Article

From Service Quality to Loyalty: Understanding Rail Commuter Satisfaction in Greater Kuala Lumpur

Maryam Kalhoro ORCID , Hui Nee Au Yong ORCID , Charles Ramendran SPR ORCID
    Received
    10 Aug 2025
    Published
    19 Oct 2025

    Abstract

    Rapid urbanization in Greater Kuala Lumpur has intensified automobile dependency, causing congestion and environmental concerns. Although urban rail systems are promoted as sustainable alternatives, their adoption remains limited. This study examines how service quality influences commuter loyalty and whether satisfaction mediates this relationship within Malaysia’s urban rail context (KTM Komuter, LRT, MRT). A structured questionnaire yielded 218 valid responses analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results show that service quality does not directly predict behavioural intention (β = 0.07, t = 0.874, p > 0.05). Instead, commuter satisfaction significantly predicts behavioural intention (β = 0.728, t = 10.338, p < 0.001) and fully mediates the link between service quality and behavioural intention (β = 0.515, t = 8.53, p < 0.001). Enhancing commuter satisfaction is therefore essential to increase rail usage, as improvements in service quality influence behaviour only when they raise satisfaction. Theoretically, the findings integrate the SERVQUAL model with the Theory of Planned Behaviour (TPB); practically, they guide policymakers in strengthening rail services to promote sustainable urban mobility.

    Keywords

    Behavioural Intention, Customer Satisfaction, Greater Kuala Lumpur, PLS-SEM, Service Quality, Urban Rail Transport

    References
    1. [1] Hizam, S.M., Ahmed, W., Akter, H., et al., 2021. Understanding the public rail quality of service towards commuters’ loyalty behavior in Greater Kuala Lumpur. Transportation Research Procedia. 55, 370–377.
    2. [2] Abdulrazzaq, L.R., Abdulkareem, M.N., Mat Yazid, M.R., et al., 2020. Traffic congestion: Shift from private car to public transportation. Civil Engineering Journal. 6(8), 1547–1554.
    3. [3] Mohd Shafie, S.H., Mahmud, M., 2020. Urban air pollutant from motor vehicle emissions in Kuala Lumpur, Malaysia. Aerosol and Air Quality Research. 20(12), 2793–2804.
    4. [4] Klang Valley Integrated Transit Map, 2021. Klang Valley Integrated Transit Map 2020. Roiseku. Available from: https://www.skyscrapercity.com/threads/klang-valley-integrated-transit-maps.1820006/page-18 (cited 28 June 2021).
    5. [5] Ministry of Transport Malaysia, 2022. Vaccinated Travel Lane by Air. Available from: https://www.mot.gov.my/en/aviation/vtl (cited 7 April 2022).
    6. [6] Department of Statistics Malaysia, 2022. Department of Statistics Malaysia Official Portal. Available from: https://www.dosm.gov.my/v1/ (cited 6 April 2022).
    7. [7] Friman, M., Lättman, K., Olsson, L.E., 2020. Public transport quality, safety, and perceived accessibility. Sustainability. 12(9), 3563. DOI: https://doi.org/10.3390/su12093563
    8. [8] Parasuraman, A., Zeithaml, V.A., Berry, L.L., 1985. A conceptual model of service quality and its implications for future research. Journal of Marketing. 49(4), 41–50.
    9. [9] Ngah, R., Putit, L., Mat, A., et al., 2020. Moderating effect of service quality on public transport travel behaviour and antecedents. Planning Malaysia. 18. DOI: https://doi.org/10.21837/pm.v18i14.819
    10. [10] de Oña, J., 2020. The role of involvement with public transport in the relationship between service quality, satisfaction and behavioral intentions. Transportation Research Part A: Policy and Practice. 142, 296–318.
    11. [11] Isai, K.I., Kadiresan, V., Jayabalan, N., et al., 2020. Customer satisfaction and commuter service: An evaluation of intercity Keretapi Tanah Melayu Berhad (KTMB) performance delivery. Malaysian Journal of Social Sciences and Humanities (MJSSH). 5(5), 95–124.
