A Review of Methodological Approaches and Modeling Techniques in Service Quality Evaluation of Surface Transportation during the Last Decade

Authors

  • Nayeem Islam Department of Civil Engineering, Bangabandhu Sheikh Mujibur Rahman Science & Technology University, Gopalganj-8100, Bangladesh

DOI:

https://doi.org/10.38032/jea.2021.04.005

Keywords:

Service Quality, Surface Transportation, Stated Importance, Neural Networks, Decision Trees, SEM

Abstract

During the duration of the last decade, a growing interest has been noticed among transport practitioners and researchers to better understand the concept of service quality in the field of surface transportation and identify important service quality (SQ) attributes of different transportation services since these results have implications for transport managers. Due to advancements in computer technology and the availability of software packages, researchers are better able to extract meaningful results from passengers’ opinions collected through stated preference surveys and communicate their findings to transport managers looking to ameliorate SQ to boost ridership on a limited budget. Since the concept of SQ is itself complex owing to the nature of the service itself compared to a tangible product and characteristics of SQ attribute, different advanced modelling techniques based on multivariate analysis, machine learning, and artificial intelligence paradigms have become popular tools among researchers. This paper aims to summarize the trends of the SQ research in the field of surface transportation during the last decade with a focus on the methodological approaches and modelling techniques and delineate future directions for research in this field.

References

Cavana, R. Y., Corbett, L. M., & Lo, Y. G., 2007. Developing zones of tolerance for managing passenger rail service quality. International Journal of Quality & Reliability Management. 24(1), pp.7-31. DOI: https://doi.org/10.1108/02656710710720303

Nathanail, E., 2008. Measuring the quality of service for passengers on the Hellenic railways. Transportation Research Part A: Policy and Practice, 42(1), pp.48-66. DOI: https://doi.org/10.1016/j.tra.2007.06.006

Carman, J.M., 1990. Consumer perceptions of service quality: an assessment of T. Journal of Retailing, 66(1), p.33.

Parasuraman, A., Zeithaml, V.A. and Berry, L.L., 1985. A conceptual model of service quality and its implications for future research. Journal of Marketing, 49(4), pp.41-50. DOI: https://doi.org/10.1177/002224298504900403

Parasuraman, A., Zeithaml, V.A. and Berry, L., 1988. SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), pp.12-40.

UNE-EN 13816, 2003. Transportation. Logistics and Services. Public Passenger Transport.Service Quality Definition, Targeting and Measurement, AENOR, Madrid.

Kittelson & Associates, United States. Federal Transit Administration, Transit Cooperative Research Program and Transit Development Corporation, 2003. Transit capacity and quality of service manual (Vol. 42). Transportation Research Board.

Eboli, L. and Mazzulla, G., 2008. Willingness-to-pay of public transport users for improvement in service quality. European Transport Trasporti Europei, 38, pp.107-118.

Deb, S. and Ahmed, M.A., 2018. Determining the service quality of the city bus service based on users’ perceptions and expectations. Travel Behaviour and Society, 12, pp.1-10. DOI: https://doi.org/10.1016/j.tbs.2018.02.008

Das, S. and Pandit, D., 2015. Determination of level-of-service scale values for quantitative bus transit service attributes based on user perception. Transportmetrica A: Transport Science, 11(1), pp.1-21. DOI: https://doi.org/10.1080/23249935.2014.910563

Basu, D. and Hunt, J.D., 2012. Valuing of attributes influencing the attractiveness of suburban train service in Mumbai city: A stated preference approach. Transportation Research Part A: Policy and Practice, 46(9), pp.1465-1476. DOI: https://doi.org/10.1016/j.tra.2012.05.010

Bordagaray, M., dell'Olio, L., Ibeas, A. and Cecín, P., 2014. Modelling user perception of bus transit quality considering user and service heterogeneity. Transportmetrica A: Transport Science, 10(8), pp.705-721. DOI: https://doi.org/10.1080/23249935.2013.823579

de Oña, R. and de Oña, J., 2015. Analysis of transit quality of service through segmentation and classification tree techniques. Transportmetrica A: Transport Science, 11(5), pp.365-387. DOI: https://doi.org/10.1080/23249935.2014.1003111

De Ona, J., de Oña, R., Eboli, L. and Mazzulla, G., 2015. Heterogeneity in perceptions of service quality among groups of railway passengers. International Journal of Sustainable Transportation, 9(8), pp.612-626. DOI: https://doi.org/10.1080/15568318.2013.849318

