Public Transportation Quality of Service: Factors, Models, and Applications

By Luigi Dell´Olio, Angel Ibeas, Juan de Ona and Rocio de Ona

Public Transportation Quality of Service: Factors, Models, and Applications is the first book to help researchers better understand the contributing factors that can improve public transportation perception among users. The book compiles in one place metrics currently dispersed in journal articles, government publications and book chapters. It critically analyzes currently available modeling methodologies such as the Ordered Logit/Probit model and Models of Structural Equations, highlighting their advantages and disadvantages. The book addresses models of desired quality, including the views of users and non-users, discussing the gap between desired and perceived quality.

The book also examines data mining approaches such as decision trees and neural networks, showing how to involve the public in the decision-making process to create policies that encourage public transport demand. Measuring passenger’s views on public transportation is of critical concern to promote wider transit use in cities around the world.

• Includes insights from both theoretical and practical points of view for both researchers and practitioners
• Features case studies in each chapter that apply models discussed
• Helps readers develop and design their own studies for measuring quality of service
• Shows how to include perceived quality in contracts
• Provides access to the survey formulas and data to better enable implementation of models

• Language: English
• Publisher: Elsevier Science
• Release date: Oct 11, 2017
• ISBN: 9780081022795

Luigi Dell´Olio

Luigi Dell´Olio is a member of the Council of the Association for European Transport, Guest Editor of Transportation Research Part A: Policy and Practice and Procedia of Social and Behavioural Science, Editor of the Journal of Scientific Research and Reports, and Editorial Board Member of the Journal of Logistics and Operational Research.

