Determinants of Customer Satisfaction in the Telecommunication Industry in Ghana: A Study of MTN Ghana Limited
Bibliographic record
Abstract
The study examined the determinants of customer satisfaction in MTN Ghana Limited. The variables of concern were customer expectation, relationship quality, perceived value, perceived quality, and customer loyalty. The American Customer Satisfaction Index (ACSI) model was adapted as the main framework for analyzing customer satisfaction. Data for the study came from a systematic random sample of 377 MTN mobile subscribers, employing questionnaires. Two managers of the mobile network were interviewed on issues related to their CRM systems. Multiple regression analyses were used to examine the relationship between customer expectation, relationship quality, perceived value, perceived (product/service) quality, customer loyalty, and customer satisfaction. The results of the multiple regression indicated that significant positive relationship existed between customer satisfaction and perceived (product/service) quality, relationship quality, and customer loyalty, but not for other variables such as customer expectation, customer complaint, and perceived value. The implications are that MTN Ghana should consider the perceptions of customers on product/service quality, the level of relationship quality and loyalty when managing relationships with customers. The company should put measures in place to build and maintain quality relationships with customers, and also improve the quality of products and services offered to customers. Again, there is the need for management to bridge the gap in their perception of relationship quality and that of customers.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".