SUBJECTIVE NORM AND THE PRIVACY CALCULUS: EXPLANING SELF-DISCLOSURE ON SOCIAL NETWORKING SITES
The privacy calculus postulates that individuals disclose information when benefits outweigh privacy risks. Despite its wide applicability, research has also challenged the privacy calculus. It was shown that individuals disclose information even if benefits do not outweigh privacy risks. Two explanations have been provided: On the one hand, perceptions might lead to a miscalcu-lation of benefits and privacy risks. On the other hand, additional concepts might alter the effect of benefits and privacy risks on disclosure. In this research study we provide a third explana-tion: We suggest subjective norm to be a factor which overlies the effect of benefits and privacy risk. Subjective norm is the perceived social pressure of individuals that other important refer-ents around expect the individual to undertake a certain behavior. To integrate subjective norm into the privacy calculus, we use the theory of reasoned action as our theoretical lens. Based on a survey with 1,466 participants and a covariance-based structural equation modeling (SEM) analysis, we can conclude that subjective norm has the strongest effect on disclosure. The re-sults contribute to theory in the privacy domain, by questioning in how far the privacy calculus can be considered, without taking the environment into consideration.
Wirth, Jakob; Maier, Christian; and Laumer, Sven, (2019). "SUBJECTIVE NORM AND THE PRIVACY CALCULUS: EXPLANING SELF-DISCLOSURE ON SOCIAL NETWORKING SITES". In Proceedings of the 27th European Conference on Information Systems (ECIS), Stockholm & Uppsala, Sweden, June 8-14, 2019. ISBN 978-1-7336325-0-8 Research Papers.