Evaluating Online Government-to-Citizen E-Governance Services at Nepal Bank Limited: Digital Service Scope and Customer Satisfaction
Bibliographic record
Abstract
This research assesses usage, satisfaction, and the barriers to adoption of on-line G2C e governance services furnished through digital channels of Nepal bank limited, using the case of the Mahendranagar office. In support of Nepal's Digital Nepal Framework, NBL acts as a critical middleman for services authorities’ offerings, such as pension payment, tax series, and scholarship payments, through online banking A descriptive quantitative technique supported via wealthy qualitative insight become followed, whereby data from 158 clients had been accrued through a web survey and from one department IT officer through a semi-structured interview. Consequences show that mobile banking is the most major access point, at 73.4% of the respondents, even as many users combine numerous offerings; superior offerings consisting of net Remit have very low standalone take-up at 2.5%. Overall pride is pretty high-approximately 80% of users are satisfied or very happy-security is perceived most positively, at 86.2% feeling secure, followed by way of speed, with 77.8% saying they're satisfied. But a noticeable reliability hole stays fewer than 75.5% of customers charge carrier availability as good or Excellent and this decreased reliability continues to decrease universal consumer pride. Correlation attempting out revealed that perceived protection had the most powerful high-quality link with common pleasure (Pearsons r = 0.692, p < 0.01, 95% CI [0.61, 0.76]). This locating got here from a Pearson correlation evaluation done after the Shapiro Wilk take a look at verified that the data met the vital assumptions for parametric attempting out. The sturdy figuring out pride with virtual G2C services. Key boundaries to adoption consist of lack of internet get right of entry to (48.1%), common server outages (24.7%), poorly designed interfaces (19.6%), restricted virtual literacy (17.7%). clients moreover indicated that quicker gadget performance (50.6%), more powerful protection features (46.8%), 24*7 availability (36.7%) may want to inspire greater usage. Insights from an IT officer align with the one’s findings, pointing to resistance to alternate and gaps in virtual abilities, despite the fact that standard infrastructure and adoption tiers seem especially strong. The have a look at in the end indicates that to reinforce lengthy-term adoption and consumer accept as true with, NBL should popularity on ensuring more strong company availability, streamlining multi-carrier procedures, and implementing client targeted schooling and alternate-control projects. The ones measures can actively decorate the general effect and performance of financial institution-facilitated e-governance in Nepal.
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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 | 0.008 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".