What drives consumer choice of Islamic banking services in the United Arab Emirates?
Bibliographic record
Abstract
Purpose Islamic banking (IB) has witnessed remarkable growth in the past decade. The purpose of this study is to explore some factors that are influencing the choice of Islamic banking and finance (IBF) products and services in the United Arab Emirates (UAE), a predominantly Muslim country. Design/methodology/approach Students enrolled at a university located in a major emirate in the UAE were asked to respond to a survey on factors underlying their decision to open an account at an Islamic bank. Responses were analyzed using descriptive statistics, analysis of variance and regression analysis. Findings Results indicate that the decision to open an account with an Islamic bank is influenced by consumer expectations regarding the conformity of the bank’s operations with Islamic principles, as well as consumers’ Arab language skills. Variables such as consumers’ nationality, gender, education and familiarity with IB do not have a significant influence on the decision to open an account at an Islamic bank. Research limitations/implications The study focuses on university students from a certain Emirate only, which somewhat limits the generalizability of the research results. Nevertheless, the findings of this study may potentially provide some practical insights for further improving and promoting IB, with special reference to the UAE youth market segment. Originality/value The research is original in nature, particularly as there have not been many instances where the choice of potential consumers (university students) regarding IB and finance services has been explored within the IB sector in a predominantly Muslim nation such as the UAE, an emerging Gulf economy. Consequently, the research findings have important implications for Islamic banks operating in a predominantly Islamic environment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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 source (direct Gemma or distilled Codex), 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".