Published in

Oxford University Press, Journal of Computer-Mediated Communication, 6(23), p. 370-388, 2018

DOI: 10.1093/jcmc/zmy020

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

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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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.