Powered by OpenAIRE graph
Found an issue? Give us feedback
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Recolector de Cienci...arrow_drop_down
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Article . 2022
License: CC BY NC ND
Data sources: ZENODO
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Transportation
Article . 2021 . Peer-reviewed
License: Springer Nature TDM
Data sources: Crossref
versions View all 4 versions
addClaim

Service quality, satisfaction and behavioral intentions towards public transport from the point of view of private vehicle users

Authors: de Oña, Juan;

Service quality, satisfaction and behavioral intentions towards public transport from the point of view of private vehicle users

Abstract

In order to attract car users towards the public transport services in an urban and metropolitan context, contributing to a sustainable mobility in cities, it is fundamental to improve our knowledge of service quality perceptions, satisfaction and behavioral intentions toward transit from the point of view of private transport users. This paper is based on the data from a single survey —carried out in two European cities (Madrid and Lisbon) — of regular private vehicle users that use public transport at least occasionally. The questionnaire gathers information about 14 attributes of service quality, four indicators for satisfaction and four indicators for behavioral intentions; as well as several sociodemographic variables that are used in the models (household location, gender, age, education, dependent members in the family and income). The study uses confirmatory factor analysis (CFA) to identify the most important service quality attributes for the car users; structural equation modeling (SEM) for investigating the relationships among the three factors; and multi-group analysis (MGA) and a multiple-indicator and multiple-causes (MIMIC) approach to identify heterogeneity in the models because of geographical context or sociodemographic characteristics. Regular private vehicle users in both cities agree that punctuality, frequency, information and intermodality are among the five most important service quality attributes. Residents in Madrid also emphasize speed, while service hours would be a priority in Lisbon. The models for both cities agree on a complete mediator role of satisfaction between service quality and behavioral intentions. The MGA and MIMIC approaches show that the models do not present important differences tied to the sociodemographic characteristics, although differences are identified between Madrid and Lisbon. The MIMIC approach identified differences associated with city, household location and education for the pooled data; while household location, age and education were significant in Lisbon.

Support from Spain´s Ministry of Economy and Competitiveness (Research Project TRA2015-66235-R) is gratefully acknowledged.

Countries
Australia, Australia, Spain, Australia, Australia, Australia, Australia, Australia, Australia, Australia, Australia, Australia, Australia
Keywords

ridership - behaviour, public transport, 330, full mediator, potential user, Full mediator, place - urban, SEM-MIMIC, loyalty, Potential user, Loyalty, place - europe, Non-user, planning - methods, ridership - perceptions, non-user, ridership - modelling, Public transport, planning - surveys

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    56
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 1%
Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
56
Top 1%
Top 10%
Top 1%
Green