电商个性化推荐对消费者购买决策的影响机制及策略分析

Analysis of the Influence Mechanism and Strategy of E-Commerce Personalized Recommendations on Consumers’ Purchase Decisions

摘要: 随着信息技术的不断迭代更新，互联网和电子商务快速发展，个性化推荐系统在这一过程中产生，并在庞大的用户信息与商品信息的基础之上深挖数据价值，为用户推荐符合其需求及偏好的商品，提供个性化的信息服务和决策支持。其重要性已经得到电商平台的广泛认可。用户愿意采纳符合需求及偏好的商品信息是用户做出购买决策的基础。本文旨在探讨个性化推荐系统对消费者购买决策的影响，通过回顾相关理论和模型，构建研究模型，并基于淘宝电商平台的个性化推荐设计调查问卷进行实证分析。实证结果显示，感知有用性、感知时效性、感知推荐质量、平台信任对采纳意愿产生影响，而采纳意愿和感知风险对购买决策产生影响。根据研究结果，本文提出了相应的建议。

Abstract: With the continuous iterative updating of information technology, the Internet and e-commerce are developing rapidly, and personalized recommendation system arises in this process. On the basis of huge user information and commodity information, it digs deep into the value of the data, recommends commodities that meet the needs and preferences of the users, and provides personalized information services and decision support. Its importance has been widely recognized by e-commerce platforms. Users’ willingness to adopt product information that meets their needs and preferences is the basis of their purchasing decisions. The purpose of this paper is to explore the impact of personalized recommendation system on consumers’ purchasing decisions by reviewing relevant theories and models, constructing a research model, and designing a survey questionnaire based on personalized recommendation on Taobao e-commerce platform for empirical analysis. The empirical results show that perceived usefulness, perceived timeliness, perceived recommendation quality, and platform trust have an impact on adoption willingness, while adoption willingness and perceived risk have an impact on purchase decision. Based on the research results, this paper puts forward the corresponding recommendations.