temporal sequence processing techniques in predicting financial inclusion and assessing economic resilience. In conclusion, this research paper offers a valuable contribution to the fields of knowledge economy, innovation, and entrepreneurship, as it provides insights and tools to enhance economic resilience in the face of an ever-changing global landscape.