Book preview

Public Transportation Quality of Service

Factors, Models, and Applications

Luigi dell’Olio

Angel Ibeas

Juan de Oña

Rocio de Oña

Table of Contents

Cover image

Title page

Copyright

Acknowledgments

Chapter 1. Introduction

Chapter 2. How to Study Perceived Quality in Public Transport

2.1. Introduction

2.2. Background

2.3. Characteristics and Methodological Aspects Relating to Service Quality in Public Transport

2.4. Methodological Approaches for Analyzing Service Quality

2.5. Methodologies to Estimate the Relative Importance of Each Service Quality Attribute

2.6. Conclusions

Chapter 3. Public Participation Techniques and Choice of Variables

3.1. Qualitative Research and Public Partnership, Introduction

3.2. Public Partnership Methods

3.3. Public Partnership Tools and Techniques

3.4. Public Partnership and the Selection of Variables

3.5. Practical Applications

Chapter 4. Designing a Survey for Public Transport Users

4.1. The Design of a Survey for Public Transport Users

4.2. Types of Survey

4.3. Methods for Collecting Information Using Surveys

Chapter 5. Geo-Social Differences in the Perception of Quality

5.1. Introduction

5.2. The First Quality Studies in Different Geosocial Contexts

5.3. Survey Types

5.4. Analysis Methodology

5.5. Most Important Variables

Chapter 6. Most Basic Methods

6.1. Introduction

6.2. Factorial Analysis

6.3. Importance-Performance Analysis

6.4. Analysis Techniques of Customer Satisfaction Indexes

6.5. Conclusions

Chapter 7. Methods Based on Random Utility Theory

7.1. Introduction

7.2. Qualitative Versus Numerical Preferences

7.3. Ordered Logit/Probit Model

7.4. Simple Ordered Logit/Probit Model

7.5. Ordered Probit Model With Systematic Variations (Interactions)

7.6. Ordered Probit Model With Random Parameters

7.7. Ordered Probit Model With Weighted Variables

7.8. Discussion

Chapter 8. Structural Equation Models

8.1. Introduction

8.2. Theoretical Foundation

8.3. Measurement Model: CFA

8.4. Structural Model: Hypothesis Testing

Chapter 9. Data Mining Approaches

9.1. Introduction

9.2. General Considerations About DM Techniques

9.3. Artificial Neural Networks

9.4. Bayesian Networks

9.5. Decision Trees

9.6. Comparative Analysis

9.7. Conclusions

Chapter 10. Beyond Perceived Quality: Desired Quality

10.1. Desired Quality

10.2. Methodology for Studying Desired Quality

10.3. Stated Preferences Surveys

10.4. Modeling the Data

10.5. Results Analysis

10.6. Conclusions

Chapter 11. Quality in Public Transport Contracts

11.1. Introduction

11.2. Approach to the Inclusion of Quality in Public Transport Contracts

11.3. Methodology

11.4. Application in a Real Case Study

11.5. Conclusions

Index

Copyright

Elsevier

Radarweg 29, PO Box 211, 1000 AE Amsterdam, Netherlands

The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom

50 Hampshire Street, 5th Floor, Cambridge, MA 02139, United States

Copyright © 2018 Elsevier Ltd. All rights reserved.

No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publisher’s permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions.

This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein).

Notices

Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary.

Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility.

To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein.

Library of Congress Cataloging-in-Publication Data

A catalog record for this book is available from the Library of Congress

British Library Cataloguing-in-Publication Data

A catalogue record for this book is available from the British Library

ISBN: 978-0-08-102080-7

For information on all Elsevier publications visit our website at https://www.elsevier.com/books-and-journals

Publishing Director: Jonathan Simpson

Acquisition Editor: Brian Romer

Editorial Project Manager: Andrae Akeh

Production Project Manager: Punithavathy Govindaradjane

Designer: Christian J. Bilbow

Typeset by TNQ Books and Journals

Acknowledgments

The authors would like to thank the road passenger transport company ALSA for their support in the research included in this book. We would also like to thank the Ministerio de Economía y Competitividad of the Spanish Government for financing the projects TRA2015-69903-R and TRA2015-66235-R (MINECO/FEDER, UE) cofinanced from European Union FEDER funds and TRA2013-48116-R, which deepened our understanding of many of the subjects described in the book. We would also like to thank EU FEDER funding for their financial support via the project G-GI3002/IDIK, part of the Programa Operativo FEDER de Andalucia 2007–2013.

The members of the Grupo de Investigación de Sistemas de Transporte (GIST) based at the University of Cantabria would like to give a special thank you to Santander City Council and the mayor Gema Igual for having faith in our group and for allowing us to experiment with these techniques in the living lab de Santander. We would also like to express our gratitude to the Ministerio de Fomento of the Spanish Government and the Minister Iñigo de la Serna for promoting and encouraging research into urban public transport quality since his time as mayor of Santander.

The members of the Transporte y Seguridad (TRYSE) research group based at the University of Granada would like to dedicate a few words of thank you to the Consorcio de Transportes del Área de Granada and in particular their managing director Christian Muñoz Monge for providing us with quality survey data over the last 10  years. The Agencia de Obra Pública of the regional government of Andalucía has kindly provided financial assistance for some of the quality research that this group has participated in.

The authors would like to dedicate some words of thanks to the members of the research groups GIST and TRYSE for their collaboration, suggestions, and support in the review of this book. We would particularly like to thank Roberto Sañudo and Sara Ezquerro for their collaboration with Chapter 3, Rubén Cordera for his collaboration with Chapter 4 and his inestimable help in reviewing most of the chapters of this book, Eneko Echaniz for his collaboration with Chapters 6 and 7, Gonzalo Antolín for his collaboration on Chapter 6, José Luis Machado for his contributions made to Chapter 8, and Conchi Garrido and Francisco J. Diez for their collaboration with Chapter 9. Particular thanks go to Marta Rojo and Hernán Gonzalo for their collaboration in the writing of Chapter 11, and, finally, the geographer Chris Tyas for his contributions, suggestions, and advice with regards to the translation of this book.

Chapter 1

Introduction

Contents

References

To understand the quality of service that users of public transport perceive they are receiving is a modern requirement. As stated by Parasuraman, Zeithaml, and Berry (1988), the improvement of quality is a business strategy that adds value to a service and helps differentiate it from its competitors. Market research carried out in the transport sector has shown the important role users have in evaluating service performance and highlighted the subjectivity of their perceptions. Although they may sometimes appear strange, the preferences of users need to be considered by the operating companies and the supervising agencies. Parasuraman, Zeithaml, and Berry (1985) proposed considering the points of view of both the service providers and the customers in order to measure the discrepancies between user expectations and transport agency objectives.

