A Good Quality Service Provision in the Network Service in Ghana: A Case Study of MTN Ghana
Bibliographic record
Abstract
This study tries to investigate if MTN Ghana provides good quality service and to establish the factors that determine the service quality of mobile telecommunication as perceived by MTN customers in Ghana. The study used both primary and secondary sources of information from the MTN (GH) Ltd employees and its customers. The primary data was mainly from the questionnaires that were administered to MTN customers and the secondary data were annual reports, brochures and manuals from the MTN (GH) Ltd offices. Purposive sampling was used to select which branch of the organization to visit for the study and stratified random sampling was used to select staffs for the study. The study used the SPSS software to run multiple Regression analysis by examining the inter-relationship between Good Quality Service (Dependent variable) and a number of explanatory (Independent) variables such as provision of efficient service, Offers wider range of service, Offers high rates of interests on premium, community mindedness, good customer retention, degree of customer relationship, Introduction of innovative products and Opportunity to complain as factors contributing to good quality service of the MTN. The results of the analysis revealed that community minded is an independent variable that makes the highest contribution to Good Quality Service. It then identified provision of efficient service as having the highest partial correlation with Good Quality Service, so it was added in the second model, model 2 and offers wider range of service was the next significant variable, so it was added to model 3, and Introduction of innovative products was the next significant variable, so it was added to model 4 and offers high rates of interests on premium was the last significant variable, which was also added to model 5. The study recommends that the MNT (Ghana) Ltd should improvement the quality of their services, as the services provided by them is perceived by MTN customers to be poor. The study further suggests that MTN needs to provide visible supports including social and infrastructural support to communities in which they operate to serve as the strongest advertisement for the MTN Company.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".