摘要
基于主成分分析(PCA)与K均值聚类(K-means),分析抖音商城消费者的行为模式与偏好.结果表明,线上购物活跃度与地区经济发展水平密切相关,且在日内不同时间段呈现显著差异与稳定规律;同时,支付工具的选择具有明显的群聚效.据此,可采用区域差异化与时段精准运营、供应链前置化,以及平台侧智能支付推荐与弹性算力扩容等一体化策略,以提升转化效率与服务水平.
Based on principal component analysis(PCA)and the K-means clustering algorithm,this study conducts an in-depth analysis of consumer behavior patterns and preferences on the Douyin Mall platform.The research reveals that consumers’online shopping activity is closely related to the economic development level of their region,and that significant differences and patterns exist in their shopping behavior across different time periods of the day.Additionally,there is a clear clustering effect in the choice of payment methods among consumers.Accordingly,integrated strategies such as regional differentiation and time-specific precise operations,supply chain front-end optimization,as well as platform-side intelligent payment recommendations and elastic computing capacity expansion can be adopted to enhance conversion efficiency and service levels.
作者
蔡钰麟
CAI Yu-lin(College of Mathematics and Statistics,Hanshan Normal University,Chaozhou,Guangdong,521041)
出处
《韩山师范学院学报》
2025年第6期26-36,共11页
Journal of Hanshan Normal University
基金
2025年度韩山师范学院教学改革项目(项目编号:E25143).
