淘宝个性化推荐页面设计对消费者购买决策的影响研究

Research on the Impact of Personalized Recommendation Page Design on Consumers’ Purchase Decisions in Taobao

摘要: 随着大数据与人工智能技术的深度融合，个性化推荐系统已成为电子商务平台的核心竞争力。淘宝作为中国电商领域的巨头，其个性化推荐页面设计深刻影响着亿万消费者的购物旅程与决策过程。以淘宝为主要研究对象，综合运用信息系统、消费者行为学及伦理学等多学科理论，能够系统剖析其个性化推荐页面的设计要素对消费者购买决策的多维度影响。研究表明，精妙的页面设计通过降低信息过载、提升感知易用性与有用性，能有效激发消费者的探索欲望，缩短决策时间，从而正向促进购买意愿与行为。然而，算法驱动的推荐亦存在显著的双刃剑效应：过度个性化可能导致“信息茧房”与“过滤气泡”，削弱消费者自主性；不透明的算法机制易引发“大数据杀熟”等伦理担忧，损害用户信任。因此在论证其积极影响的同时，也深刻反思了其潜在风险，并最终从平台优化、算法治理与消费者教育等角度，提出引导个性化推荐系统健康发展的策略建议，以期为构建更具正向价值共创效应的电商生态环境提供理论参考与实践指引。

Abstract: With the deep integration of big data and artificial intelligence technologies, personalized recommendation systems have become the core competitiveness of e-commerce platforms. As a giant in the Chinese e-commerce field, Taobao’s personalized recommendation page design profoundly influences the shopping journey and decision-making process of hundreds of millions of consumers. Taking Taobao as the main research object and comprehensively applying theories from information systems, consumer behavior, and ethics, a systematic analysis can be conducted on the multi-dimensional impact of the design elements of its personalized recommendation pages on consumer purchase decisions. Research shows that a well-designed page can effectively reduce information overload, enhance perceived ease of use and usefulness, stimulate consumers’ exploration desires, shorten decision-making time, and thereby positively promote purchase intentions and behaviors. However, algorithm-driven recommendations also have a significant double-edged sword effect: excessive personalization may lead to “information cocoons” and “filter bubbles”, weakening consumer autonomy; opaque algorithm mechanisms can easily trigger ethical concerns such as “big data price discrimination”, damaging user trust. Therefore, while demonstrating its positive impacts, the potential risks are also deeply reflected upon, and ultimately, strategies for guiding the healthy development of personalized recommendation systems are proposed from the perspectives of platform optimization, algorithm governance, and consumer education, in order to provide theoretical references and practical guidance for building a more positively value-creating e-commerce ecosystem.