Analysis information quality to usage intention: a PLS-SEM study of perceived usefulness and perceived risk in digital service adoption

Abstract

This study examined how information quality and perceived risk shape intention to use digital services through perceived usefulness in a technology acceptance framework. The empirical model used 149 valid questionnaire responses containing twenty Likert-scale indicators representing information quality, perceived risk, perceived usefulness, and intention to use. Partial least squares structural equation modeling was applied through measurement purification, reliability assessment, discriminant validity testing, bootstrapping, effect-size analysis, and predictive relevance assessment. The results showed that information quality strongly improved perceived usefulness and directly increased intention to use, whereas perceived risk weakened intention to use and had a nonsignificant direct effect on perceived usefulness after measurement purification. Perceived usefulness significantly mediated the influence of information quality on intention to use and functioned as the strongest proximal determinant of usage intention. The findings confirm that digital service adoption is driven by useful, credible, and actionable information, while risk perception remains a behavioral barrier that must be managed through transparent service design