An AHP Approach for Ranking Critical Success Factors of Customers Experience in Iranian Banks from Managers’ Viewpoint
Bibliographic record
Abstract
Nowadays, customer experience is considered as a critical factor in growth cycle of each business. These daysonly those organizations that their main focus is fulfilling customer’s demands and desires with maximumquality can be succeed. The main purpose of this study is identifying and prioritizing critical success factorsfrom perspective of bank’s managers and experts. Considering these factors as key success factors can improvecustomer experience in banking services and help the banks to provide more favorable experience forcustomer .The statistical population consist of manager and customer of Refah bank in Isfahan city. Because thenumber of managers was limited census method has been used to select appropriate number of manager andexpert. For data analyzing, Analytic Hierarchy Process (AHP) through pair-wise comparison of factors andsub-factors has been applied by using Expert Choice software. The results suggest that “behavioral experience”is the most important factor in designing customer experience. So, behavioral experience has the most influenceon critical success factors at Refah bank. Cognitive aspect possesses the second priority and “affectiveexperience” possesses the lowest priority among all the other factors. By calculating inconsistency rate ofpair-wise comparison matrix, consistency of these factors is also acceptable. In addition, considering the resultsub-criteria of “employees” and “service process” possess the first and second priority respectively betweenfourteen sub-criteria of critical success factors.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".