Young adults’ acceptance of data-driven personalized advertising: Privacy and Trust Equilibrium (PATE) model

Purpose: This study aims to examine young social media users’ differential acceptance of data-driven ad personalization depending on the types of personal data used, and to propose and test the Privacy and Trust Equilibrium (PATE) model, a new conceptual model developed to explain the intertwined nature of the competing influences of platform-related factors (privacy concern, trust, and privacy fatigue) on acceptance of ad personalization. Design/methodology/approach: A survey of 440 Instagram users aged 18–24 in Australia was conducted to examine the relationships between the three factors of the PATE model and acceptance of ad personalization utilizing overt vs covert data collection methods. Findings: This study shows the highest level of acceptance for personalization using overtly collected data and the lowest for covert data. The results also support the PATE model, revealing the competing dynamics of how the platform-related factors shape consumers’ acceptance of data-driven ad personalization. Privacy concern discourages Instagram users from accepting personalized ads, while trust encourages them. When the pushing influence of privacy concern and the pulling influence of trust form equilibrium, generating cognitive dissonance, privacy fatigue seems to play a significant role in resolving the dissonance, leading to increased acceptance. Originality/value: This study advances the understanding of how concurrent push–pull-resigning factors affect young consumers’ acceptance of data-driven ad personalization practices, expanding the scope of research on data-driven personalized advertising and privacy.