Islamic Banking: Analytical Field Study for Customer’s Satisfaction and Direction
Bibliographic record
Abstract
This study gives guidelines to Jordanian Islamic bank's administrations regarding their costumers’ tendencies when it comes to the quality of service provided to them from their own point of view, so these banks may be able to rate themselves and recognize their competitive ranking and do all possible procedures in order to avoid any shortcomings and fix them by enhancing the quality of service provided. Thus, not only that these banks keep their current costumers, but also they are able to attract new ones which will have a positive effect on the overall achievement of Jordanian Islamic banks. Many Jordanians do not prefer to deal with commercial non-Islamic banks for religious reasons. This is the main result why Islamic banks have a huge share in market and consequently gain huge profits. Islamic banks that work in the Jordanian community must follow certain procedures in order to enhance the quality of their services to be strong competitors with other commercial banks. They also must work hard to improve these services as well as create new ones, so that they meet the costumers’ expectations by understanding their views for the Islamic banks services. The methodology employed a sample of 329 respondents took part in this study. 77% of them were received. The statistical methods used in this research are the percentages and repetitive, the arithmetic means, the correlation variation and the multiple regression analysis. The problem of this study arises from the fact the banking services forwarded in general to the customers who were dissatisfied in order to develop its market share and maximize the profit. The objectives of the research are to identify the Islamic banks customers’ trends, testing the quality of banking services and establishing a base of information for Islamic banks to help them in reforming the weaknesses of their performance. The major findings revealed a positive correlation between the variables tangible, reliability and responsiveness, from one side and negative with respect to empathy and assurance on the other side.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".