感知风险理论视域下电商评论的风险缓冲机制与网络营销策略优化研究
Research on the Risk-Buffering Mechanism of E-Commerce Reviews and Optimization of Online Marketing Strategies from the Perspective of Perceived Risk Theory
摘要: 在数字经济背景下，消费者在线决策面临复杂的感知风险，而电商评论是化解该风险的关键信息机制。现有研究多聚焦于评论的总体有用性，未能深入解析其针对不同风险类型的作用差异。基于感知风险理论，通过理论演绎构建了一个“评论–风险”匹配分析框架。该框架将电商评论划分为认知主导型与情感/社会主导型两类，并将其分别与功能性风险(财务、功能风险)及心理社会性风险(社会、心理风险)建立了对应缓冲关系。分析表明，评论的风险缓冲效能取决于其内容特质与消费者主导性感知风险之间的匹配度：认知型评论通过提供事实信息降低功能性风险，情感社会型评论则通过构建认同缓解心理社会性风险。这一匹配逻辑为平台优化评论生态治理、商家实施精准化营销沟通以及消费者提升信息利用效率提供了系统的理论依据与实践指引，推动了电商评论研究从“有用性”评估向“针对性”设计的范式深化。
Abstract: In the context of the digital economy, consumers face complex perceived risks during online decision-making, with e-commerce reviews serving as a critical information mechanism to mitigate such risks. Existing research predominantly focuses on the overall helpfulness of reviews, lacking a nuanced analysis of their differential effects on various risk types. Grounded in perceived risk theory, a “review-risk” matching analytical framework is constructed through theoretical deduction. This framework categorizes e-commerce reviews into cognitively dominant and emotionally/socially dominant types, linking them respectively to functional risks (financial, performance risks) and psycho-social risks (social, psychological risks). The analysis demonstrates that the risk-buffering effectiveness of reviews depends on the match between their content characteristics and consumers’ dominant perceived risks: cognitive reviews reduce functional risks by providing factual information, while emotional-social reviews alleviate psycho-social risks by building identification and resonance. This matching logic provides a systematic theoretical foundation and practical guidance for platforms to optimize review ecosystem governance, for merchants to implement precise marketing communication, and for consumers to enhance information utilization efficiency, thereby advancing the study of e-commerce reviews from a paradigm of “helpfulness” evaluation to one of “targeted” design.
文章引用：周歆禹. 感知风险理论视域下电商评论的风险缓冲机制与网络营销策略优化研究[J]. 电子商务评论, 2026, 15(2): 280-289. https://doi.org/10.12677/ecl.2026.152156

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