Analysis of post-sale reverse logistics in e-commerce with a dropshipping management model: A case study

The e-commerce model leveraging dropshipping offers significant flexibility but grapples with critical challenges in reverse logistics. This study examined the primary causes of product returns within a retail company operating under the dropshipping model and proposed enhancements to its reverse logistics processes. Using tools such as the Ishikawa diagram and statistical analysis, the research investigated common issues like damaged goods, undelivered items, and incorrect shipments. Findings revealed operational inefficiencies and gaps in supplier communication. Proposed solutions include stricter operational controls, the use of more durable packaging, and the integration of artificial intelligence to streamline information flow and reduce return rates. The study concludes that these initiatives can enhance competitiveness and customer satisfaction while minimizing operational costs.