A Composite Index for Evaluating Transit Service Quality across Different User Profiles

Oña, Juan de; Oña, Rocío de; Diez-Mesa, Francisco; Eboli, Laura; Mazzulla, Gabriella

doi:10.5038/2375-0901.19.2.8

Cited by 34 publications

(14 citation statements)

References 27 publications

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“…Improving public transport supply quality and detecting the real demand of citizens for its development were investigated by several scholars through employing not only statistical methodologies but also dynamical methodologies. In reference [1], the metropolitan Metro of Seville service quality was evaluated to provide a reliable measurement tool for transit performance by using composite index that combines the passenger point of view with the service provider point of view. Reference [2] aimed to evaluate the service quality of public bus transport in the UK by adopting a quality competition model and fare levels for high-density routes.…”

Section: Introductionmentioning

confidence: 99%

An Integrated Decision Support Model for Evaluating Public Transport Quality

et al. 2020

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Big cities suffer from serious complex problems such as air pollution, congestion, and traffic accidents. Developing public transport quality in such cities is considered an efficient remedy to obviate these critical issues. This paper aims to determine the significant supply quality criteria of public transportation. As a methodology, a hybrid Analytic Hierarchy Process (AHP) combined with the Best Worst Method (BWM) is applied. The proposed model is basically a hierarchy structure with at least a 5 × 5 pairwise comparison matrix or larger. A real-world complex problem was examined to validate the created model (public transport quality improvement). An urban bus transport system in the Jordanian capital city, Amman, was used as a case study; three stakeholder groups (passengers, nonpassengers, and representatives of the local government) participated in the evaluation process. The conventional Analytic Hierarchy Process (AHP) leads to weak consistency in the case of existing 5 × 5 pairwise comparison matrices or larger, particularly in estimating complex problems. To avoid this critical issue in AHP, we used Best Worst Method (BWM) comparisons, which make the evaluation process easier for decision makers; moreover, it saves survey time and provides more consistency when compared to AHP pairwise comparisons. The model adopted highlighted the most significant service quality criteria that influence urban bus transport systems. Furthermore, the sensitivity analysis conducted detected the stability of the criteria ranking in the three levels of the hierarchical structure. Since the proposed AHP–BWM model (which is the sole example of this sort of combination) is independent from the decision attributes, it can be applied to arbitrary hierarchically structured decision problems with a relatively large number of pairwise comparisons.

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Section: Introductionmentioning

confidence: 99%

An Integrated Decision Support Model for Evaluating Public Transport Quality

et al. 2020

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“…Traditionally, transit market research has categorized transit users as either captive or choice riders according to their vehicle access and travel behaviour (12)(13)(14). While more recent research started to segment the market further by incorporating additional factors such as attitudes and personal motivations, travel behavior and trip details and sociodemographic information in order to develop more specific policy recommendations targeted towards each group (15)(16)(17)(18). Yet such an approach to market segmentation leads to the generation of system-wide policies that require an abundance of resources to implement, while only the targeted segment of the market will benefit from this policy.…”

Section: Introductionmentioning

confidence: 99%

Where is the happy transit rider? Evaluating satisfaction with regional rail service using a spatial segmentation approach

Grisé

El-Geneidy

2018

Transportation Research Part A: Policy and Practice

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Public transit agencies are delivering transport services in a rapidly changing and highly competitive transportation market. Ensuring rider's satisfaction in such an environment has led several public transit agencies to adopt different marketing strategies. For example, market segmentation analyses are commonly employed by transit agencies to identify groups of users, which are subsequently used as a base for developing policies and strategies aimed at improving customer satisfaction. However, previous studies adopting this market segmentation approach have predominantly ignored spatial and contextual factors related to the transit network and the built environment of where a user resides, resulting in network-wide policies that are difficult to implement especially for agencies with scarce resources. This study presents a new segmentation approach that incorporates spatial and contextual factors in addition to other rider's preferences and satisfaction levels with commuter rail service in the Greater Toronto and Hamilton Area, Canada. Including these factors in a market segmentation analysis has enabled us to recommend service interventions at a local and finer scale compared to previous studies, while at the same time providing the greatest impact on a specified segment of riders. This research provides transit planners and policy makers with a spatial segmentation approach, which can be used to maximize the benefits of service improvements intended to increase satisfaction with public transit among certain groups of users in a region.

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“…Functional quality is usually considered more relevant [12], since it refers to intangible aspects of the transport service, such as users' perceptions. However, some authors, such as Tyrinopoulos and Aifadopoulou [15] and de Oña et al [16], include quantitative information related to the technical aspects of the service within their evaluations, so as to eliminate the subjectivity of considering transport service quality solely from the users' perspective.…”

Section: Concept and Components Of Perceived Service Qualitymentioning

confidence: 99%

Intra-Urban Spatial Disparities in User Satisfaction with Public Transport Services

Cordera¹,

Nogués²,

González-González³

et al. 2019

Sustainability

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Knowing public transport service’s user satisfaction is essential to maintaining and increasing its quality and demand. Several studies have analysed the factors influencing users’ satisfaction, considering their perceptions of specific attributes of the service. However, other aspects, such as the spatial distribution of users, i.e., their origin neighbourhoods, could significantly affect their satisfaction with the service, showing social inequity patterns. This paper proposes a new methodology to evaluate whether these spatial differences in satisfaction exist. Using the city of Santander (Spain) as an example, ordered probit models have been estimated, linking the bus users’ overall satisfaction with variables that include their perceptions of the service and socio-demographic characteristics, and with dummy variables which classify each trip according to its neighbourhood origin. Our results confirm the existence of variations in satisfaction depending on the area of the city under study. In addition, user characterization variables, such as age, which were not significant when considering the city as a whole, proved to be influential in some areas. The estimated model, considering spatial differences, had a higher goodness of fit than that of models not taking zoning into account, and reproduced the overall satisfaction pattern presented in the study area with less error. The consideration of spatial differences in the modelling process enabled the detection of priority areas in which to implement measures to improve service quality and equity, thus increasing the use of public transport and supporting the promotion of a more sustainable mobility.

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A Composite Index for Evaluating Transit Service Quality across Different User Profiles

Abstract: Abstract

Cited by 34 publications

References 27 publications

An Integrated Decision Support Model for Evaluating Public Transport Quality

An Integrated Decision Support Model for Evaluating Public Transport Quality

Where is the happy transit rider? Evaluating satisfaction with regional rail service using a spatial segmentation approach

Intra-Urban Spatial Disparities in User Satisfaction with Public Transport Services

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