Author List: Tam, Kar Yan; Ho, Shuk Ying;
Information Systems Research, 2005, Volume 16, Issue 3, Page 271-291.
With advances in tracking and database technologies, firms are increasingly able to understand their customers and translate this understanding into products and services that appeal to them. Technologies such as collaborative filtering, data mining, and click-stream analysis enable firms to customize their offerings at the individual level. While there has been a lot of hype about web personalization recently, our understanding of its effectiveness is far from conclusive. Drawing on the elaboration likelihood model (ELM) literature, this research takes the view that the interaction between a firm and its customers is one of communicating a persuasive message to the customers driven by business objectives. In particular, we examine three major elements of a web personalization strategy: level of preference matching, recommendation set size, and sorting cue. These elements can be manipulated by a firm in implementing its personalization strategy. This research also investigates a personal disposition, need for cognition, which plays a role in assessing the effectiveness of web personalization. Research hypotheses are tested using 1,000 subjects in three field experiments based on a ring-tone download website. Our findings indicate the saliency of these variables in different stages of the persuasion process. Theoretical and practical implications of the findings are discussed.
Keywords: elaboration likelihood model; human computer interaction; persuasion; preference matching; recommendation set size; sorting cue; web personalization
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#13 0.379 personalization content personalized willingness web pay online likelihood information consumers cues customers consumer services elaboration preference experiment framing customized timing
#108 0.173 model research data results study using theoretical influence findings theory support implications test collected tested based empirical empirically context paper
#278 0.083 website users websites technostress stress time online wait delay aesthetics user model image elements longer waiting appeal attract utility internet
#168 0.076 firms firm financial services firm's size examine new based result level including results industry important account does suggests characterize limited
#212 0.071 business digital strategy value transformation economy technologies paper creation digitization strategies environment focus net-enabled services processes insights challenges key response