The Mediating Role of Customer Satisfaction among SERVQ and Loyalty in the Banking Sector
Bibliographic record
Abstract
This study aims to measure the effectiveness of service quality in Islamic banks compared to conventional banks with the objective of improving the performance of those banks, taking into consideration the customer's point of view in this regard, and hoping to offer an effective contribution to creating an Islamic alternative to conventional banks. The researchers have adopted in their perception of this study on the KSA’s market as a sample for the analysis of the status of Islamic banks in terms of the services provided to customers. Thus, the research is based on investigation and we used a sample of 1050 clients from Saudi Bank sector. Therefore, the analysis of our sample used exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) presented a multitude of structural relations path that gave rise to different results. In case of CB, the results shown that exist a direct effect between customer satisfaction, empathy, assurance and tangibles. The loyalty has an indirect effect within empathy, assurance, tangibles and a direct effect within customer satisfaction variable. However, in case of IB, the results indicated that exist a direct effect between customer satisfaction, responsiveness and reliability. The loyalty has an indirect effect within responsiveness, reliability, and direct effect within customer satisfaction. The role of customer satisfaction as a mediator between service quality and loyalty is major in both cases. Findings revealed that each type of banks presented its specificity in service quality.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".