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<p>This study investigates the evolving dynamics of East Asian economic integration by examining how green technology adoption mitigates geopolitical risks and fosters sustainable regional development. Employing a dual-level analytical framework, we combine macroeconomic trend analysis—anchored in the Environmental Kuznets Curve (EKC) model—with focused case studies, notably China’s Belt and Road Initiative (BRI) and the regional development of Xuzhou. We introduce a neural-network forecasting model that captures nonlinear interactions between economic expansion and environmental indicators, achieving a prediction accuracy of 95.37%. Our empirical results demonstrate that strategic green-technology investments not only soften the income–pollution trade-off but also enhance resilience to external shocks. The Xuzhou case further illustrates how coupling-coordination analysis can guide local policy by identifying key drivers that harmonize urban growth with ecological capacity. By integrating data-driven modeling with predictive analysis, this research provides actionable insights for policymakers seeking to balance economic growth with environmental stewardship across East Asia.</p>

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Data-Driven Green Technology Integration and Geopolitical Risks in East Asian Economic Development: A Predictive Analysis

  • 期刊论文

  • 发表日期：

    2025年10月23日

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  • Kang Meng,
  • Ying Wang

摘要

This study investigates the evolving dynamics of East Asian economic integration by examining how green technology adoption mitigates geopolitical risks and fosters sustainable regional development. Employing a dual-level analytical framework, we combine macroeconomic trend analysis—anchored in the Environmental Kuznets Curve (EKC) model—with focused case studies, notably China’s Belt and Road Initiative (BRI) and the regional development of Xuzhou. We introduce a neural-network forecasting model that captures nonlinear interactions between economic expansion and environmental indicators, achieving a prediction accuracy of 95.37%. Our empirical results demonstrate that strategic green-technology investments not only soften the income–pollution trade-off but also enhance resilience to external shocks. The Xuzhou case further illustrates how coupling-coordination analysis can guide local policy by identifying key drivers that harmonize urban growth with ecological capacity. By integrating data-driven modeling with predictive analysis, this research provides actionable insights for policymakers seeking to balance economic growth with environmental stewardship across East Asia.