Key success drivers for implementation blockchain technology in UAE Islamic banking
Bibliographic record
Abstract
The utilization of blockchain technology is increasingly emerging as a catalyst for significant changes across multiple industries, including the domain of Islamic finance. This study examines the influence of blockchain technology on the factors that contribute to the successful adoption of blockchain in Islamic banks located in the United Arab Emirates (UAE). The present study employs a cross-sectional survey methodology, encompassing a sample of 344 banking professionals. The investigation utilizes Partial Least Squares Structural Equation Modeling (PLS-SEM) as a statistical technique to examine the association between several crucial variables, namely Trust, Financial Transfers, Operating Expenses, Safety and Security, and the effective implementation of blockchain technology. The results indicate that these variables have a major impact on the effectiveness of implementing blockchain technology, confirming its ability to boost the efficiency of transactions, decrease expenses, and enhance security while adhering to Shariah law. This work makes a vital contribution to the scholarly discourse around the deployment of technology in the context of Islamic banking. In particular, it emphasizes blockchain technology's part in fostering innovation within the sector and fostering a culture of compliance with the sector's ethical and operational standards.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".