Demand has a direct relationship with perceived quality and this relationship is what has motivated the development of many applied research works such as the multiple studies on the design of performance-based contracts in the transport sector (Hensher & Prioni, 2002; Hensher, Stopher, & Bullock, 2003; Mokonyama & Venter, 2013), which are aimed at giving the companies incentives to improve their performance and penalizing those that do not provide a quality service.

Evidently there is a dilemma as to whether or not an improvement in performance will have a direct and immediate effect on increasing the demand. Friman (2004) stated that the level of satisfaction felt by users due to service improvements cannot rise without end and does, therefore, have a limit. By observing how user perception changed with improvements made to the system, they realized that users do not always perceive these changes as a positive thing or where they do perceive them, the changes do not always influence their satisfaction levels. This leads to the understanding that it is important to know how users behave and how their satisfaction levels can be influenced or not by changes made to the system.

By performing research in this field, we are able to achieve two fundamental targets:

• Find solutions that maximize user satisfaction.

• Improve the system at an acceptable cost by avoiding unnecessary expense on parts of the service that have no influence on user satisfaction.

We also need to establish what perceived quality actually means. It could be the quality of certain goods or a service compared with similar goods or services or it may simply be the level of quality provided by the goods or services on their own.

These two definitions define two concepts of quality:

• Relative perceived quality

• Absolute perceived quality

Given the assumption that no clear distinction is available in the international literature for these two concepts, we can state that satisfaction is normally associated with relative perceived quality, where the reference is toward the users' own experiences or expectations.

Therefore, when we speak about relative perceived quality, we need to be clear that our perceived quality refers to something that in the literature is called expected quality or which some studies define as desired quality (dell'Olio, Ibeas, & Cecin, 2011). Parasuraman, Berry, and Zeithaml (1991) opened the debate about whether or not different types of expectation existed and finally distinguished between adequate service quality and desired service quality with a zone of tolerance between the two levels of quality (Parasuraman, 1994). The level of satisfaction can, therefore, be defined as the subjective measure relative to the expectations or desires of the users, whereas the absolute perceived quality is an overall evaluation of the current level of quality without being subjected to any reference value.

All these topics are going to be addressed in this book and in particular we are going to provide an overall view of the diverse techniques currently used for measuring perceived quality and how these concepts can be applied to transport contracts to help improve services.

The book is divided into 11 chapters including the present introductory chapter. The second chapter aims to provide an overall view about the beginnings of and how the analysis of user perceived quality has developed in the field of public transport services (de Oña & de Oña, 2015). The main methods of analysis used to evaluate quality will be presented by differentiating them into aggregate methods and disaggregate methods and further differentiating between methods based only on perceptions and those based on user expectations and perceptions together. Among other methods, brief descriptions will be made of the SERVQUAL model (Parasuraman et al., 1988), the SERVPERF (service performance) model (Carrillat, Jaramillo, & Mulki, 2007), the importance-performance analysis (IPA) model, Zones of Tolerance (Hu, 2010), and some of their variations.

Chapter 3 will introduce techniques to encourage citizen participation in qualitative research, highlighting the importance of public opinion in the planning and management of transport (Ibeas, dell'Olio, & Montequín, 2011). This chapter is very important because it helps us in how to choose the relevant variables for the models and in the estimation of perceived and expected quality.

Chapter 4 describes the survey design process for users of public transport. User satisfaction surveys are differentiated from stated preferences surveys and different methods are described for establishing survey samples, which are able to represent the characteristics of public transport users and their evaluations of the service (Fowler, 2014).

