User Trust, Security, and Data Privacy Awareness in GoPay Usage Using Protection Motivation Theory (PMT) - Diva Ayu Gitareswara; Tri Suratno; Dewi Lestari (International Journal Software Engineering and Computer Science (IJSECS), 2025)
The widespread adoption of GoPay in Indonesia has raised significant questions about user data privacy and security, dimensions frequently overlooked by traditional utility-focused adoption models such as TAM and UTAUT. This research addresses that gap by applying Protection Motivation Theory (PMT) to examine the psychological drivers behind GoPay usage intention. Through a quantitative national survey of 105 active users analyzed via PLS-SEM, the model explained 69.3% of variance in behavioral intention (R²=0.693). Results show that privacy concern, perceived severity, perceived vulnerability, response cost, response efficacy, and trust significantly and positively influence usage intention. In contrast, security features and user self-efficacy were not significant drivers. The findings demonstrate that users' behavioral intentions are more strongly influenced by their evaluation of potential threats and confidence in the service provider's protective capabilities rather than technical security features or personal competence alone. The study advances understanding of digital payment adoption by revealing that psychological threat assessment processes, rather than technical security perceptions, primarily drive user decisions. GoPay users prioritize the platform's ability to protect them over their own technical skills or general security features. These findings offer practical implications for digital wallet providers seeking to enhance user adoption through targeted trust-building strategies rather than solely focusing on technical security improvements.