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The Use of an Automated System GreenFeed to Monitor Enteric Methane and Carbon Dioxide Emissions from Ruminant Animals

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Green supply chain transformation and emission reduction based on machine learning.

Tao Wu¹, Minxin Zuo¹

¹School of Economics, 12460Jiangxi University of Finance and Economics, Nanchang, China.

Science Progress

|March 27, 2023

Summary

Artificial intelligence (AI) aids green supply chain transformation. Machine learning technology upgrade risks impact market equilibrium only under asymmetric information, highlighting the need for government support.

Keywords:

Carbon emissions artificial intelligence green supply chain transformation investment risk technology upgrade

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Area of Science:

Operations Research
Environmental Economics
Artificial Intelligence

Background:

Global warming and environmental degradation necessitate supply chain transformations.
Artificial intelligence offers new possibilities for sustainable supply chain management.
Carbon emission technologies and machine learning upgrades are key areas of focus.

Purpose of the Study:

To examine a Cournot game model of two competing supply chains.
To analyze the impact of machine learning technology upgrades under varying information scenarios.
To inform government policy for green supply chain initiatives.

Main Methods:

Utilized a Cournot duopoly game model.
Investigated scenarios with symmetric and asymmetric information regarding technology upgrade investment risk.
Modeled different carbon emission technologies.

Main Results:

Under symmetric information, machine learning upgrade risk does not influence market equilibrium.
Under asymmetric information, technology upgrade risk significantly affects equilibrium quantities and prices.
The study identifies critical factors for green supply chain success.

Conclusions:

Government support, including technology and financial aid, is crucial for traditional supply chains to adopt advanced machine learning for carbon emission reduction.
Asymmetric information plays a vital role in competitive supply chain dynamics.
AI-driven upgrades are essential for achieving green supply chain goals.