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Optimizing Reverse Logistics in Retail Sector
Abstract
Reverse Logistics (RL) has become a critical challenge in supply chain management, especially for retail and e-commerce. With online shopping growth, product returns have increased due to sizing issues, quality concerns, and unmet customer expectations. This study analyzes return causes in online apparel shopping and proposes cost optimization strategies. Our findings show that understanding return drivers—fit issues, quality mismatches, and delivery delays—helps businesses reduce returns and enhance customer satisfaction. The research emphasizes adopting AI, blockchain, and IoT technologies to improve reverse logistics efficiency. Recommendations include implementing centralized return centers, automating supply chains, and educating customers to minimize costs. The study highlights RL's role in sustainability through recycling, refurbishment, and waste reduction practices. This research provides valuable insights for students, academics, and industry professionals seeking to address RL challenges and enhance supply chain sustainability in the apparel industry and beyond.
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