Privacy Relevance and Disclosure Intention in Mobile Apps: The Mediating and Moderating Roles of Privacy Calculus and Temporal Distance.

In digital societies, users' privacy decisions not only affect personal information security and application sustainability, but also profoundly influence the formulation and enforcement of relevant laws. However, existing research mainly adopts a dichotomous perspective of rationality and bounded rationality, lacking an integrated framework to explain the complexity of users' privacy decisions. Therefore, this study integrates privacy calculus theory and Psychological Distance Theory within the Elaboration Likelihood Model (ELM) framework to explore their mediating and moderating roles in the relationship between perceived privacy relevance and disclosure intention. To achieve the research objectives, we employed the vignette method to design an online survey with a 2 (perceived relevance: low vs. high) × 2 (temporal distance: near vs. distant) between-subjects design, ultimately collecting 293 valid responses. The conclusions are as follows: (1) perceived relevance positively affects users' privacy disclosure intention, and perceived benefits and perceived risks play a partial mediating role between them; (2) contrary to individuals' common preference for near temporal distance (immediate rewards), distant temporal distance (delayed rewards) have a more pronounced enhancing effect on the positive relationship between perceived relevance and perceived benefits; (3) the results excluded the influence of control variables such as gender, age, and education level on privacy disclosure intention. This study not only proposes an integrated analytical framework, revealing that users' privacy decisions are jointly influenced by both rational and irrational factors, but also provides practical insights for application developers and regulatory agencies. Finally, we also discuss the limitations of this study and directions for future research.