This study explores the unique aspects of gaming privacy by proposing a dual-factor model of privacy concerns: breadth (BPC) and depth (DPC). It aims to examine how privacy concerns in gaming differ from those in other online contexts and to provide explanatory insights into the factors associated with users' privacy perceptions and behaviors in entertainment-driven environments. Flow, defined as a state of deep immersion and engagement, is introduced as a moderating factor, shaping the relationships between privacy concerns and disclosure intentions within gaming contexts.
Two empirical studies were conducted. Study 1, a 2×2 online experiment (N = 240), compared privacy concerns between utility-driven instant messaging applications and entertainment-driven games. Study 2 employed the Antecedent-Privacy Concern-Outcome model to validate the relationships among privacy concerns, perceived vulnerability, and information disclosure intentions (N = 766), with flow as a moderating factor.
Study 1 revealed that users generally exhibited lower privacy concerns in gaming contexts, though privacy cues can increase their DPC. Study 2 showed that gaming contexts encourage users to trade privacy for entertainment, with flow experiences amplifying this effect.
Theoretically, this study introduces a dual-factor privacy concerns framework, contributing to the understanding of gaming privacy and its formation. The study also provides a novel explanation for the privacy paradox by incorporating flow. Practically, it advises game developers to enhance privacy cues and transparency and recommends policymakers stabilize gaming privacy regulations to avoid confusion from frequent changes.
The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-07-2025-0510