    12. [12] de Oña, J., Estévez, E., de Oña, R., 2021. Public transport users versus private vehicle users: Differences about quality of service, satisfaction and attitudes toward public transport in Madrid (Spain). Travel Behaviour and Society. 23, 76–85.
    13. [13] Dols, J., Alcalá, E., Masiá, J., et al., 2017. Transportation safety requirements in the use of pushchairs on buses. Journal of Traffic and Transportation Engineering. 5(2), 63–76. DOI: https://doi.org/10.17265/2328-2142/2017.02.002
    14. [14] Chen, M., Shen, C.-W., 2020. The correlation analysis between the service quality of intelligent library and the behavioral intention of users. The Electronic Library. 38(1), 95–112.
    15. [15] Nayum, A., Nordfjærn, T., 2021. Predictors of public transport use among university students during the winter: A MIMIC modelling approach. Travel Behaviour and Society. 22, 236–243.
    16. [16] Parasuraman, A., Zeithaml, V.A., Berry, L.L., 1988. SERVQUAL instrument. PsycTESTS Dataset. Available from: https://doi.org/10.1037/t09264-000
    17. [17] Nieuwenhuijsen, M., Khreis, H., 2018. Urban and transport planning, environment and health. In Integrating Human Health into Urban and Transport Planning. Springer: Cham, Switzerland. pp. 3–16.
    18. [18] Mat, A., Bahry, N.S., Kori, N.L., et al., 2019. The influence of service quality and passenger satisfaction towards Electric Train Services (ETS): A PLS-SEM approach. Foundations of Management. 11(1), 57–64.
    19. [19] Ali, W., 2016. An assessment of the passengers’ satisfaction from service quality of onboard employees of Saudi Airlines—an empirical study. Archives of Business Research. 4(1). DOI: https://doi.org/10.14738/abr.41.1830
    20. [20] Esmailpour, J., Aghabayk, K., Abrari Vajari, M., et al., 2020. Importance–performance analysis (IPA) of bus service attributes: A case study in a developing country. Transportation Research Part A: Policy and Practice. 142, 129–150.
    21. [21] Soltanpour, A., Mesbah, M., Habibian, M., 2020. Customer satisfaction in urban rail: A study on transferability of structural equation models. Public Transport. 12(1), 123–146.
    22. [22] Zhang, C., Liu, Y., Lu, W., et al., 2019. Evaluating passenger satisfaction index based on PLS-SEM model: Evidence from Chinese public transport service. Transportation Research Part A: Policy and Practice. 120, 149–164.
    23. [23] Hadiuzzman, M., Das, T., Hasnat, M.M., et al., 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), 257–277.
    24. [24] Momotaz, S.N., 2019. Effects of service quality and perceived value on customer satisfaction to mobile internet service: Evidence from Bangladesh. International Review of Business Research Papers. 15(1), 60–86.
    25. [25] Zeithaml, V.A., Berry, L.L., Parasuraman, A., 1996. The behavioral consequences of service quality. Journal of Marketing. 60(2), 31–46.
    26. [26] Calisir, F., Bayraktaroglu, A.E., Gumussoy, C.A., et al., 2014. Effects of service quality dimensions including usability on perceived overall quality, customer satisfaction, and return intention in different hospital types. International Journal of Advanced Operations Management. 6(4), 518–522.
    27. [27] Grönroos, C., 1978. A service-orientated approach to marketing of services. European Journal of Marketing. 12(8), 588–601.
    28. [28] Yuda Bakti, I.G., Rakhmawati, T., Sumaedi, S., et al., 2020. Public transport users’ WOM: An integration model of the theory of planned behavior, customer satisfaction theory, and personal norm theory. Transportation Research Procedia. 48, 3365–3379.
    29. [29] Buran, B., Demir, E., Sari, H., et al., 2025. Passenger satisfaction modelling in public bus systems: meta-analysis and framework. Case Studies on Transport Policy. Available from: https://trid.trb.org/View/2557067
    30. [30] Hamzah, M.I., Wahab, S.N., Abd Rashid, M.H., et al., 2023. Switching intention, word-of-mouth and quality of public transport services: Kuala Lumpur conurbation. Multimodal Transport. 2(3), 100082.
