Optimizing the logistics distribution network for rural e-commerce holds significant importance for promoting economic growth. This paper proposes an urban logistics distribution model to achieve an efficient, low-consumption rural logistics innovation service model. Subsequently, it combines regression analysis, factor analysis models, and k-means clustering to optimize the logistics distribution network for rural e-commerce. Taking County S as a case study, the results show that the average scores for villages and towns in “Cluster-1,” “Cluster-2,” and “Cluster-3” are 2.6, -0.24, and 0.27, respectively. Among these, Cluster-1—TC Town and LX Town—achieve the highest scores. Priority should be given to the layout of logistics network nodes in these areas to improve logistics organizational structures and drive the efficient development of rural logistics.
