Financial Literacy and Behavioral Intention to Use Central Banks’ Digital Currency: Moderating Role of Trust
Bibliographic record
Abstract
Building on the Innovation Diffusion Theory, this study proposes and explores the influence of financial literacy on the behavioral intention to use central banks’ digital currency (CBDC) and the moderating role of trust of respondents in the financial institution on the above relationship. This study has employed a quantitative research design to examine the relationship between financial literacy, behavioral intention to use CBDC and trust. The final sample comprised 241 respondents who had used CBDC across India. The statistical relationship between the above variables was assessed using PROCESS macro in SPSS 23.0. Findings revealed that financial literacy emerges as a strong predictor of CBDC use. Individuals with higher financial literacy are more likely to understand the features, benefits and risks associated with adopting CBDC. The interaction effect reveals that as financial literacy increases, the relative importance of trust diminishes. On the other hand, those who lack sufficient knowledge of financial literacy depend more on trust to fill in their knowledge gaps. This is one of the first studies to scientifically support the relationship between trust and financial literacy and how both influence behavioral intention to use CBDC. This research contributes valuable knowledge to the discourse on the use of CBDC, which is crucial for achieving a nation’s broader digital transformational goal.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".