    31. [31] Ab Karim, S.N., Rahman, M.A., Hassan, N.A., et al., 2025. Service quality attributes affecting satisfaction of KTM Komuter passengers (Klang Valley). Applied Mathematical Modelling and Experiments. 48(1), 131–152.
    32. [32] Ibrahim, A.N.H., Borhan, M.N., Yazid, M.R.M., 2023. Modeling passenger satisfaction and reuse intention with monorail (Kuala Lumpur): hybrid SEM–ANN. Mathematics. 11(15), 3361. DOI: https://doi.org/10.3390/math11153361
    33. [33] Owusu-Agyemang, S., Boateng, F., Mensah, K., et al., 2024. Transit made easy: adoption and impact of transport apps. Case Studies on Transport Policy. 12, 100–114. https://doi.org/10.1016/j.cstp.2024.100114
    34. [34] Henríquez-Jara, B., Morales, P., Soto, L., et al., 2025. Impact of real-time information apps on passenger satisfaction in 13 Chilean cities. Transportation Research Part A: Policy and Practice. 200(C). DOI: https://doi.org/10.1016/j.tra.2025.104622
    35. [35] de Oña, J., de Oña, R., Garrido, C., 2022. Service quality, satisfaction and behavioral intentions in public transport. Transportation. 49(1), 237–269.
    36. [36] Wang, Y., 2025. Examining urban rail transit choice intention. SAGE Open. 15(3), 1–15.
    37. [37] Dou, M., Guo, Q., Ding, C., 2024. How do people perceive the quality of urban transport? Case of Shanghai Metro using UGC. Journal of Urban Management. 13(3), e1000827.
    38. [38] Lv, F., Wu, Q., Ren, H., et al., 2024. Driving further growth of the electric vehicle market in China: Insights from multi-theoretical integration models. Transportation Research Part F: Traffic Psychology and Behaviour. 107, 887–902. DOI: https://doi.org/10.1016/j.trf.2024.10.013
    39. [39] Beck, D., Silva, R., Fernandes, T., et al., 2025. From commute to contentment: Evaluating service quality in Lisbon’s rapid transit system through non-solicited user feedback. Case Studies on Transport Policy. 20, 101460. DOI: https://doi.org/10.1016/j.cstp.2025.101460
    40. [40] Bian, J., Harper, M., Collins, R., et al., 2023. Current practices and trends of transit apps across 295 US agencies. Journal of Transport Geography. 110, 103593.
    41. [41] Flores, L.C., Martinez, A., Khan, S., et al., 2025. Service quality, trust and passenger satisfaction in e-public transport: Doha Metro. World Electric Vehicle Journal. 16(3), 174. DOI: https://doi.org/10.3390/wevj16030174
    42. [42] OECD–ITF, 2024. Fare’s fair: experiences and impacts of fare policies. Policy Paper No.132. International Transport Forum: Paris, France.
    43. [43] Worldline, 2025. Eight trends shaping the future of public transit payments. White Paper. Publisher: Worldline, Belgium.
    44. [44] Visa, 2020. Urban Transportation—The Connection to a Brighter Tomorrow. White Paper. Visa Inc.: Foster City, CA, USA.
    45. [45] Sumaedi, S., Yarmen, M., 2015. Measuring perceived service quality of fast-food restaurant in Islamic country: A conceptual framework. Procedia Food Science. 3, 119–131.
    46. [46] Wang, D., Wang, Y., Zhu, S., et al., 2020. Train rescheduling for minimizing passenger travel time under disruption for metro lines. In Proceedings of the 2020 IEEE 16th International Conference on Control & Automation (ICCA), Singapore, 9–11 October 2020.
    47. [47] Ansory, S.M., Safira, A.S.A., 2018. Age segmentation for predicting behavioural intention of using railway services in Indonesia. Asian Journal of Business and Accounting. 11(1), 229–264.
    48. [48] Belay, D.G., 2020. Assessing risks of urban public transport governance. International Journal of Risk and Contingency Management. 9(2), 19–32.
