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

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. B...

Full description

Saved in:
Bibliographic Details
Published in:Journal of computer-mediated communication 2018-11, Vol.23 (6), p.370-388
Main Authors: Bol, Nadine, Dienlin, Tobias, Kruikemeier, Sanne, Sax, Marijn, Boerman, Sophie C, Strycharz, Joanna, Helberger, Natali, de Vreese, Claes H
Format: Article
Language:English
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary: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.
ISSN:1083-6101
1083-6101
DOI:10.1093/jcmc/zmy020