Muslim customer perceived value on customer satisfaction and loyalty: Religiosity as a moderation
Bibliographic record
Abstract
This study aims to determine the effect of Muslim customer perceived value on customer satisfaction and customer loyalty of sharia banking and religiosity role in moderating the existing effect. The study population includes all customers of Sharia banking. Total samples of 104 respondents are selected by accidental sampling technique. To know and to test the research hypothesis, data are analyzed by partial least square (PLS). This study has four results. First, the Muslim customer perceived value (MCPV) variable directly affects customer satisfaction. It consists of price, emotional values, and social values variables. While the quality, Islamic physical attributes, and Islamic non-physical attributes variables directly do not affect satisfaction of Islamic banking customers. Second, Muslim customer perceived value (MCPV) variable directly affects customer loyalty. It consists of price, emotional value, physical and non-physical attributes of Islam. Moreover, quality and social value variables directly do not affect loyalty of sharia banking customers. Third, satisfaction only mediates the effect of price, emotional value, and social value variables on the loyalty of sharia banking customers. Satisfaction does not mediate the effect of quality, Islamic physical attributes, and Islamic nonphysical attributes affect the loyalty of sharia banking customers. Forth, Religiosity does not moderate the effect of Muslim customer perceived value (MCPV) variable, namely Islamic physical attributes and Islamic nonphysical attributes, on satisfaction of sharia banking customers.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".