Bibliographic record
Abstract
For maintaining competitiveness in the market, the pursuit of service quality for service providers is necessary. Customer satisfaction is necessary for acquiring customer loyalty and having better financial controls. Service quality on banks is done on several studies including USA, Canada and Tunisia, Malaysia, five Balkan countries: Albania, Greece, FRYOM, Bulgaria and Serbia and India. The research gap in the current literature is that very few studies have been done on the impact of demographic variables on the perception of service quality. The objective of this article is to examine the effect of type of bank i.e. public and private sector banks on perception of quality of banking services. The instrument used for evaluating service quality was Bank Service Quality created by Bahia and Nantel (2000). This instrument consists of 31 items which spans 6 dimensions: access; effectiveness and assurance; tangibles; price; services portfolio and reliability. In the study, perception was only measured with the items of perception only. A quantitative research approach and well-structured survey questionnaire was used in the study. Convenience sampling was used with 51 questionnaires and google forms were used for collecting the data. Data collected was analysed using SPSS version 16. The highest score for both public and private sector banks was for “effectiveness and assurance” dimension. The lowest score for public and private sector banks was for “reliability” dimension. ANOVA was used to check whether there were significant differences among public and private sector banks for six dimensions. The result shows that there are non-significant differences among perceptions of public sector and private sector banks on all six dimensions. There are nonsignificant differences on all 31 items in the case of public sector and private sector banks. The study shows that respondents of both public and private sector banks perceive that service quality of banks is not as per their expectations. The limitation of this study is that convenience sampling has been used in the study. Moreover, it would not represent the perception of service quality of banks in the whole of India. Future studies could be done involving large and representative samples. Keywords: service quality, reliability, banks, service portfolio, access
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".