Studying the Impact of E-Service Quality on E-Loyalty of Customers in the Area of E-Banking Services
Bibliographic record
Abstract
Customer loyalty is one of the ways to build a competitive advantage and important issue in e-banking debate to achieve higher profits. While customers are less loyal to their banks and they use e-services of various banks. Despite the importance of e-loyalty, fewer banks appear to be successful in creating e-loyalty of customer. Also, there is a little knowledge about mechanisms to create customer loyalty on the Internet. The purpose of this study is better understanding the impact of e-service quality on e-loyalty of bank customers. In this regard, Hekmat Iranian Bank has been studied. In this study we made use of simple random sampling (SRS). In this method each of elements in the population has an equal chance of being selected. In this research, 384 people were considered among all customers of Hekmat Iranian bank. We also concluded that variables of completing the banking services, security, privacy and accountability and designing website will have a significant positive impact on e-loyalty and finally recommendations are presented according to the research findings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.010 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".