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Record W4306925938 · doi:10.18280/ijsdp.170625

Evaluating the Level of the Shuttle Service Quality at Al al-Bayt University Campus Using the SERVQUAL Model

2022· article· en· W4306925938 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2022
Typearticle
Languageen
FieldEngineering
TopicUrban Transport Systems Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSERVQUALService qualityReliability (semiconductor)Service (business)BusinessOperations managementComputer scienceMarketingEngineering

Abstract

fetched live from OpenAlex

This paper mainly adopts descriptive analysis method and case study method and uses SERVQUAL model and statistical method to measure and evaluate the service quality level of shuttle bus of Al al-Bayt University. The study concluded that the order of the dimensions of measuring the quality of shuttle service was as follows: assurance, reliability, and empathy at a medium level; then tangibility followed by responsiveness at a low level for each. In general, the students' satisfaction level with the shuttle services provided at the campus was low, especially for the tangibility and responsiveness dimensions. This research is of value to transport service providers in understanding the gaps in and requirements of their service provision. To policy makers it highlights the dissatisfaction in the current levels of public transport service, as well as providing some indication of areas in which future interventions can be directed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.100
GPT teacher head0.312
Teacher spread0.212 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it