Does Artificial Intelligence (AI) enhance green economy efficiency? The role of green finance, trade openness, and R&D investment
Unlocking Green Economic Efficiency in Marine Fisheries with AI
This study analyzes the impact of Artificial Intelligence (AI) on the green economic efficiency of marine fisheries in China's coastal regions from 2009 to 2020. Utilizing the entropy method and Super-EBM model, we identify AI as a significant enhancer of efficiency, with green finance, trade openness, and R&D investment acting as crucial moderating factors. These findings offer vital guidance for sustainable marine development.
Executive Impact at a Glance
Key performance indicators highlighting the immediate value of AI adoption.
AI Impact on Efficiency
Green Finance Amplification
R&D Investment Threshold
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Direct AI Impact
AI significantly improves the green economic efficiency of marine fisheries through optimized resource allocation, reduced production costs, enhanced information flow, and improved environmental monitoring.
Moderating Factors
Green finance, trade openness, and R&D investment are crucial moderating variables that accelerate AI development and further enhance the green economic efficiency of marine fisheries.
AI Development & Efficiency
The study reveals a comprehensive framework for assessing AI development in marine fisheries, highlighting its role in enhancing overall efficiency and sustainability.
Threshold Effects
The impact of AI on green economic efficiency varies non-linearly across different intervals of green finance, trade openness, and R&D investment, indicating critical thresholds for optimal impact.
Policy Implications
The findings are crucial for understanding and advancing the informatization strategy of marine fisheries, holding significant implications for the sustainable development of global marine fisheries.
AI's Direct Enhancement of Green Efficiency
AI positively and significantly impacts green economic efficiency (0.033, 5% significance).Combined Boost from AI and Moderating Factors
Green finance, trade openness, and R&D investment significantly amplify AI's positive effect.Enterprise Process Flow
Entropy Method & Super-EBM Model
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Fixed Effects Model
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Moderation Effect Model
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Panel Threshold Model
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Comprehensive AI Impact Assessment
| Moderator | Low Threshold Impact | High Threshold Impact |
|---|---|---|
| Green Finance |
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| Trade Openness |
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| R&D Investment |
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Strategic Recommendations for Sustainable Marine Fisheries
Policymakers should establish special funds for AI projects in marine fisheries, refine financial regulatory frameworks for AI technologies, actively negotiate favorable trade terms, and increase fiscal support for AI technology R&D. These measures will foster technological innovation and enhance environmental protection, ensuring resource preservation and economic efficiency for coastal fisheries.
Advanced AI ROI Calculator
Our advanced ROI calculator helps enterprises quantify the potential green economic efficiency improvements and cost savings by integrating AI into marine fisheries operations. Input your organizational data to see tailored estimates.
Estimated Annual Savings
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Productive Hours Reclaimed Annually
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Implementation Timeline & Key Phases
A structured approach ensures successful AI integration and maximized green economic efficiency. Here's a typical roadmap:
Phase 1: AI Readiness Assessment & Strategy
Evaluate current infrastructure, data readiness, and organizational capabilities. Define clear objectives for AI integration to enhance green economic efficiency.
Phase 2: Pilot Program & Technology Integration
Implement AI technologies in a controlled pilot environment. Focus on optimizing resource allocation, reducing waste, and improving information flow.
Phase 3: Scaling & Moderating Factor Alignment
Expand AI applications across the organization. Align with green finance, trade openness, and R&D investment strategies to amplify AI's impact.
Phase 4: Continuous Optimization & Monitoring
Regularly monitor AI performance, environmental impact, and economic efficiency. Use feedback loops for continuous improvement and adaptation to market changes.
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