This article describes a unified approach to privacy decision research that
describes the cognitive processes involved in users’ “privacy calculus” in terms of system-related
perceptions and experiences that act as mediating factors to information disclosure. The approach is
applied in an online experiment with 493 participants using a mock-up of a context-aware recommender
system. Analyzing the results with a structural linear model, we demonstrate that personal privacy
concerns and disclosure justification messages affect the perception of and experience with a system,
which in turn drive information disclosure decisions. Overall, disclosure justification messages do not
increase disclosure. Although they are perceived to be valuable, they decrease users’ trust and satisfaction.
Another result is that manipulating the order of the requests increases the disclosure of items requested
early but decreases the disclosure of items requested later.
The statistical analysis of the experiment presented in this paper consists of two
parts. We first validate the measured latent concepts in a series of Confirmatory
Factor Analyses (CFAs), one for disclosure behavior and one for the subjective
measures. Subsequently, we test the structural relations between the manipulations
and the subjectively and behaviorally measured latent concepts using Structural
Equation Modeling (SEM). In this section, we provide a detailed explanation of these
statistical methods using the data from this paper as an example.