Optimal Refund and Ordering Decisions for Fresh Produce E-Commerce Platform: A Comparative Analysis of Refund Policies

Different refund policies offered by e-commerce platforms provide diverse options for consumers and are crucial for enhancing after-sales service. This study constructs a refund and ordering decision model based on three typical refund policies: both basic refund and refund guarantee option (‘Policy I’), basic refund only (‘Policy II’), and refund guarantee option only (‘Policy III’). We examine scenarios where demand is influenced by price, refund policies, and stochastic factors, and returns are affected by refund policies, aiming to determine the optimal refund and ordering decisions for fresh produce e-commerce platforms. Our results indicate that, under the same parameters, the platform achieves the maximum order quantity and highest expected profit with Policy I. The return rate under Policy I is always higher than under Policy III, but not consistently higher than under Policy II. Additionally, as the sensitivity of demand to the refund policy increases, both the order quantity and basic refund price rise, while the refund guarantee option price decreases. Conversely, as the sensitivity of returns to the refund policy increases, the opposite occurs. Although market demand uncertainty does not impact the basic refund or refund guarantee option prices, the platform must increase order quantities to manage market volatility.