Even though many Internet users express concerns about their online privacy, they rarely take the necessary measures to protect it. To understand the reasons for the observed discrepancy, previous research has identified several factors that determine users’ online privacy protection. Nevertheless, to date, there has been no attempt to empirically test a model that integrates key personality, cognitive, and motivational factors into a comprehensive explanation of protection behaviour formation. This master’s thesis sought to address this gap by drawing on the protection motivation theory and integrating previous findings into a conceptual model of internet users’ privacy management. The model was tested on a probability sample of adult internet users (N = 574) using structural equation modelling. Following theoretical assumptions, we expected that basic personality traits determine online privacy protection by directly inducing privacy concerns and privacy self-efficacy, which in turn, by promoting or inhibiting the development of privacy protection intentions and privacy cynicism, lead to actual privacy-protective behaviour or the absence thereof. The empirical results partially support the proposed model. Personality indeed emerged as an important factor in online privacy protection, but its effect was not limited to the initial phase of the protection behaviour formation process. All the Big Five personality traits, apart from extraversion, played a significant role, but at different stages of the process, with privacy concerns, self-efficacy, and intention to protect – but not privacy cynicism – serving as mediators of the effects of respective personality traits on privacy protection. The results of this master’s thesis deepen our understanding of the complex psychological mechanisms that foster or inhibit privacy protection among Internet users and shed light on the role of personality throughout the process of protection behaviour formation. The findings also enable the identification of user characteristics that make individuals most vulnerable to maladaptive responses to privacy threats on the Internet, providing a roadmap for developing more effective evidence-based privacy protection interventions.
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