2005) Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective. Information Systems Research 16(3):271-291. http://dx.W ith 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.

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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There has been a notable increase in consumer use of mobile applications. Consumers begin to adopt mobile commerce applications. In response, firms have been investing billions of dollars in order to enhance the hardware and software platforms for mobile commerce. Consequently, with such large investments, firms are highly motivated to attract new clients and retain their old customers. In the present study, the strategic parameters have been studied in order to determine the ways in which mobile service providers acquire new customers. For the purpose of analysis, the dependent variable is the service subscribers' intention to switch to a new service provider with personalized services. Four main constructs have been studied - the amount and the perceived usefulness of general advertisements, the perceived usefulness and privacy issues about personalized advertisements. This empirical study indicates that all four constructs are significant in affecting the decision by subscribers to change to a new mobile service provider.