    49. [49] Kucharčíková, A., Mičiak, M., 2018. Human capital management in transport enterprises with the acceptance of sustainable development in the Slovak Republic. Sustainability. 10(7), 2530.
    50. [50] Lwesya, F., Jaffu, R., 2017. Customer service quality management in public transport: The case of rail transport in Tanzania. International Review. 3–4, 102–117.
    51. [51] Van Oort, N., Cats, O., 2015. Improving public transport decision making, planning and operations by using Big Data: Cases from Sweden and the Netherlands. In Proceedings of the 2015 IEEE 18th International Conference on Intelligent Transportation Systems (ITSC), Canary Islands, Spain, 15–18 September 2015.
    52. [52] Halvorsen, A., Koutsopoulos, H.N., Ma, Z., et al., 2019. Demand management of congested public transport systems: A conceptual framework and application using smart card data. Transportation. 47(5), 2337–2365. DOI: https://doi.org/10.1007/s11116-019-10017-7
    53. [53] La, S.-J., Cho, Y., 2019. Investigating utility, attitude, intention, and satisfaction of skill-sharing economy. Journal of Industrial Distribution & Business. 10(1), 39–49. DOI: https://doi.org/10.13106/jidb.2019.vol10.no1.39
    54. [54] Oliver, N., Delbridge, R., 1991. Beyond customer satisfaction: The changing face of UK car retailing. International Journal of Retail & Distribution Management. 19(3). DOI: https://doi.org/10.1108/EUM0000000002941
    55. [55] Foroudi, P., Cuomo, M.T., Foroudi, M.M., 2019. Continuance interaction intention in retailing. Information Technology & People. 33(4), 1303–1326. DOI: https://doi.org/10.1108/ITP-09-2018-0421
    56. [56] de Oña, J., 2021. Understanding the mediator role of satisfaction in public transport: A cross-country analysis. Transport Policy. 100, 129–149.
    57. [57] Oliver, R.L., 1999. Whence consumer loyalty? Journal of Marketing. 63(4 Suppl 1), 33–44.
    58. [58] Hu, H.-H.S., Kandampully, J., Juwaheer, T.D., 2009. Relationships and impacts of service quality, perceived value, customer satisfaction, and image: An empirical study. The Service Industries Journal. 29(2), 111–125.
    59. [59] Ahmed, S., Choudhury, M.M., Ahmed, E., et al., 2020. Passenger satisfaction and loyalty for app-based ride-sharing services: Through the tunnel of perceived quality and value for money. The TQM Journal. 33(6), 1411–1425.
    60. [60] Nyeck, S., Morales, M., Ladhari, R., et al., 2002. Ten years of service quality measurement: Reviewing the use of the SERVQUAL instrument. Cuadernos de Difusión. 7(13), 101–107.
    61. [61] Sam, E.F., Hamidu, O., Daniels, S., 2018. SERVQUAL analysis of public bus transport services in Kumasi Metropolis, Ghana: Core user perspectives. Case Studies on Transport Policy. 6(1), 25–31.
    62. [62] Jacot, B., Fivet, C., Shope, M., et al., 2017. An optimized bracing system for distributed lateral loads. In Proceedings of the Annual International Conference on Architecture and Civil Engineering (ACE 2017), Singapore, 15–16 May 2017.
    63. [63] Ingvardson, J.B., Nielsen, O.A., 2019. The relationship between norms, satisfaction and public transport use: A comparison across six European cities using structural equation modelling. Transportation Research Part A: Policy and Practice. 126, 37–57. DOI: https://doi.org/10.1016/j.tra.2019.05.016
    64. [64] Wang, Y., Zhang, Z., Zhu, M., et al., 2020. The impact of service quality and customer satisfaction on reuse intention in urban rail transit in Tianjin, China. SAGE Open. 10(1), 21582440198.
