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Cited by 477

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Perceived service quality in bus transit service: A structural equation approach

Open access
de Oña, Juan, de Oña, Rocío, Eboli, Laura, Mazzulla, Gabriella·2013·Transport Policy

Abstract

This paper proposes a methodology for evaluating the quality of service perceived by users of a bus transit service. A Structural Equation Model (SEM) approach is used to reveal the unobserved latent aspects describing the service and the relationships between these aspects with the Overall Service Quality. Data from a Customer Satisfaction Survey conducted by the Transport Consortium of Granada (Spain) are analyzed. A total of 1200 surveys were collected, and two passengers’ statements about the Overall Service Quality were gathered: the first one when passengers have not reflected on the attributes describing the service, and the second one after they have thought about them. This is the first time that the Overall Service Quality of a public transport system has been jointly explained by these two overall evaluations when a SEM approach is adopted.

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Crossref · 10.1016/j.tranpol.2013.07.001

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Metadata

Authors
de Oña, J., de Oña, R., Eboli, L., & Mazzulla, G.
Venue
Transport Policy
Publisher
Elsevier BV
Published
2013-09
Volume
29
Pages
219-226
ISSN
0967-070X (ISSN-L)
OpenAlex
W2080833703
Cited by
477
References
22
FWCI
59.02
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Perceived service quality in bus transit service: A structural equation approach. https://app.cochat.ai/papers/10.1016/j.tranpol.2013.07.001
The paper
de Oña, J., de Oña, R., Eboli, L., & Mazzulla, G. (2013). Perceived service quality in bus transit service: A structural equation approach. Transport Policy. https://doi.org/10.1016/j.tranpol.2013.07.001

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.