Transformative privacy calculus: Conceptualizing the personalization-privacy paradox on social media

Abstract

The rapid evolution of digital marketing underscores a critical tension between personalization and privacy, exacerbated by advances in data technologies and artificial intelligence. This study delves into the personalization-privacy paradox, emphasizing the dichotomy of consumer behavior—desiring customized interactions while guarding personal data. We explore how happiness with the internet (HWI) influences users' willingness to disclose personal information on social media, employing social exchange theory as our conceptual framework. Our research develops and tests a conceptual model that investigates the psychological mechanisms driving information-sharing behaviors on social media, including the moderating roles of trust beliefs and information collection concerns. By examining the mediating effect of posting frequency on the relationship between HWI and information disclosure for personalization, our findings contribute to understanding the complex interplay between happiness, trust and privacy concerns, coined as transformative privacy calculus. Our study enriches social exchange and privacy calculus theories, providing valuable implications for marketers aiming to navigate the balance between personalization and privacy, suggesting strategies to enhance user engagement without compromising privacy standards.