The quality of service desired by public transport users

By Luigi dell'Olio, Angel Ibeas, Patricia Cecín. 2011

661 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Transportation

View Paper: https://www.semanticscholar.org/paper/211352d749486f5af4ba854ee672f259dd141c71

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Citations in the corpus

The relationship between norms, satisfaction and public transport use: A comparison across six European cities using structural equation modelling (2019, background): “comfort (de Oña et al., 2013; Fellesson and Friman, 2012; van Lierop et al., 2017; Weinstein, 2000; Redman et al., 2013; dell’Olio et al., 2011; Allen et al., 2018a; Guirao et al., 2016), staff behavior (de Oña et al.”
Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use? (2014, methodology): “Currently, the MNL model is widely used in biometrics, econometrics, psychometrics, sociometrics, and many other fields, where it uses a set of explanatory variables to predict the probabilities of different possible outcomes of categorically distributed responses (Dakin et al., 2006; Millington et ”
Travel satisfaction revisited : on the pivotal role of travel satisfaction in conceptualizing a travel behavior process (2017, background): “Service attributes such as cleanliness, comfort, the personnel’s behaviour, safety, punctuality and frequency are most likely to influence public transport users’ satisfaction (e.g., de Oña et al., 2013; dell’Olio et al., 2011; van Lierop et al., 2017).”
Do people travel with their preferred travel mode? Analysing the extent of travel mode dissonance and its effect on travel satisfaction (2018, background): “Furthermore, the quality of service attributes such as cleanliness, comfort, and punctuality are important elements affecting public transport ridership (e.g., Chen et al., 2011; dell’olio et al., 2011; Lai and Chen, 2011; van Lierop et al., 2018).”
Modelling user perception of bus transit quality considering user and service heterogeneity (2014, methodology): “tures allow the numerical treatment of data by estimating latent variables (Eboli and Mazzulla 2007, 2012b). Wen, Lan, and Chen (2005) carried out an exploratory factorial analysis where the hidden variables are finally introduced into the modal split model for the intercity bus services in Taiwan. ”
Crowding in public transport: Who cares and why? (2017, background): “…on survey data, various studies have thus highlighted that crowding is a major component of PT users’ satisfaction and service quality, next to travel duration, connectivity of the network, service frequency and fares (see Eboli and Mazzulla 2007, Dell’Olio et al. 2011, de Ona and de Ona 2015).”
Satisfaction-induced travel behaviour (2019, background): “The way people perceive public transport trips is influenced by service attributes such as punctuality, frequency, cleanliness, comfort, and the personnel’s behaviour (e.g., de Oña et al., 2013; dell’Olio et al., 2011; van Lierop et al., 2018).”