Information Disclosure on Digital Platform Services:The Roles of Multidimensional Trust and Perceived Benefits of Recommendation Algorithms

This study examines how trust in personal information management capabilities can be associated with the intention to disclose personal information, with the perceived benefit of YouTube algorithm as a mediating factor. Using survey data from 4,437 Korean users, we employed factor analysis and mediation analysis. The results revealed that trust in established entities and in emerging platforms positively predicted the intention to disclose personal information. However, an unexpected algorithm literacy paradox emerged: while trust promoted perceived benefit of YouTube algorithm paradoxically decreased intention to disclose personal information. These findings challenge assumptions about the benefits of algorithmic transparency and extend privacy calculus theory by demonstrating that algorithm awareness can inhibit personal information disclosure. Increased algorithmic understanding may enhance privacy consciousness, leading to more cautious information disclosures. This research contributes to digital privacy literature and provides insights into platform design and transparency policy development.