The Effect of Service Quality on Customers’ Satisfaction of Inter-District Public Bus Companies in the Central Region of Sarawak, Malaysia
Bibliographic record
Abstract
Service quality is a vital factor that influences customer satisfaction. For profit organizations such as public bus companies, high customer satisfaction is a sign for business success and the ability to create long-term relationships with their customers. This research is to assess the effects of service quality attributes on customers’ satisfaction towards service quality provided by inter-district public bus companies in the Central Region of Sarawak. The research adapted SERVQUAL model proposed by Parasuraman, Zeithaml and Berry (1988). A total of 400 respondents were obtained among inter-district public bus users through a convenient sampling method. The mean score for customers’ satisfaction was 2.24, which means the level of customer satisfaction towards the service quality of inter-district buses in the Central Region was low. Meanwhile, the result from the multiple regression analysis showed that service quality dimensions of empathy, assurance, and responsibility had significant effects on customers’ satisfaction. The inter-district public bus companies in the Central Region of Sarawak should improve their service quality by building and obtaining customer trust to keep existing customers and at the same time to attract potential customers. Good customers’ experience towards service and the power of word mouth are marketing tools to enhance business reputation relative to other competitors.
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".