<p>This study introduces a sustainable Economic Production Quantity (EPQ) model tailored for online retail systems handling perishable and short shelf-life products, where customer cancellations pose financial and environmental challenges. Unlike conventional models that treat cancelled orders as waste, the proposed framework implements a conditional refund mechanism, where partial refunds are issued only if the cancelled product is successfully resold at a discounted price. The model captures dynamic inventory behavior under customer cancellations, time-decaying resale probabilities, refund conditions, and carbon credit incentives. Notably, the refund policy is directly linked to resale success and environmental performance via credits earned for each successful resale. Two scenarios are compared: a baseline EPQ model without refunds and a refund-responsive model that jointly optimizes production parameters and resale discount. Two metaheuristic techniques—Weighted Particle Swarm Optimization (WPSO) and Constriction Factor PSO (CPSO)—are employed to solve the nonlinear optimization problem. Results show that the refund-responsive strategy improves total profit by 16.3%, with approximately 70% of cancelled items resold and contributing 6.57% to total revenue. Carbon credits offset some refund liability, enhancing the model’s circularity and environmental alignment. This work offers a practical tool for online retailers to reduce inventory waste, improve profitability, and integrate refund policies with circular economy objectives.</p>

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A Circular Inventory Model for Perishable E-Commerce Goods with Resale-Triggered Refunds and Carbon Credit Incentives

  • Prabal Das,
  • Nabendu Sen

摘要

This study introduces a sustainable Economic Production Quantity (EPQ) model tailored for online retail systems handling perishable and short shelf-life products, where customer cancellations pose financial and environmental challenges. Unlike conventional models that treat cancelled orders as waste, the proposed framework implements a conditional refund mechanism, where partial refunds are issued only if the cancelled product is successfully resold at a discounted price. The model captures dynamic inventory behavior under customer cancellations, time-decaying resale probabilities, refund conditions, and carbon credit incentives. Notably, the refund policy is directly linked to resale success and environmental performance via credits earned for each successful resale. Two scenarios are compared: a baseline EPQ model without refunds and a refund-responsive model that jointly optimizes production parameters and resale discount. Two metaheuristic techniques—Weighted Particle Swarm Optimization (WPSO) and Constriction Factor PSO (CPSO)—are employed to solve the nonlinear optimization problem. Results show that the refund-responsive strategy improves total profit by 16.3%, with approximately 70% of cancelled items resold and contributing 6.57% to total revenue. Carbon credits offset some refund liability, enhancing the model’s circularity and environmental alignment. This work offers a practical tool for online retailers to reduce inventory waste, improve profitability, and integrate refund policies with circular economy objectives.