The main geosocial differences found in the analysis of public transport service quality from a user's point of view are presented in Chapter 5. The different territorial contexts are classified on a world scale in accordance with the per capita Gross National Income of each nation and this classification is used to address the main differences found between them (e.g., Abenoza, Cats, & Susilo, 2017; Irfan, Mui, Kee, & Shahbaz, 2012; Tyrinopoulos & Antoniou, 2008). Furthermore, the variables identified as being of greatest importance for the users are presented according to public transport industry, field of operation, and territorial context.

Chapter 6 introduces a series of methodologies, which can be used for determining the most influential factors in the study of public transport quality. The methods aimed at determining the importance of the main influential factors on public transport quality are presented first and two of these methods are further developed: factorial analysis and IPA. This is followed in the second part of the chapter by a series of indices and procedures, which have been used in the study of public transport quality: SERVQUAL, SERVPERF, and QUATTRO (Quality approach in tendering urban public transport operations) (European Commission, 1998).

Various methods based on random utility theory that consider systematic variations in user taste (Greene & Hensher, 2010) are presented in Chapter 7. Different model specifications are proposed to find the relative importance of each variable (Echaniz, dell'Olio, & Ibeas, 2017). These models apply random utility theory in order to study ordered data from a qualitative satisfaction scale considering the nonlinearity present on the scale to be modeled.

Chapter 8 presents structural equations models as being one of the most commonly used techniques for analyzing user perceived quality in the field of public transport as well as the attitudes of users toward the service (Chou, Lu, & Chang, 2014). This method allows us to estimate the effect and relationships between multiple variables and provides an overall view of different aspects of the studied phenomena (Hair, Black, Babin, & Anderson, 2010).

Chapter 9 describes some of the data mining techniques that have been used in the evaluation and modeling of public transport quality. The three most commonly used techniques are artificial neuron networks (Garrido, de Oña, & de Oña, 2014), Bayesian networks (Perucca & Salini, 2014) and decision trees (de Oña, de Oña, & Calvo, 2012). The chapter ends with a comparative analysis of the main advantages and disadvantages of each of these three data mining techniques.

The concept of desired quality is introduced in Chapter 10 as being what the users and potential users expect they should receive from a public transport service (dell'Olio, Ibeas, & Cecin, 2011). A methodology is proposed to determine this aspect using stated preferences surveys, followed by the estimation of logit type discrete choice models aimed at modeling and analyzing the results (dell'Olio, Ibeas, Cecín, & dell'Olio, 2011).

Chapter 11 introduces a new methodology for the inclusion of quality parameters in public transport contracts by using a system of incentives for operators to invest in making service improvements (Rojo, dell'Olio, Gonzalo-Orden, & Ibeas, 2015). This approach makes investing a more attractive option for the operating companies. The results are quite positive: without increasing the overall amount invested by the overseeing administrations improvements were seen in the quality of service as perceived by the current users and demand for public transport increased (thereby reducing externalities from private car use) with an acceptable profit margin for the operators.

The codes for the software NLogit (Greene, 2007) have been added to Chapters 7 and 10 to make it easier for the end users of this book to reproduce the results of this research.

References

Abenoza R.F, Cats O, Susilo Y.O. Travel satisfaction with public transport: Determinants, user classes, regional disparities and their evolution. Transportation Research A: Policy and Practice. 2017;95:64–84. https://doi.org/10.1016/j.tra.2016.11.011.

Carrillat F.A, Jaramillo F, Mulki J.P. The validity of the SERVQUAL and SERVPERF scales. International Journal of Service Industry Management. 2007;18(5):472–490. https://doi.org/10.1108/09564230710826250.

Chou P.-F, Lu C.-S, Chang Y.-H. Effects of service quality and customer satisfaction on customer loyalty in high-speed rail services in Taiwan. Transportmetrica A: Transport Science. 2014;10(10):917–945. https://doi.org/10.1080/23249935.2014.915247.

Echaniz E, dell'Olio L, Ibeas Á. Modelling perceived quality for urban public transport systems using weighted variables and random parameters. Transport Policy. 2017. https://doi.org/10.1016/j.tranpol.2017.05.006.

European Commission. Quattro : Quality approach in tendering urban public transport operations. Office for Official Publications of the European Communities; 1998.

