Acknowledgment to the Reviewers of Journal of Environmental & Earth Sciences in 2025
2026-02-06
Eco-Intelligent Trade Networks: AI Applications in Regional Economic Development and Their Implications for Environmental Management
Authors
-
Na Wang
Tourism and E-Commerce College, Baise University, Baise 533000, China
DOI:
https://doi.org/10.30564/jees.v8i5.13035Abstract
Eco-intelligent trade networks are emerging as a critical governance frontier where regional economic development and environmental management intersect. With the increase in networked production and logistics systems, the environmental issues of greenhouse gas emissions, air contamination, water stress, and land-use change spread across jurisdiction by trade. Artificial intelligence can provide new functionality to monitor, assign, and control these impacts because it combines the different streams of heterogeneous data, such as customs and transaction data, logistics telemetry, remote sensing data, facility monitoring data, and corporate disclosures. The review is a synthesis of artificial intelligence (AI) applications that help in direct support of environmental management functions in trade networks, i.e., monitoring and anomaly detection, measurement-reporting-verification, risk-based enforcement targeting, and regulatory decision support. It also looks at the operationalization of AI-enabled intelligence using policy tools and corporate practices such as green corridors and smart ports, sustainable procurement and due diligence, certification, and claims verification, green upgrading industrial policy, and environmentally linked finance-based risk management. In these spheres, it can be seen that AI can enhance transparency and resource distribution, although the results will rely on the backbone of data and accounting, institutional capabilities, as well as governance protections. Major risks are rebound effects, which increase overall burdens with efficiency increase, a burden on less monitored areas and suppliers, and exclusion of data-poor suppliers and regions, and obscurity, which adversely affects procedural legitimacy. The review frames AI as a component of an auditable decision system and not a context-independent tool of optimization, offering priorities to priorities on causal assessment, benchmarking, and inclusive guidelines to implementation.
Keywords:
Artificial Intelligence; Trade Networks; Regional Development; Environmental Management; Measurement, Reporting, and Verification (MRV)References
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Wang, N. (2026). Eco-Intelligent Trade Networks: AI Applications in Regional Economic Development and Their Implications for Environmental Management. Journal of Environmental & Earth Sciences, 8(5), 48–82. https://doi.org/10.30564/jees.v8i5.13035
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