Scholarlink

<p>While blockchain technology holds transformative potential for cross-border trade, existing studies inadequately address multi-stakeholder incentive misalignment and regulatory fragmentation across jurisdictions. This paper bridges critical gaps: the lack of empirically validated models quantifying dynamic trade-offs among customs (prioritizing compliance), financial institutions (managing risk-return), and enterprises (maximizing profits), and the absence of mechanisms harmonizing blockchain ecosystems with heterogeneous legal frameworks. This study develops a tripartite evolutionary game model integrating cost–benefit parameters and policy adaptation metrics. Using the Hengqin Guangdong-Macao case, empirical analysis demonstrates that blockchain adoption achieves Pareto efficiency. Sensitivity analysis confirms model robustness (± 0.15 parameter variance tolerance), while cross-chain legal compliance protocols resolve of jurisdictional conflicts. Key findings demonstrate that blockchain digital ecosystems enhance trade efficiency by enabling real-time information synchronization, reduce operational risks through immutable transaction records, and alleviate trust barriers via decentralized governance. Results establish that blockchain ecosystems optimize multi-party collaboration only when technical interoperability coexists with dynamic incentive rebalancing, offering policymakers a replicable framework to align decentralized innovation with cross-border regulatory coherence.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

The game theory issues of blockchain digital ecosystem in cross-border trade

  • 期刊论文

  • 发表日期：

    2025年7月25日

查看全文
  • Jie Li,
  • Rui Wang,
  • Xiaotong Cai,
  • Yansheng Chen,
  • Chao Cao

摘要

While blockchain technology holds transformative potential for cross-border trade, existing studies inadequately address multi-stakeholder incentive misalignment and regulatory fragmentation across jurisdictions. This paper bridges critical gaps: the lack of empirically validated models quantifying dynamic trade-offs among customs (prioritizing compliance), financial institutions (managing risk-return), and enterprises (maximizing profits), and the absence of mechanisms harmonizing blockchain ecosystems with heterogeneous legal frameworks. This study develops a tripartite evolutionary game model integrating cost–benefit parameters and policy adaptation metrics. Using the Hengqin Guangdong-Macao case, empirical analysis demonstrates that blockchain adoption achieves Pareto efficiency. Sensitivity analysis confirms model robustness (± 0.15 parameter variance tolerance), while cross-chain legal compliance protocols resolve of jurisdictional conflicts. Key findings demonstrate that blockchain digital ecosystems enhance trade efficiency by enabling real-time information synchronization, reduce operational risks through immutable transaction records, and alleviate trust barriers via decentralized governance. Results establish that blockchain ecosystems optimize multi-party collaboration only when technical interoperability coexists with dynamic incentive rebalancing, offering policymakers a replicable framework to align decentralized innovation with cross-border regulatory coherence.