“Guess You Like It” – How personalized recommendation timing and product type influence consumers’ acceptance: An ERP study

产品(数学) 分类 机制(生物学) 过程(计算) 偏爱 认知 推荐系统 计算机科学 感知 心理学 认知需要 知识管理 人工智能 万维网 哲学 几何学 数学 认识论 神经科学 经济 微观经济学 操作系统
作者
Qian Shang,Jialiang Chen,Huijian Fu,Cuicui Wang,Guanxiong Pei,Jia Jin
出处
期刊:Neuroscience Letters [Elsevier BV]
卷期号:807: 137261-137261 被引量:6
标识
DOI:10.1016/j.neulet.2023.137261
摘要

Personalized recommendation has been increasingly used in online shopping environment, and improving the effectiveness of personalized recommendation is an important issue. On the basis of two-stage decision theory and preference inconsistency theory, our study adopted the neuroscientific methodology of event-related potential to investigate the decision-making process and psychological mechanism of consumers for personalized recommendation under different recommendation timings (browsing and decision stages) and recommended product types (similar and related). Behavioral results showed that consumers' acceptance of similar product recommendations was higher than that of related product recommendations during the browsing stage, whereas no difference was observed in consumers' acceptance of the two product types during the decision stage. More importantly, neurophysiology results provided underlying psychological mechanism for exploring consumers' decision-making process for personalized recommendations. Consumers' psychological mechanism of the personalized recommendations might be divided into two processes, the early automatic cognitive process indicated by the N2 component, and the late advanced cognitive process indicated by the P3 component. We suggested that N2 reflects the perceptual mismatch between the recommended products and the target products, and P3 reflects the attention capture during categorization evaluation of the recommended product and the target product. These findings have important theoretical and practical significance for the deeper understanding of consumers' decision-making process and psychological mechanism in personalized recommendation, as well as improving the effectiveness of personalized recommendation.
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