Assessment of Quality of Service of Mobile Network Operators in Akure
Bibliographic record
Abstract
This study assessed and compared the Quality of Service provided by the four major Mobile Network Operators(MNOs) in Akure, Nigeria as well as assessed their level of compliance with Nigerian Communications Commission standard. The study also examined the level of customer satisfaction on the services delivered by the MNOs. The effect of Quality of Service on the satisfaction of the customers of the MNOs was also investigated in this study.Primary data was collected in this study using both the drive test and survey questionnaire techniques. The drive test technique was used to collect data on the Quality of Service provided by the MNOs while the survey questionnaire was used to collect data on customer satisfaction from 527 respondents.Descriptive statistics was used to assess the level of Quality of Service provided and also to examine the level of customer satisfaction. The one-way ANOVA was adopted to compare the Quality of Service provided among the MNOs while Regression analysis was used to examine the effect of Quality of Service on customer satisfaction.The study revealed that the Quality of Service of the Mobile Network Operators in Akure differed significantly (P<0.05). It also revealed a moderate level of satisfaction among the customers. Though the Quality of Service provided by the Mobile Network Operators was found not to meet Nigerian Communications Commission standard for most of the key performance indicators, MTN was found to be the best. The study also revealed that the effect of Quality of Service on the satisfaction of customers is insignificant. The study recommended that the Mobile Network Operators should build more base stations as this would help reduce coverage gaps and blind spots and ultimately increase their network coverage.
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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 | 0.001 | 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 | 0.000 |
| 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".