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Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective

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 customi...

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Published in:Information systems research 2005-09, Vol.16 (3), p.271-291
Main Authors: Tam, Kar Yan, Ho, Shuk Ying
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Language:English
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description 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.
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subjects Behavior
Building customization
Collaboration
Communication
Customer information files
Customer services
Customers
Customization
Data mining
Decision making
Elaboration likelihood model
Empowerment
human computer interaction
Hypotheses
Information processing
Information storage and retrieval systems
Information technology
Internet
Need for cognition
Persuasion
preference matching
recommendation set size
Recommendations
Ring tones
Saliency
sorting cue
Studies
web personalization
Websites
World Wide Web
title Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective
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