Journal article
Government Influence on AI investment and energy leakage mitigation technology in SCM: Duality modeling and scenario analysis
Sustainable futures, v 10, 100853
01 Dec 2025
Featured in Collection : UN Sustainable Development Goals @ Drexel
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.
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Details
- Title
- Government Influence on AI investment and energy leakage mitigation technology in SCM: Duality modeling and scenario analysis
- Creators
- Jafar Hussain (Corresponding Author) - Jiangxi University of Water Resources and Electric PowerBenjamin Lev - Drexel UniversityJifan Ren - Harbin Institute of Technology
- Publication Details
- Sustainable futures, v 10, 100853
- Publisher
- Elsevier
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Decision Sciences (and Management Information Systems)
- Web of Science ID
- WOS:001521845700009
- Scopus ID
- 2-s2.0-105008907628
- Other Identifier
- 991022197410104721
UN Sustainable Development Goals (SDGs)
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Source: SDGs in the Output
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Environmental Sciences
- Operations Research & Management Science