The effect of personalization provider characteristics on privacy attitudes and behaviors: An Elaboration Likelihood Model approach

Many computer users today value personalization but perceive it in conflict with their desire for privacy. They therefore tend not to disclose data that would be useful for personalization. We investigate how characteristics of the personalization provider influence users' attitudes towards personalization and their resulting disclosure behavior. We propose an integrative model that links these characteristics via privacy attitudes to actual disclosure behavior. Using the Elaboration Likelihood Model, we discuss in what way the influence of the manipulated provider characteristics is different for users engaging in different levels of elaboration represented by the user characteristics of privacy concerns and self-efficacy. We find particularly that a reputation management is effective when users predominantly use the peripheral route i.e., a low level of elaboration, but much less so when they predominantly use the central route i.e., a high level of elaboration; b client-side personalization has a positive impact when users use either route; and c personalization in the cloud does not work well in either route. Managers and designers can use our results to instill more favorable privacy attitudes and increase disclosure, using different techniques that depend on each user's levels of privacy concerns and privacy self-efficacy.