摘要
电子商务平台积累的海量数据为深入解析消费者行为模式提供了新的研究视角。文章基于大数据分析方法,系统分析消费者在商品浏览、信息搜索、比价、筛选、购买决策等环节行为轨迹,揭示目标导向型、价值比较型、社交互动型、体验探索型等典型行为模式的特征。通过构建消费者行为模式形成机制模型,阐明信息处理基础、决策机制等影响要素在行为模式形成过程里中作用机理。研究发现,电商消费者行为模式具有显著的稳定性特征、场景适应规律与群体分布特点,这些规律性认识为深入理解电商环境下的消费者行为提供重要依据。
The massive data accumulated by e-commerce platforms offers new research perspectives for a deeper understanding of consumer behavior patterns.This paper employs big data analysis methods to systematically analyze consumer behavior trajectories through product browsing,information searching,price comparison,fi ltering,and purchase decision-making stages,revealing typical behavioral patterns such as goal orientation,value comparison,social interaction,and experiential exploration.By constructing a model for the mechanisms of consumer behavior pattern formation,the paper clarifi es the roles of information processing foundations,decision-making mechanisms,and other infl uencing factors during the formation process.The research indicates that e-commerce consumer behavior patterns exhibit significant stability traits,scenario adaptation laws,and group distribution characteristics,providing important foundations for a more profound understanding of consumer behavior within the e-commerce environment.
作者
岳彬
Yue Bin(Hangzhou Hot Spot List Culture and Media Co.,Ltd.Hangzhou,Zhejiang 310056)
出处
《中国商论》
2025年第14期82-85,共4页
China Journal of Commerce
关键词
大数据分析
电商平台
消费者行为
电子商务
模式识别
行为规律
big data analysis
e-commerce platform
consumer behavior
e-commerce
pattern recognition
behavior rule