De Oña, R. and De Oña, J., 2013. Analyzing transit service quality evolution using decision trees and gender segmentation. WIT transactions on the built environment, 130, pp.611-621. DOI: https://doi.org/10.2495/UT130491

Hadiuzzaman, M., Farazi, N.P., Hossain, S. and Malik, D.G., 2019. An exploratory analysis of observed and latent variables affecting intercity train service quality in developing countries. Transportation, 46(4), pp.1447-1466. DOI: https://doi.org/10.1007/s11116-017-9843-6

de Oña, J., de Oña, R. and López, G., 2016. Transit service quality analysis using cluster analysis and decision trees: a step forward to personalized marketing in public transportation. Transportation, 43(5), pp.725-747. DOI: https://doi.org/10.1007/s11116-015-9615-0

Das, S. and Pandit, D., 2012. Methodology to identify the gaps in the level of service provided for urban bus transit: Case study Kolkata. Spandrel, 4(Spring), pp.59-71.

Thomas, L.J., Rhind, D.J. and Robinson, K.J., 2006. Rail passenger perceptions of risk and safety and priorities for improvement. Cognition, Technology & Work, 8(1), pp.67-75. DOI: https://doi.org/10.1007/s10111-005-0021-9

Machado-León, J.L., de Oña, R., Baouni, T. and de Oña, J., 2017. Railway transit services in Algiers: priority improvement actions based on users perceptions. Transport Policy, 53, pp.175-185. DOI: https://doi.org/10.1016/j.tranpol.2016.10.004

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

Hadiuzzaman, M., Malik, D.G., Barua, S., Qiu, T.Z. and Kim, A., 2019. Modeling passengers’ perceptions of intercity train service quality for regular and special days. Public Transport, 11(3), pp.549-576. DOI: https://doi.org/10.1007/s12469-019-00213-0

Hadiuzzman, M., Das, T., Hasnat, M.M., Hossain, S. and Rafee Musabbir, S., 2017. Structural equation modeling of user satisfaction of bus transit service quality based on stated preferences and latent variables. Transportation Planning and Technology, 40(3), pp.257-277. DOI: https://doi.org/10.1080/03081060.2017.1283155

Islam, R., Musabbir, S.R., Ahmed, I.U., Hadiuzzaman, M., Hasnat, M. and Hossain, S., 2016. Bus service quality prediction and attribute ranking using probabilistic neural network and adaptive neuro fuzzy inference system. Canadian Journal of Civil Engineering, 43(9), pp.822-829. DOI: https://doi.org/10.1139/cjce-2016-0119

Islam, M.R., Hadiuzzaman, M., Banik, R., Hasnat, M.M., Musabbir, S.R. and Hossain, S., 2016. Bus service quality prediction and attribute ranking: a neural network approach. Public transport, 8(2), pp.295-313. DOI: https://doi.org/10.1007/s12469-016-0124-0

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

Pakdil, F. and Kurtulmusoglu, F.B., 2014. Improving service quality in highway passenger transportation: a case study using quality function deployment. EJTIR, 14(4), pp.375-393.

Kurtulmuşoğlu, F.B., Pakdil, F. and Atalay, K.D., 2016. Quality improvement strategies of highway bus service based on a fuzzy quality function deployment approach. Transportmetrica A: Transport Science, 12(2), pp.175-202. DOI: https://doi.org/10.1080/23249935.2015.1117535

De Vaus, D., & de Vaus, D. (2013). Surveys In Social Research (6th ed.). Routledge. DOI: https://doi.org/10.4324/9780203519196

Johnson, R.A. and Wichern, D.W., 2014. Applied multivariate statistical analysis (Vol. 6). London, UK:: Pearson.

Mahmoud, M. and Hine, J., 2016. Measuring the influence of bus service quality on the perception of users. Transportation Planning and Technology, 39(3), pp.284-299. DOI: https://doi.org/10.1080/03081060.2016.1142224

Kotrlik, J.W.K.J.W. and Higgins, C.C.H.C.C., 2001. Organizational research: Determining appropriate sample size in survey research appropriate sample size in survey research. Information Technology, Learning, and Performance Journal, 19(1), p.43-50.

Jomnonkwao, S. and Ratanavaraha, V., 2016. Measurement modelling of the perceived service quality of a sightseeing bus service: An application of hierarchical confirmatory factor analysis. Transport Policy, 45, pp.240-252. DOI: https://doi.org/10.1016/j.tranpol.2015.04.001

Stevens, J., 1966. Applied Multivariate Statistics for the Social Sciences. Lawrence Erlbaum Associates, NJ.

