대중 교통에서의 안면인식 기반 결제 시스템 수용성 분석: 확장된 기술수용모형 적용 = User Acceptance of Facial Recognition-Based Contactless Payment in Public Transportation: An Extended TAM Perspective

다국어 초록 (Multilingual Abstract)

The adoption of facial recognition–based contactless payment systems in public transportation has been expanding; however, public acceptance remains uncertain. This study surveyed metropolitan transit users in South Korea and empirically tested an extended Technology Acceptance Model (TAM) by integrating Perceived Privacy Risk (PPR) and Trust in Technology (TT) into the original constructs of Perceived Ease of Use (PEOU), Perceived Usefulness (PU), and Intention to Use (IU). Structural Equation Modeling (SEM) was employed for analysis. The results reveal that PEOU significantly enhances PU, and both PEOU and PU directly strengthen IU. PPR negatively influences IU not only directly but also indirectly by reducing trust in technology. Conversely, TT emerged as the strongest positive predictor of IU and partially mitigated the negative effect of PPR through a mediating pathway.
These findings highlight that successful adoption of biometric-based payment services in the public transportation sector requires more than technical efficiency; institutional trust and robust privacy protection mechanisms are essential. The study provides theoretical and practical implications for designing citizen-centered smart transportation services and establishing policy frameworks that ensure trust and privacy.