2019
DOI: 10.1007/s11116-019-09996-4
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Modelling user satisfaction in public transport systems considering missing information

Abstract: Collecting data to obtain insights into customer satisfaction with public transport services is very time-consuming and costly. Many factors such as service frequency, reliability and comfort during the trip have been found important drivers of customer satisfaction. Consequently, customer satisfaction surveys are quite lengthy, resulting in many interviews not being completed within the aboard time of the passengers/respondents. This paper questions as to whether it is possible to reduce the amount of informa… Show more

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Cited by 13 publications
(12 citation statements)
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“…The scenarios of each choice experiment are characterized by two choice alternatives described by six attributes. The number of attributes and their levels of variations were chosen by taking into account that the more attributes and levels there are in a choice experiment design, the less likely that dominant alternatives will exist [62]; otherwise, the interviewees should not be asked to compare too many variables, to avoid the lack of their concentration in making their choice [63][64][65]. The alternatives of a "before/after the flight" scenario are described by the following variables: Waiting time at check-in, time spent for boarding operations, terminal-aircraft transfer mode, delay of flight departure, time spent for luggage delivery, and cost of the ticket.…”
Section: Sp Survey Designmentioning
confidence: 99%
“…The scenarios of each choice experiment are characterized by two choice alternatives described by six attributes. The number of attributes and their levels of variations were chosen by taking into account that the more attributes and levels there are in a choice experiment design, the less likely that dominant alternatives will exist [62]; otherwise, the interviewees should not be asked to compare too many variables, to avoid the lack of their concentration in making their choice [63][64][65]. The alternatives of a "before/after the flight" scenario are described by the following variables: Waiting time at check-in, time spent for boarding operations, terminal-aircraft transfer mode, delay of flight departure, time spent for luggage delivery, and cost of the ticket.…”
Section: Sp Survey Designmentioning
confidence: 99%
“…The method used to complete the sample has been based on Multiple Imputation [54,55]. The study developed by Echaniz et al [56] showed that it is possible to obtain conclusive results using this imputation method for satisfaction studies in public transport. Multiple imputation is estimated by using a procedure called Fully Conditional Specification (FCS), which uses an iterative Monte Carlo method with Markov chains [57].…”
Section: Ordered Logit Modelmentioning
confidence: 99%
“…By using the multiple imputation method a small prediction error is assumed. Echaniz et al [56] showed that estimating a model by using multiple imputation to complete the database leads to a lower model fit. The differences on fits between full dataset models and partial data models was empirically proven to be 2% less correct predictions when multiple imputation is used to complete the missing information.…”
Section: Ordered Logit Modelmentioning
confidence: 99%
“…On the other hand, some researchers tried to improve the overall methodology framework by applying SEM or discrete choice models ( 16 ). An SEM represents the most appropriate methodology to measure latent variables and assessing the structural relationships between these latent variables given the multidimensional nature of SQ attributes ( 5, 17 ).…”
Section: Literature Reviewmentioning
confidence: 99%