摘要
随着电子商务的迅猛发展，消费者行为模式日益复杂化和多样化，基于大数据技术对消费者行为进行深入分析已成为学术界与产业界共同关注的热点问题。本研究旨在通过整合多源数据，运用大数据分析方法，揭示电子商务环境中消费者行为的关键特征及其影响因素。研究采用数据挖掘、机器学习及统计建模等技术手段，对海量交易记录、用户评价、浏览轨迹等数据进行系统性分析，构建了涵盖购买偏好、决策路径和忠诚度预测的综合分析框架。结果表明，消费者行为呈现出显著的情境依赖性和动态演化特性，且社交互动、个性化推荐等因素对其决策过程具有重要影响。此外，本研究创新性地提出了一种基于时间序列的消费者行为预测模型，能够有效提升对消费者未来行为的预测精度。该模型在实际应用中表现出良好的稳定性和适应性，为电商平台优化营销策略、提升用户体验提供了重要参考。总体而言，本研究不仅深化了对电子商务消费者行为的理解，还为相关领域的理论发展与实践应用做出了积极贡献。
关键词：电子商务；消费者行为；大数据分析；预测模型；社交互动
Abstract
With the rapid development of e-commerce, consumer behavior patterns have become increasingly complex and diversified. Conducting in-depth analyses of consumer behavior based on big data technology has emerged as a focal issue of common concern in both academia and industry. This study aims to reveal the key characteristics and influencing factors of consumer behavior in e-commerce environments by integrating multi-source data and employing big data analytical methods. By utilizing techniques such as data mining, machine learning, and statistical modeling, a comprehensive analytical fr amework was constructed to systematically analyze massive datasets, including transaction records, user reviews, and browsing trajectories, covering aspects such as purchasing preferences, decision-making paths, and loyalty prediction. The findings indicate that consumer behavior exhibits significant context-dependency and dynamic evolution characteristics, with social interactions and personalized recommendations playing crucial roles in the decision-making process. Additionally, this study innovatively proposes a time-series-based consumer behavior prediction model, which effectively enhances the accuracy of predicting future consumer behavior. Demonstrating excellent stability and adaptability in practical applications, the model provides valuable references for e-commerce platforms to optimize marketing strategies and improve user experiences. Overall, this research not only deepens the understanding of consumer behavior in e-commerce but also makes positive contributions to the theoretical development and practical application of related fields.
Keywords：E-commerce; Consumer Behavior; Big Data Analysis; Prediction Model; Social Interaction
目 录
摘要 I
Abstract II
一、绪论 1
(一) 研究背景与意义 1
(二) 国内外研究现状分析 1
(三) 研究方法与技术路线 2
二、大数据在电子商务中的应用基础 2
(一) 大数据技术概述 2
(二) 电子商务中的大数据来源 3
(三) 消费者行为数据的采集与处理 3
三、消费者行为特征的大数据分析 4
(一) 消费者购买行为模式识别 4
(二) 消费者偏好分析方法 5
(三) 行为预测模型构建 5
四、基于大数据的消费者行为优化策略 6
(一) 个性化推荐系统设计 6
(二) 营销策略的数据驱动优化 6
(三) 提升用户体验的具体措施 7
结 论 9
参考文献 10
