The Effects of Web Personalization on User Attitude and Behavior: An Integration of the Elaboration Likelihood Model and Consumer Search Theory1

精化可能性模型 个性化 精化 实现(概率) 收入 选择(遗传算法) 心理学 计算机科学 消费者行为 业务 营销 万维网 社会心理学 说服 数学 人工智能 统计 哲学 会计 人文学科
作者
Shuk Ying Ho,David Bodoff
出处
期刊:Management Information Systems Quarterly [MIS Quarterly]
卷期号:38 (2): 497-520 被引量:264
标识
DOI:10.25300/misq/2014/38.2.08
摘要

Web personalization can achieve two business goals: increased advertising revenue and increased sales revenue. The realization of the two goals is related to two kinds of user behavior: item sampling and item selection. Prior research does not provide a model of attitude formation toward a personalization agent nor of how attitudes relate to these two behaviors. This limits our understanding of how web personalization can be managed to increase advertising revenues and/or sales revenues. To fill this gap, the current research develops and tests a theoretical model of user attitudes and behaviors toward a personalization agent. The model is based on an integration of two theories: the elaboration likelihood model (ELM) and consumer search theory (CST). In the integrated model, a user’s attitude toward a personalization agent is influenced by both the number of items he/she has sampled so far (from CST) and the degree to which he/she cognitively processes each one (from ELM). In turn, attitude is modeled to influence both behaviors—that is, item selection and any further item sampling. We conducted a lab study and a field study to test six hypotheses. This research extends the theory on web personalization by providing a more complete picture of how sampling and processing of personalized recommendations influence a user’s attitude and behavior toward the personalization agent. For online merchants, this research highlights the trade-off between item sampling and item selection and provides practical guidance on how to steer users toward the attitudes and behaviors that will realize their business goals.
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