Fowler F.J. Survey research methods. SAGE Publication, Inc; 2014.

Friman M. Implementing quality improvements in public transport. Journal of Public Transportation. 2004;7(4). https://doi.org/. http://dx.doi.org/10.5038/2375-0901.7.4.3.

Garrido C, de Oña R, de Oña J. Neural networks for analyzing service quality in public transportation. Expert Systems with Applications. 2014;41(15):6830–6838. https://doi.org/10.1016/j.eswa.2014.04.045.

Greene W.H. NLOGIT 4.0 reference guide.. New York: Econometric software, inc; 2007.

Greene W.H, Hensher D.A. Modeling ordered choices : A primer. Cambridge University Press; 2010 Retrieved from. http://econpapers.repec.org/bookchap/cupcbooks/9780521194204.htm.

Hair J.F, Black W.C, Babin B.J, Anderson R.E. Multivariate data analysis : A global perspective. Pearson Education; 2010 Retrieved from. https://books.google.es/books/about/Multivariate_Data_Analysis.html?id=SLRPLgAACAAJ&redir_esc=y.

Hensher D.A, Prioni P. A service quality index for area-wide contract performance assessment. Journal of Transport Economics and Policy. 2002;36(1):93–113 Retrieved from. https://ideas.repec.org/a/tpe/jtecpo/v36y2002i1p93-113.html.

Hensher D.A, Stopher P, Bullock P. Service quality—developing a service quality index in the provision of commercial bus contracts. Transportation Research Part A: Policy and Practice. 2003;37(6):499–517. https://doi.org/10.1016/S0965-8564(02)00075-7.

Hu K. Evaluating city bus service based on zone of tolerance of expectation and normalized importance. Transport Reviews. 2010;30(2):195–217. https://doi.org/10.1080/01441640902884780.

Ibeas A, dell'Olio L, Montequín R.B. Citizen involvement in promoting sustainable mobility. Journal of Transport Geography. 2011;19(4):475–487. https://doi.org/10.1016/j.jtrangeo.2010.01.005.

Irfan S.M, Mui D, Kee H, Shahbaz S. Service quality and rail transport in Pakistan: A passenger perspective. World Applied Sciences Journal. 2012;18(3):361–369. https://doi.org/10.5829/idosi.wasj.2012.18.03.3044.

Mokonyama M, Venter C. Incorporation of customer satisfaction in public transport contracts ? A preliminary analysis. Research in Transportation Economics. 2013;39(1):58–66. https://doi.org/10.1016/j.retrec.2012.05.024.

de Oña J, de Oña R. Quality of service in public transport based on customer satisfaction surveys: A review and assessment of methodological approaches. Transportation Science. 2015;49(3):605–622. https://doi.org/10.1287/trsc.2014.0544.

de Oña J, de Oña R, Calvo F.J. A classification tree approach to identify key factors of transit service quality. Expert Systems with Applications. 2012;39(12):11164–11171. https://doi.org/10.1016/j.eswa.2012.03.037.

dell'Olio L, Ibeas A, Cecin P. The quality of service desired by public transport users. Transport Policy. 2011;18(1):217–227. https://doi.org/10.1016/j.tranpol.2010.08.005.

dell'Olio L, Ibeas A, Cecín P, dell'Olio F. Willingness to pay for improving service quality in a multimodal area. Transportation Research C: Emerging Technologies. 2011;19(6):1060–1070. https://doi.org/10.1016/j.trc.2011.06.004.

Parasuraman A. Alternative scales for measuring service quality: A comparative assessment based on psychometric and diagnostic criteria. Journal of Retailing. 1994;70(3):201–230. https://doi.org/10.1016/0022-4359(94)90033-7.

Parasuraman A, Berry L.L, Zeithaml V.A. Understanding customer expectations of service. MIT Sloan Management Review. 1991;32(3):39.

Parasuraman A, Zeithaml V.A, Berry L.L. A conceptual model of service quality and its implications for future research. Journal of Marketing. 1985;49(4):41. https://doi.org/10.2307/1251430.

