A Review of AI-Driven Dynamic Pricing and Emission Reduction Strategies in Green Supply Chains

Pengfei Hong; Weiyan Chen

doi:10.54691/501r5m22

Authors

Pengfei Hong Translator
Weiyan Chen

DOI:

https://doi.org/10.54691/501r5m22

Keywords:

Artificial Intelligence; Dynamic Pricing; Emission Reduction Strategies; Green Supply Chain Management; Machine Learning.

Abstract

This paper reviews the application of artificial intelligence technologies in green supply chain management, with a particular focus on the integration of dynamic pricing mechanisms and emission reduction strategies. As global attention to climate change increases, companies face the dual challenge of reducing carbon emissions while maintaining economic benefits. Artificial intelligence is reshaping green supply chain management practices by providing data-driven decision support, optimizing pricing strategies, and allocating resources efficiently. This review analyzes current research progress, application cases, and discusses future directions and challenges, aiming to provide a systematic reference framework for both academia and industry.

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