Factors affecting middle eastern countries' intention to use financial technology
Bibliographic record
Abstract
Financial technology, also known as Fintech, continues to transform the financial services sector globally. Fintech adoption has been delayed in some places, particularly in the Middle East, despite the potential positive benefits. This study investigates the mediating effect of perceived ease of use on the relationship between seamless transactions, financial risk, legal risk, security risk, perceived risk, and the intention to use financial technology in Middle Eastern countries. Data was collected from 500 respondents from five Middle Eastern countries (Jordan, Kuwait, Saudi Arabia, Qatar, and the United Arab Emirates) using a structured questionnaire, and partial least squares structural equation modelling (PLS-SEM) was used to test the research model. The findings demonstrate that perceived ease of use strongly mediates the links between seamless transactions, financial risk, legal risk, security risk, perceived risk, and the intention to use financial technology. The study shed light on the significance of perceived ease of use in influencing people's intention to utilize financial technology as well as the function it serves in minimizing the effects of perceived risks. The findings of this study could be useful for financial technology companies operating in Middle Eastern countries, policymakers, and researchers interested in the adoption of financial technology.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.006 |
| Open science | 0.001 | 0.001 |
| 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".