    65. [65] Kalhoro, M., Au Yong, H.N., Ramendran, S.P.R., 2021. Understanding the factors affecting pro-environment behavior for city rail transport usage: Territories’ empirical evidence—Malaysia. Sustainability. 13(22), 12483. DOI: https://doi.org/10.3390/su132212483
    66. [66] Sadiku, M.N., Shadare, A.E., Musa, S.M., 2019. Urban computing: A primer. International Journal of Advances in Scientific Research and Engineering. 5(10), 152–156.
    67. [67] Dong, J., Liu, C., Lin, Z., 2014. Charging infrastructure planning for promoting battery electric vehicles: An activity-based approach using multiday travel data. Transportation Research Part C: Emerging Technologies. 38, 44–55. DOI: https://doi.org/10.1016/j.trc.2013.11.001
    68. [68] Quddus, M., Rahman, F., Monsuur, F., et al., 2019. Analyzing bus passengers’ satisfaction in Dhaka using discrete choice models. Transportation Research Record. 2673(2), 758–768. DOI: https://doi.org/10.1177/0361198119825846
    69. [69] Brohi, S.N., Pillai, T.R., Asirvatham, D., et al., 2018. Towards smart cities development: A study of public transport system and traffic-related air pollutants in Malaysia. IOP Conference Series: Earth and Environmental Science. 167, 012015. DOI: https://doi.org/10.1088/1755-1315/167/1/012015
    70. [70] Zhang, W., Jenelius, E., Badia, H., 2019. Efficiency of semi-autonomous and fully autonomous bus services in trunk-and-branches networks. Journal of Advanced Transportation. 2019, 1–17. DOI: https://doi.org/10.1155/2019/7648735
    71. [71] Kalhoro, M., Au Yong, H.N., Ramendran, S.P.R., 2021. Commuter’s age, gender and public transport usage: A literature review. In Proceedings of the 3rd Africa-Asia Dialogue Network (AADN) International Conference on Advances in Business Management and Electronic Commerce Research, Kuala Lumpur, Malaysia, 2021.
    72. [72] Hair, J.F., Risher, J.J., Sarstedt, M., et al., 2019. When to use and how to report the results of PLS-SEM. European Business Review. 31(1), 2–24. DOI: https://doi.org/10.1108/EBR-11-2018-0203
    73. [73] Black, W., Babin, B.J., 2019. Multivariate data analysis: Its approach, evolution, and impact. In The Great Facilitator. Springer: Cham, Switzerland. pp. 121–130.
    74. [74] Fornell, C., Larcker, D.F., 1981. Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research. 18(3), 382–388. DOI: https://doi.org/10.1177/002224378101800313
    75. [75] Bamberg, S., Rölle, D., Weber, C., 2003. Does habitual car use not lead to more resistance to change of travel mode? Transportation. 30(1), 97–108. DOI: https://doi.org/10.1023/A:1021282523910
    76. [76] de Oña, J., de Oña, R., 2022. Is it possible to attract private vehicle users towards public transport? Understanding the key role of service quality, satisfaction and involvement on behavioral intentions. Transportation. 50, 1073–1101.
    77. [77] Alzoubi, H., Alshurideh, M., Kurdi, B.A., et al., 2022. Does BLE technology contribute towards improving marketing strategies, customers’ satisfaction and loyalty? The role of open innovation. International Journal of Data and Network Science. 6(2), 449–460. DOI: https://doi.org/10.5267/j.ijdns.2021.12.009
    78. [78] Machado-León, J.L., de Oña, J., de Oña, R., et al., 2016. Socio-economic and driving experience factors affecting drivers’ perceptions of traffic crash risk. Transportation Research Part F: Traffic Psychology and Behaviour. 37, 41–51.
    79. [79] de Oña, J., de Oña, R., Eboli, L., et al., 2016. Index numbers for monitoring transit service quality. Transportation Research Part A: Policy and Practice. 84, 18–30.
