E-Commerce Supply Chain Resilience and Sustainability Through AI-Driven Demand Forecasting and Waste Reduction

The rapid growth of e-commerce demands innovative solutions for resilient and sustainable supply chains. This study explores the role of AI-driven demand forecasting (AIDF) and AI-driven waste reduction (AIDWR) in enhancing supply chain efficiency, minimizing operational waste, and fostering sustainability. Analyzing data from 539 samples via PLS-SEM, the findings highlight how AIDF optimizes demand accuracy, reduces overproduction, and minimizes stockouts, while AIDWR lowers resource consumption and mitigates environmental impacts. Operational Waste Reduction mediates AI’s effectiveness, aligning efficiency with sustainability goals and promoting adaptable, environmentally conscious supply chains. These insights guide e-commerce managers in leveraging AI for resilience and sustainable growth. The study underscores the transformative potential of AI to meet dual objectives of operational excellence and sustainability.

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Publication Details

Journal
Sustainability
Published
2025-12-30
DOI
https://doi.org/10.3390/su18010360
Primary Topic
Supply Chain Resilience and Risk Management
Type
article
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article

E-Commerce Supply Chain Resilience and Sustainability Through AI-Driven Demand Forecasting and Waste Reduction

Daoping Wang, Shafiul Bashar, Hanxi Dong
Sustainability
Supply Chain Resilience and Risk Management
article

E-Commerce Supply Chain Resilience and Sustainability Through AI-Driven Demand Forecasting and Waste Reduction

Daoping Wang, Shafiul Bashar, Hanxi Dong
article en

Abstract

The rapid growth of e-commerce demands innovative solutions for resilient and sustainable supply chains. This study explores the role of AI-driven demand forecasting (AIDF) and AI-driven waste reduction (AIDWR) in enhancing supply chain efficiency, minimizing operational waste, and fostering sustainability. Analyzing data from 539 samples via PLS-SEM, the findings highlight how AIDF optimizes demand accuracy, reduces overproduction, and minimizes stockouts, while AIDWR lowers resource consumption and mitigates environmental impacts. Operational Waste Reduction mediates AI’s effectiveness, aligning efficiency with sustainability goals and promoting adaptable, environmentally conscious supply chains. These insights guide e-commerce managers in leveraging AI for resilience and sustainable growth. The study underscores the transformative potential of AI to meet dual objectives of operational excellence and sustainability.

SustainabilityVol. 18(1)
Beijing Information Science & Technology University (CN), University of Science and Technology Beijing (CN)
Responsible consumption and production
Openalex Percentile: Top 23%
Supply Chain Resilience and Risk Management
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E-Commerce Supply Chain Resilience and Sustainability Through AI-Driven Demand Forecasting and Waste Reduction — Daoping Wang, Shafiul Bashar, et al. · Sustainability (2025) | TGRS Research Map | TGRS