【摘要】 针对电子商务背景下网购商品运输和配送中的瓶颈问题,在分析和调研电商的快递配送流程的基础上,利用仿真方法得到大量的电商销售和快递运输配送数据,借助数据挖掘的方法对该数据进行分析,提出物流瓶颈优化策略并验证其有效性。研究结果表明:来自上海和广东的销售量较大的网上店铺的商品运输中更容易发生延误,且滞留商品多为食品和服饰。这说明在网购商品的物流配送过程中,运输条件、消费者偏好、商品发货地、商品类别、店铺成交量和信誉度等因素都是导致物流瓶颈产生的原因。对此,本文提出电商快递配送优化策略并证明其能够有效减少快递在运输途中的延误,尤其是在节假日期间。更多还原

【Abstract】 Some measures were taken to solve the transportation bottleneck problem of online shopping under the background of e-commerce in this paper. Based on the investigation and analysis of e-commerce logistics distribution process, first of all, a simulation model was set up to obtain a large number of e-commerce sales and logistics transportation data. Then, the method of data mining was used in big data analysis. Finally, the logistics bottleneck optimization strategy was proposed and its effectiveness was verified. The results show that goods belonging to food and clothing from Shanghai and Guangdong or from stores with large sales volume are more likely to be delayed in the transportation. This indicates that transportation conditions, consumer preferences, commodity delivery place, commodity category, sales volume and reputation of store are the causes of logistics bottlenecks. In this regard, this paper puts forward the optimization strategy of e-commerce logistics distribution and proves its effectiveness, especially during holidays.更多还原