Understanding the Effects of Personalization as a Privacy Calculus: Analyzing Self-Disclosure Across Health, News, and Commerce Contexts

Abstract

Abstract The privacy calculus suggests that online self-disclosure is based on a cost–benefit trade-off. However, although companies progressively collect information to offer tailored services, the effect of both personalization and context-dependency on self-disclosure has remained understudied. Building on the privacy calculus, we hypothesized that benefits, privacy costs, and trust would predict online self-disclosure. Moreover, we analyzed the impact of personalization, investigating whether effects would differ for health, news, and commercial websites. Results from an online experiment using a representative Dutch sample (N = 1,131) supported the privacy calculus, revealing that it was stable across contexts. Personalization decreased trust slightly and benefits marginally. Interestingly, these effects were context-dependent: While personalization affected outcomes in news and commerce contexts, no effects emerged in the health context.