Measuring Commuters’ Perception on Service Quality Using SERVQUAL in Public Transportation
Bibliographic record
Abstract
In the current scenario of globalization, public transportation services (PTS) need to introspect sensitivitytowards the quality of services offered. In this context, this study examined the commuters’ perception onservice quality offered by the public transport services of twin cities of Hyderabad and Secunderabad, India. TheSERVQUAL scale is administered to measure the commuter’s perception on service quality. A survey wasconducted among the commuters who were regularly availing public transport services for travelling. A randomsample of 534 respondents were taken for data collection, among them 512 were finalized for final analysis. Thestudy concluded that the service quality delivery meets the perception of commuters. In general, people of twincities of Hyderabad and Secunderabad are benefited with the service quality delivery by public transport services.This paper brings out a service quality image which can be adopted by other cities whose population depends onpublic transportation services.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".