Cited by 632

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

Tam, Kar Yan, Ho, Shuk Ying·2005·Information Systems Research

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Abstract

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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Authors: Tam, K. Y., & Ho, S. Y.
Venue: Information Systems Research
Publisher: Institute for Operations Research and the Management Sciences (INFORMS)
Published: 2005-09
Volume: 16
Issue: 3
Pages: 271-291
ISSN: 1047-7047 (ISSN-L)
1526-5536
DOI: 10.1287/isre.1050.0058
OpenAlex: W2111865761
Cited by: 632
References: 3
FWCI: 27.08
Type: journal article
Language: en
Open access: closed

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

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