Users’ Mobility Well Being in The Context of Public Transportation Services
Abstract
Mobility well-being is increasingly recognised as an important element in evaluating urban public transportation systems, particularly in ensuring equitable, safe and liveable access to social and economic opportunities. In the context of Kota Kinabalu City, issues related to the quality of public transportation services continue to affect users’ mobility well-being despite various infrastructure improvements implemented since the city achieved city status. Weaknesses in terms of accessibility, fare, facilities, safety and information technology have reduced users’ dependence on public transportation and encouraged the use of private vehicles. Therefore, this study aims to examine the relationship between users’ needs for public transportation services and mobility well-being, with emphasis on the mobility needs that remain insufficiently addressed by the existing public transportation system. The study adopts a fully quantitative approach. Data were collected through the distribution of questionnaires to public transportation users in Kota Kinabalu City and analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that the dimensions of accessibility, fare and technology have significant relationships with users’ mobility wellbeing. In contrast, the dimensions of facilities and safety were found to have no significant relationship with mobility well-being. These findings indicate that accessibility, fare and technology are important elements that should be prioritised in improving the mobility wellbeing of public transportation users in Kota Kinabalu City. This study contributes to the development of the mobility well-being concept within the context of developing cities by highlighting users’ mobility needs that remain unmet by the existing public transportation system, while also providing practical implications for authorities and transportation planners in strengthening urban mobility well-being.
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References
Abdul Ghapar Othman & Kausar hj. Ali. (2025). Transportation and quality of life. Planning Malaysia. Journal of the Malaysian Institute of Planners. https://doi.org/10.21837/pm.v18i13.774
Azizul Mohd Ladin, Besar, S. N. B. A., Harith, N. S. H., Bolong, N., Saad, I., & Taha, N. (2020). Pilot study for the modelling of congestion pricing in Kota Kinabalu, Sabah. MATTER: International Journal of Science and Technology, 6(1). https://doi.org/10.20319/mijst.2020.61.3344
Binder, F., Glas, A. H., & Eßig, M. (2025, June). Life cycle costs: A guide to preparing and executing contracts. Contract Management. https://ncmahq.org/Web/Shared_Content/CM-Magazine/CM-Magazine-June-2025/Life-Cycle-Costs--A-Guide-to-Preparing-and-Executing-Contracts.aspx
De Vos, J., Schwanen, T., Van Acker, V., & Witlox, F. (2013). Travel and subjective well-being: A focus on findings, methods and future research needs. Transport Reviews, 33(4), 421-442. https://doi.org/10.1080/01441647.2013.815665
Delbosc, A., & Currie, G. (2011). The spatial context of transport disadvantage, social exclusion and well-being. Journal of Transport Geography, 19(6), 1130-1137. https://doi.org/10.1016/j.jtrangeo.2011.04.005
Diener, E. (1984). Subjective well-being. Psychological Bulletin, 95(3), 542–575. https://doi.org/10.1037/0033-2909.95.3.542
Diener, E., Lucas, R. E., & Oishi, S. (2018). Advances and open questions in the science of subjective well-being. Collabra: Psychology, 4(1), 15. https://doi.org/10.1525/collabra.115
Eboli, L., & Mazzulla, G. (2011). Performance indicators for an objective measure of public transport service quality. European Transport Research Review, 3, 69–79. https://ideas.repec.org/a/sot/journl/y2012i51p4.html
Elsamani, Y., & Kajikawa, Y. (2024). Envisioning the Future of Mobility: A Well-Being-Oriented Approach. Sustainability, 16(18), 8114. https://doi.org/10.3390/su16188114
Fornell, C. R., & Lacker, D. F. (1981). Two structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Geurs, K. T., & van Wee, B. (2004). Accessibility evaluation of land-use and transport strategies: Review and research directions. Journal of Transport Geography, 12, 127–140. https://doi.org/10.1016/j.jtrangeo.2003.10.005
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European business review, 31(1), 2-24. https://doi.org/10.1108/EBR-11-2018-0203
Henseler, J., Hubona, G., & Ray, P. A. (2016). Using PLS path modeling in new technology research: updated guidelines. Industrial management & data systems, 116(1), 2-20. https://doi.org/10.1108/IMDS-09-2015-0382
Hossan, D., Aktar, A., & Zhang, Q. (2020). A study on partial least squares structural equation modeling (PLS-SEM) as emerging tool in action research. LC International Journal of STEM, 1(4), 130-146. DOI: https://doi.org/10.47150
Ibrahim, A. N. H., Borhan, M. N., Yusoff, S., & Ismail, A. (2020). Evaluating comfort and information quality in public transport systems. Promet. Traffic & Transportation, 32(4), 453–464. https://doi.org/10.7307/ptt.v32i4.3352
Litman, T. (2020). Evaluating public transit benefits and costs: Best practices guidebook (3rd ed.). Victoria Transport Policy Institute. https://www.vtpi.org/tranben.pdf
Nathanail, E. (2008). Measuring the quality of service for passengers on the Hellenic railways. Transportation Research Part A, 42, 48–66. https://doi.org/10.1016/j.tra.2007.06.006
Rainieri, G., Carra, M., Richiedei, A., & Pezzagno, M. (2024). Evaluating active mobility: Enhancing the framework for social sustainability. TeMA-Journal of Land Use, Mobility and Environment, 113-128. https://doi.org/10.6093/1970-9870/10912
Sarma, H. D., Teixeira, R., Sangeeta, S., Martinez-Pastor, B., & McHenry, H. (2025). An overview of the capability approach in wellbeing-focused transport network criticality assessment. Transportation Research Interdisciplinary Perspectives, 31, 101443. https://doi.org/10.1016/j.trip.2025.101443
Sivilevičius, H., & Žuraulis, V. (2025). Modeling the impact of interaction factors for transport system elements on quality of life using multi-criteria decision-making and applied statistical methods. Sustainability, 17(5), Article 1784. https://doi.org/10.3390/su17051784
Stanley, J., Hensher, D., & Currie, G. (2011). Social exclusion and public transport: Investigating the links. Transport Policy, 18(6), 876–884. https://doi.org/10.1016/j.tranpol.2011.06.003
Sugito, E., Mohamad, D., & Roosli, R. (2025). Evaluating urban public bus transport service quality. Planning Malaysia Journal. https://doi.org/10.21837/pm.v23i36.1711
Tyrinopoulos, Y., & Antoniou, C. (2008). Public transit user satisfaction: Variability and policy implications. Transport Policy, 15(4), 260–272. https://doi.org/10.1016/j.tranpol.2008.06.002
van Burgsteden, M., Grigolon, A., & Geurs, K. (2024). Improving community wellbeing through transport policy: A literature review and theoretical framework, based on the Capability Approach. Transport Reviews, 44(6), 1161–1186. https://doi.org/10.1080/01441647.2024.2374818
Watson, D., Clark, L. A., & Tellegen, A. (1988). Development and validation of brief measures of positive and negative affect: the PANAS scales. Journal of personality and social psychology, 54(6), 1063. https://doi.org/10.1037/0022-3514.54.6.1063