    80. [80] Lai, W.-T., Chen, C.-F., 2011. Behavioral intentions of public transit passengers—The roles of service quality, perceived value, satisfaction and involvement. Transport Policy. 18(2), 318–325. DOI: https://doi.org/10.1016/j.tranpol.2010.09.003
    81. [81] Ahmad Radzi, N.A., 2015. A study on determinants of service quality in e-commerce towards customers’ purchase intention in Malaysia. SSRN Electronic Journal. Available from: https://dx.doi.org/10.2139/ssrn.2698759
    82. [82] Ali, F., 2016. Hotel website quality, perceived flow, customer satisfaction and purchase intention. Journal of Hospitality and Tourism Technology. 7(2), 213–228. DOI: https://doi.org/10.1108/JHTT-02-2016-0010
    83. [83] Goyal, G., Samalia, H.V., Verma, P., 2017. Interpretive structural modeling for integrating quality management in manufacturing and service counterparts. International Journal of Quality & Reliability Management. 34(9), 1568–1591.
    84. [84] Izogo, E.E., 2017. Customer loyalty in telecom service sector: The role of service quality and customer commitment. The TQM Journal. 29(1), 19–36.
    85. [85] Pandit, R., Balyan, D.R., 2011. Measuring service quality in retail banking. Indian Journal of Applied Research. 3(8), 380–381.
    86. [86] Fida, B.A., Ahmed, U., Al-Balushi, Y., et al., 2020. Impact of service quality on customer loyalty and customer satisfaction in Islamic banks in the Sultanate of Oman. SAGE Open. 10(2). DOI: https://doi.org/10.1177/2158244020919517
    87. [87] Munim, Z.H., Noor, T., 2020. Young people’s perceived service quality and environmental performance of hybrid electric bus service. Travel Behaviour and Society. 20, 133–143. DOI: https://doi.org/10.1016/j.tbs.2020.03.003
    88. [88] Fu, X., Juan, Z., 2017. Understanding public transit use behavior: Integration of the theory of planned behavior and the customer satisfaction theory. Transportation. 44(5), 1021–1042. DOI: https://doi.org/10.1007/s11116-016-9692-8
    89. [89] Adamos, G., Nathanail, E., 2022. How attractive are public transport interchanges? A cross comparison of two European terminals. Transactions on Transport Sciences. 13(1), 74–83.
    90. [90] Maghfur, M., Hurriyati, R., Sultan, M.A., 2021. How to improve online shop customer satisfaction through service quality. Dinasti International Journal of Digital Business Management. 2(5), 856–871. DOI: https://doi.org/10.31933/dijdbm.v2i5.974
    91. [91] Slack, N.J., Singh, G., 2020. The effect of service quality on customer satisfaction and loyalty and the mediating role of customer satisfaction. The TQM Journal. 32(3), 543–558. DOI: https://doi.org/10.1108/TQM-07-2019-0187
    92. [92] Soebandhi, S., Wahid, A., Darmawanti, I., 2020. Service quality and store atmosphere on customer satisfaction and repurchase intention. BISMA (Bisnis dan Manajemen). 13(1), 26–36.
    93. [93] Ajzen, I., 1991. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 50(2), 179–211. DOI: https://doi.org/10.1016/0749-5978(91)90020-T
    94. [94] de Oña, J., 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), 605–622. DOI: https://doi.org/10.1287/trsc.2014.0544
    95. [95] Wardhana, A., Syahputra, S., Kartawinata, B.R., 2017. Determinant factors of consumer preferences in Indonesia Airlines Industry. Jurnal Bisnis dan Manajemen. 18(02), 11–20.
    96. [96] Tan, C.-N.-L., Ojo, A.O., Cheah, J.-H., et al., 2019. Measuring the influence of service quality on patient satisfaction in Malaysia. Quality Management Journal. 26(3), 129–143. DOI: https://doi.org/10.1080/10686967.2019.1615852
    97. [97] Akhtar, J., 2011. Determinants of service quality and their relationship with behavioural outcomes: Empirical study of the private commercial banks in Bangladesh. International Journal of Business and Management. 6(11), 146–156. DOI: https://doi.org/10.5539/ijbm.v6n11p146
    98. [98] Donald, I.J., Cooper, S.R., Conchie, S.M., 2014. An extended theory of planned behaviour model of the psychological factors affecting commuters’ transport mode use. Journal of Environmental Psychology. 40, 39–48. DOI: https://doi.org/10.1016/j.jenvp.2014.03.003
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