Client's satisfaction towards cleaning service provided by the cleaning service firm in schools at Padawan area : A case study on Zona Enterprise / Wan Ismail Wan Sunusi
Bibliographic record
Abstract
Customers' satisfaction has been a very prominent issue in marketing. It is very important to deliver high level of service quality which in turn will create satisfied customers who will keep patronizing our business and generate profitability for us, Kotler (2000)The objective of this study is to estimate the satisfaction level of customers toward the service cleaning provided by Zona Enterprise by using eleven ( 1 1 ) determinants as proposed by Ghobidian et. al. The eleven determinants are responsiveness, reliability, sect-frity, courtesy, competence, understanding the customers, customization, access, communication, tangible and credibility.Besides obtaining customers satisfaction level by using the determinants, this research also determined which of the determinants had the strongest impact on customers' satisfaction as perceived by the customers. Through that way, the researcher was able to know the determinants that the customers perceived as having a strong influence on satisfaction.The findings shows that almost three quarter ofl the respondents were satisfied with the cleaning service provided by Zona Enterprise with the percentage of satisfaction amounted to 70.8%. Respondents were very satisfied with the determinants access and tangibles while quite dissatified with Understanding the customers and also tangibles. For the ranking part, the respondents ranked Reliability as the determinant that has the strongest impact and influence on customers' satisfaction with total score of 394. Meanwhile, Customization is on the lowest rank with total score of 323.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".