The privacy calculus theory proposes that an individual’s intention to disclose personal information is based on a risk-benefit analysis. This article by Dienlin and Metzger suggests that, in the context of Social Networking Sites, or SNS (which shares much in common with sharing economy platforms), an extended model of the privacy calculus is required to predict self-disclosure on sites such as Facebook, Instagram or Snapchat.
The study uses a U.S. representative sample to test the privacy calculus’ generalizability and extend its theoretical framework by including both self-withdrawal behaviours (e.g. deleting of posts, limiting view-able audience) and privacy self-efficacy (e.g. self-protective behaviors such as adjusting privacy settings). Results from the study confirmed the extended privacy calculus model, with both privacy concerns and privacy self-efficacy positively predicting the use of self-withdrawal. With regard to predicting self-disclosure in SNSs, benefits outweighed privacy concerns. When it comes to self-withdrawal, privacy concerns outweighed both privacy self-efficacy and benefits.