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

By Kar Yan Tam, S. Y. Ho. Information systems research, 2005

676 citations recorded by the source corpus.

Subfields: Information Systems and Management, Marketing, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/54566b1c97968ac5f5280632afcb14c1b5fdb6e5

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Citations in the corpus

The elaboration likelihood model: review, critique and research agenda (2014, background): “Recent studies have emphasized an online component whose inputs seem to affect persuasion (Hershberger, 2003; Karson and Korgaonkar, 2001; Liu and Shrum, 2009; SanJosé-Cabezudo et al., 2009; Sinclaire et al., 2010; Tam and Ho, 2005; Yang et al., 2006).”
Persuasion in crowdfunding: An elaboration likelihood model of crowdfunding performance (2017, background): “Through this application, a body of evidence suggests that organizations can use internet-based communications as an effective means for changing the attitudes of both potential customers (Petty and Wegener, 1999) and other various stakeholders (Tam and Ho, 2005).”
What motivates customers to participate in social commerce? The impact of technological environments and virtual customer experiences (2014, background): “Therefore, personalization perception represents the fit between website content and one’s preferences [56].”
Social Media Brand Community and Consumer Behavior: Quantifying the Relative Impact of User- and Marketer-Generated Content (2013, background): “Consumers are inundated with irrelevant information in online environments nowadays (Tam and Ho 2005).”
Empirical Analysis of the Impact of Recommender Systems on Sales (2010, background): “Sellers can analyze historical data and recommend products to induce them to take certain actions, such as visiting a product Web page or purchasing a product or service in accordance with their business objectives [45].”
Adoption of Electronic Health Records in the Presence of Privacy Concerns: The Elaboration Likelihood Model and Individual Persuasion (2009, background): “Persuasive messages focus the attention of the subject, leading to a reallocation of cognitive resources and eliciting responses (such as an attitude change) or a behavior (Tam and Ho 2005).”
Explaining the user experience of recommender systems (2012, background): “Tam and Ho (2005) find that making one recommendation stand out increases user attraction, elaboration, and choice likelihood of that recommendation.”
Creating Social Contagion through Viral Product Design: A Randomized Trial of Peer Influence in Networks (2011, neutral): “In addition, the personalization of messages tends to make them much more effective, especially in online environments in which we are constantly bombarded with irrelevant information (Tam and Ho 2005; Dijkstra 2008).”
Is this for me? How Consumers Respond to Personalized Advertising on Social Network Sites (2015, background): “Therefore, the effects of personalization and of the attitude toward the Facebook context may be different for high- and low-involvement products (Tam and Ho 2005).”
Evaluating recommender systems from the user’s perspective: survey of the state of the art (2012, background): “aspect of a recommender system, because it has been found that preference matching positively influences users’ elaboration on and the acceptance of the recommendation (Tam and Ho 2005).”