Parasuraman A, Zeithaml V.A, Berry L.L. SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing. 1988;64(1):12–40 Retrieved from. http://search.proquest.com/openview/7d007e04d78261295e5524f15bef6837/1?pq-origsite=gscholar&cbl=41988.

Perucca G, Salini S. Travellers' satisfaction with Railway transport: A Bayesian network approach. Quality Technology & Quantitative Management. 2014;11(1):71–84. https://doi.org/10.1080/16843703.2014.11673326.

Rojo M, dell'Olio L, Gonzalo-Orden H, Ibeas Á. Inclusion of quality criteria in public bus service contracts in metropolitan areas. Transport Policy. 2015;42:52–63. https://doi.org/10.1016/j.tranpol.2015.05.002.

Tyrinopoulos Y, Antoniou C. Public transit user satisfaction: Variability and policy implications. Transport Policy. 2008;15(4):260–272. https://doi.org/10.1016/j.tranpol.2008.06.002.

Chapter 2

How to Study Perceived Quality in Public Transport

Abstract

This chapter aims to provide an overall view of the birth and development of research into the quality users of public transport perceive they receive from the service. The procedures and manuals developed in the European Union and the United States will be described to support public transport managers and operating companies in accurately assessing their services. The main characteristics and methodological aspects inherent in this concept will also be described along with the principal methods used for evaluating quality being classified in a way that differentiates between aggregate methods and disaggregate methods and, in turn, between those methods based only on user perceptions and those based on their expectations and perceptions together. Brief descriptions will be provided about various methods such as the SERVQUAL model, the SERVPERF model, the IPA model, and the Zones of Tolerance, as well as some of their varieties. Finally, the different methodologies used to obtain the importance users place on each attribute describing their public transport service will be addressed, differentiating between the stated importance method and the derived importance method, highlighting their advantages and disadvantages in each case.

Keywords

Aggregate performance-expectation models; Aggregate satisfaction models; Customer satisfaction survey; Derived importance; Disaggregate models; Heterogeneity; Literature review; Service quality data; Stated importance

Contents

2.1 Introduction

2.2 Background

2.2.1 European Union Recommendations for Analyzing Service Quality

2.2.2 US Recommendations for the Analysis of Service Quality

2.3 Characteristics and Methodological Aspects Relating to Service Quality in Public Transport

2.3.1 Complexity of the Concept of Quality

2.3.2 Service Quality Attributes

2.3.3 Nature of the Data

2.3.4 Surveys

2.3.5 Heterogeneity

2.4 Methodological Approaches for Analyzing Service Quality

2.4.1 Aggregate Models Based on Expectations and Perceptions

2.4.2 Aggregate Models Based on the Perception of Quality or on Satisfaction

2.4.3 Disaggregate Models Based Only on Perceptions

2.4.4 Disaggregate Models of Expectations and Perceptions

2.5 Methodologies to Estimate the Relative Importance of Each Service Quality Attribute

2.5.1 Stated Importance

2.5.2 Derived Importance

2.5.2.1 Bivariate Correlations

2.5.2.2 Regression Analysis

2.5.2.3 Structural Equation Models

2.6 Conclusions

References

2.1. Introduction

Public transport represents a suitable alternative to traveling by private car and has become a hugely important part of sustainable transport policies. As the perceived quality of public transport users is widely recognized to be a determining factor on their behavior, the quality of public transport service being delivered has become one of the main priorities within sustainable transport politics, given that it motivates and encourages travelers to choose modes of transport that are more efficient in their use of space and energy (Cascetta & Carteni, 2014).

The European Union has adopted a user-based quality of service policy that encourages the development of methods, which concentrate on the needs and expectations of passengers. Over recent years, the quality has been seen to become a critical factor for companies that believe they can edge an advantage over their competitors due to their superior quality standards. In

Reviews for Public Transportation Quality of Service

[Qzqwe · Rating: 5 out of 5 stars]

petmalu to itz petmalu to itz petmalu to itz petmalu to itz