The Impact of E-Banking on Customer Satisfaction: Evidence from Banking Sector of Pakistan
Bibliographic record
Abstract
Customer satisfaction is imperative for the incessant survival of any organization around the world. This research work intends to investigate the impact of E-banking variables on customer satisfaction in Pakistan. Five service quality dimensions; reliability, responsiveness, assurance, tangibles and empathy, derived from the SERVQUAL model with support of literature review have been selected as forecasters of customer satisfaction in E-banking. Research design of the study is quantitative. Data has been gathered through already tested questionnaire from 264 E-banking users as respondents, from different cities of Pakistan. Results of the study have revealed that there is momentous relationship between service quality dimensions and customer satisfaction in E-banking in Pakistan, with more weightage of reliability, responsiveness and assurance among the five dimensions. Through this study we can conclude that service quality in E-banking leads to satisfied customers and thus banks can gain competitive advantage by offering better-quality services to their customers in today’s emulous world.
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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 | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".