Parametric Approach to the Assessment of Service Quality Attributes of Municipal Passenger Transport in Moscow
Bibliographic record
Abstract
The paper presents the results of research of passenger transport services in the city of Moscow by public transport.The research method is based on assessing the quality by using "Mystery Shopper" observation method.The peculiarity of the method involves the use of parametric indices outlined by researchers and affecting quality of the provided transportation service.These parameters include cleanliness, ticket-selling speed, presence of cellular signal, etc.The obtained results demonstrate that, given the existing features of automatic vending machines, they still cannot completely replace traditional ticket offices.The results of the research demonstrate that the applied method does not allow relating the presence of a particular inspected parameter to service quality perception by consumers.The researchers see the future direction of their work on the revision of the applied methodology in the part for calculation the level of satisfaction, for example, based on a special index.In particular, inclusion of the parameters of perceived quality, use of a multi-stage or stratified sampling to improve the representativeness of the research results, use of frequency measurement -4 times per year to account for the seasonality factor.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".