Supervisors: Marco Hubert & Sascha Steinmann
Discussants: Alice Grønhøj & Jonas Valbjørn

Abstract
Personal data collection and continuous exposure to advertisements is an integral part of free internet. Advances in machine learning and artificial intelligence enable social media platforms to gather extensive data on individual users, leading to highly personalized advertising experiences. While such personalization offers many benefits, the underlying dataveillance behind such practices raises significant concerns in privacy and invasiveness, creating a personalization paradox. To ensure the positive effects of personalized advertisements, it is crucial to understand how companies can balance the benefits and risks created by the practices. Accordingly, this study investigates how the type of data used for personalization impacts consumer perceptions of both the benefits (Informativeness, relevance, and entertainment value) and the risks (vulnerability, invasiveness, and privacy concerns) of personalized advertising, as well as its effects on behavioral intentions. Furthermore, it examines the moderating role of privacy literacy, suggesting that the extent to which individuals understand personalization mechanisms can impact their perceptions and responses to personalized advertising.

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