Indonesia’s swift digital finance evolution presents a striking contradiction: while 83% adopt digital payments, financial literacy reaches merely 65.43%, contributing to over 10,000 annual fraud incidents. Current Digital Financial Literacy (DFL) models lack unified definitions, exhibit circular measurement approaches, and remain untested in developing economies. This research fills these voids by constructing and testing a comprehensive DFL framework specifically designed for Indonesia. Conceptualizing DFL as a second-order reflective model to eliminate measurement overlap, we examined four components – Attitudes, Behavior, Knowledge, Skills – through PLS-SEM analysis of 510 participants, achieving robust psychometric indicators (CR > 0.85, AVE > 0.60) and accounting for 61.9% literacy variation. Extensive validation procedures confirmed framework dependability. Within this sample, Attitudes showed the strongest association with overall DFL (β = 0.441, p < 0.001), with comparatively weaker associations observed for Behavior, Skills, and Knowledge. Given the cross-sectional design, these patterns are interpreted as associational rather than as evidence of a universal causal hierarchy among DFL dimensions. Socioeconomic status was associated with moderation of the knowledge–literacy link, exhibiting a pattern consistent with a U-shaped form. Regulatory environment showed a consistent direct association with literacy. Findings recommend emphasizing confidence-building experiential initiatives, regulatory enhancement, and socioeconomically customized strategies for developing nations.
Putri et al. (Fri,) studied this question.