Government Influence on AI investment and energy leakage mitigation technology in SCM: Duality modeling and scenario analysis

• Effective SCM strategies for mitigating energy leakage and optimizing costs. • AI integration reduces energy leakage and operational costs in SCM. • Simulation-based duopoly models identify optimal decisions for sustainability. • Collaborative investments enhance long-term profitability and market competitiveness. This study investigates the economic dynamics within a supply chain management (SCM) involving manufacturers, agents, and retailers. It focuses on strategies to mitigate energy leakage (EL) through the integration of artificial intelligence (AI) technology and the imposition of EL taxes. A simulation-based optimization model is used to find different optimal scenarios. Through a series of optimized scenarios, the research examines the impacts of these interventions on SCM efficiency, profitability, and sustainability. The findings reveal that while the introduction of EL taxes initially increases operational costs, it effectively causes an improvement in energy efficiency. At the same time, significant investments in AI technology reduce energy wastage, leading to enhanced profitability and sustainability across the SCM. The research concludes with recommendations for SCM entities to actively invest in AI technology and for governments to impose taxes as a penalty. Additionally, it suggests further exploration of collaborative investments and emerging technologies to enhance SCM sustainability.

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Publication Details

Journal
Sustainable Futures
Published
2025-06-16
DOI
https://doi.org/10.1016/j.sftr.2025.100853
Citations
1
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
Field-Weighted Citation Impact
2.23
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article

Government Influence on AI investment and energy leakage mitigation technology in SCM: Duality modeling and scenario analysis

Jafar Hussain, Benjamin Lev, Jifan Ren
1 citations
Sustainable Futures
Supply Chain Resilience and Risk Management
2.23
article

Government Influence on AI investment and energy leakage mitigation technology in SCM: Duality modeling and scenario analysis

Jafar Hussain, Benjamin Lev, Jifan Ren
article en
1 citations

Abstract

• Effective SCM strategies for mitigating energy leakage and optimizing costs. • AI integration reduces energy leakage and operational costs in SCM. • Simulation-based duopoly models identify optimal decisions for sustainability. • Collaborative investments enhance long-term profitability and market competitiveness. This study investigates the economic dynamics within a supply chain management (SCM) involving manufacturers, agents, and retailers. It focuses on strategies to mitigate energy leakage (EL) through the integration of artificial intelligence (AI) technology and the imposition of EL taxes. A simulation-based optimization model is used to find different optimal scenarios. Through a series of optimized scenarios, the research examines the impacts of these interventions on SCM efficiency, profitability, and sustainability. The findings reveal that while the introduction of EL taxes initially increases operational costs, it effectively causes an improvement in energy efficiency. At the same time, significant investments in AI technology reduce energy wastage, leading to enhanced profitability and sustainability across the SCM. The research concludes with recommendations for SCM entities to actively invest in AI technology and for governments to impose taxes as a penalty. Additionally, it suggests further exploration of collaborative investments and emerging technologies to enhance SCM sustainability.

Sustainable FuturesVol. 10
Jiangxi University of Water Resources and Electric Power (CN), Guangdong Medical College (CN), Harbin Institute of Technology (CN), Yan'an University (CN), Drexel University (US)
Openalex Percentile: Top 11%
Supply Chain Resilience and Risk Management
2.23
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Government Influence on AI investment and energy leakage mitigation technology in SCM: Duality modeling and scenario analysis — Jafar Hussain, Benjamin Lev, et al. · Sustainable Futures (2025) | TGRS Research Map | TGRS