De Oña, R., Eboli, L. and Mazzulla, G., 2014. Key factors affecting rail service quality in the Northern Italy: a decision tree approach. Transport, 29(1), pp.75-83. DOI: https://doi.org/10.3846/16484142.2014.898216

de Oña, J., de Oña, R. and Garrido, C., 2017. Extraction of attribute importance from satisfaction surveys with data mining techniques: a comparison between neural networks and decision trees. Transportation Letters, 9(1), pp.39-48. DOI: https://doi.org/10.1080/19427867.2015.1136917

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

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

Yilmaz, V. and Ari, E., 2017. The effects of service quality, image, and customer satisfaction on customer complaints and loyalty in high-speed rail service in Turkey: a proposal of the structural equation model. Transportmetrica A: Transport Science, 13(1), pp.67-90. DOI: https://doi.org/10.1080/23249935.2016.1209255

Machado-León, J.L., de Oña, R. and de Oña, J., 2016. The role of involvement in regards to public transit riders' perceptions of the service. Transport Policy, 48, pp.34-44. DOI: https://doi.org/10.1016/j.tranpol.2016.02.014

Cheng, X., Cao, Y., Huang, K. and Wang, Y., 2018. Modeling the satisfaction of bus traffic transfer service quality at a high-speed railway station. Journal of Advanced Transportation, 2018. DOI: https://doi.org/10.1155/2018/7051789

Hu, X., Zhao, L. and Wang, W., 2015. Impact of perceptions of bus service performance on mode choice preference. Advances in Mechanical Engineering, 7(3), p.1687814015573826. DOI: https://doi.org/10.1177/1687814015573826

Jen, W., Tu, R. and Lu, T., 2011. Managing passenger behavioral intention: an integrated framework for service quality, satisfaction, perceived value, and switching barriers. Transportation, 38(2), pp.321-342. DOI: https://doi.org/10.1007/s11116-010-9306-9

Joewono, T.B., Tarigan, A.K. and Susilo, Y.O., 2016. Road-based public transportation in urban areas of Indonesia: what policies do users expect to improve the service quality?. Transport policy, 49, pp.114-124. DOI: https://doi.org/10.1016/j.tranpol.2016.04.009

Nwachukwu, A.A., 2014. Assessment of passenger satisfaction with intra-city public bus transport services in Abuja, Nigeria. Journal of Public Transportation, 17(1), pp.99-119. DOI: https://doi.org/10.5038/2375-0901.17.1.5

Rojo, M., Gonzalo-Orden, H., dell'Olio, L. and Ibeas, A., 2011, February. Modelling gender perception of quality in interurban bus services. In Proceedings of the Institution of Civil Engineers-Transport (Vol. 164, No. 1, pp. 43-53). Thomas Telford Ltd. DOI: https://doi.org/10.1680/tran.9.00031

Rojo, M., dell'Olio, L., Gonzalo-Orden, H. and Ibeas, Á., 2013. Interurban bus service quality from the users' viewpoint. Transportation Planning and Technology, 36(7), pp.599-616. DOI: https://doi.org/10.1080/03081060.2013.845432

Dell’Olio, L., Ibeas, A. and Cecin, P., 2011. The quality of service desired by public transport users. Transport Policy, 18(1), pp.217-227. DOI: https://doi.org/10.1016/j.tranpol.2010.08.005

Rojo, M., Gonzalo-Orden, H., dell’Olio, L. and Ibeas, Á., 2012. Relationship between service quality and demand for inter-urban buses. Transportation Research Part A: Policy and Practice, 46(10), pp.1716-1729. DOI: https://doi.org/10.1016/j.tra.2012.07.006

Weinstein, A., 2000. Customer satisfaction among transit riders: How customers rank the relative importance of various service attributes. Transportation Research Record, 1735(1), pp.123-132. DOI: https://doi.org/10.3141/1735-15

Downloads

Published

18-12-2021
  • Abstract view28

How to Cite

Islam, N. (2021). A Review of Methodological Approaches and Modeling Techniques in Service Quality Evaluation of Surface Transportation during the Last Decade. Journal of Engineering Advancements, 2(04), 197–202. https://doi.org/10.38032/jea.2021.04.005

Issue

Section

Review Articles