The concept of sustainable urban mobility has gained increasing attention in recent years due to the challenges posed by rapid urbanization and environmental degradation. The objective of this study is to explore the role of on-demand transportation in promoting sustainable urban mobility, incorporating insights from customer interests and demands through survey analysis. To fulfill this objective, a mixed-methods approach was employed, combining a systematic literature review with survey analysis of customer interests and demands regarding on-demand transportation services. This study combines a systematic literature review and a targeted survey to provide a comprehensive analysis of sustainable urban mobility, addressing gaps in understanding customer preferences alongside technological and financial considerations. The literature review encompassed various aspects including technological advancements, regulatory frameworks, user preferences, and environmental impacts. The survey analysis involved collecting data on customer preferences, satisfaction levels, and suggestions for improving on-demand transportation services. The findings of the study revealed significant insights into customer interests and demands regarding on-demand transportation services. Analysis of survey data indicated that factors such as convenience, affordability, reliability, and environmental sustainability were key considerations for customers when choosing on-demand transportation options. Additionally, the survey identified specific areas for improvement, including service coverage, accessibility, and integration with existing transportation networks. By providing flexible, efficient, and environmentally friendly transportation options, on-demand services have the potential to reduce congestions, improve air quality, and enhance overall urban livability.

1. Bokolo, A. J. (2020, June). Applying enterprise architecture for digital transformation of electro mobility towards sustainable transportation. In Proceedings of the 2020 on Computers and People Research Conference (pp. 38–46).
2. Bokolo, A. J. (2021). Exploring data driven initiatives for smart city development: empirical evidence from techno-stakeholders’ perspective. Urban Research & Practice, 15(4), 529–560. https://doi.org/10.1080/17535069.2020.1869816
3. Bokolo, A. J. (2023a). Data driven approaches for smart city planning and design: a case scenario on urban data management. Digital Policy, Regulation and Governance, 25(4), 351–367. https://doi.org/10.1108/dprg-03-2022-0023
4. Bokolo, A. J. (2023b). Data enabling digital ecosystem for sustainable shared electric mobility-as-a-service in smart cities-an innovative business model perspective. Research in Transportation Business & Management, 51, 101043. https://doi.org/10.1016/j.rtbm.2023.101043
5. Briner, R. B., and Denyer, D. (2012). Systematic Review and Evidence Synthesis as a Practice and Scholarship Tool. In D. M. Rousseau (Ed.), The Oxford Handbook of Evidence-Based Management (pp. 112–129). Oxford University Press. https://doi.org/10.1093/oxfordhb/9780199763986.013.0007
6. Denyer, D., and Tranfield, D. (2009). Producing a Systematic Review. In D. Buchanan and A. Bryman (Eds.), The SAGE Handbook of Organizational Research Methods (pp. 671–689). SAGE Publications Ltd.
7. future research perspectives. Long range planning, 49(1), 36–54.
8. García, J. R. R., Lenz, G., Haveman, S. P., and Bonnema, G. M. (2019). State of the Art of Mobility as a Service (MAAS) Ecosystems and Architectures—An overview of, and a definition, Ecosystem and System architecture for Electric Mobility as a Service (EMAAS). World Electric Vehicle Journal, 11(1), 7. https://doi.org/10.3390/wevj11010007
9. Georgakis, P., Almohammad, A., Bothos, E., Magoutas, B., Arnaoutaki, K., and Mentzas, G. (2020). Heuristic-Based Journey Planner for Mobility as a Service (MAAS). Sustainability, 12(23), 10140. https://doi.org/10.3390/su122310140
10. Hamel, C., Michaud, A., Thuku, M., Skidmore, B., Stevens, A., Nussbaumer-Streit, B., and Garritty, C. (2021). Defining rapid reviews: a systematic scoping review and thematic analysis of definitions and defining characteristics of rapid reviews. Journal of Clinical Epidemiology, 129, 74–85. https://doi.org/10.1016/j.jclinepi.2020.09.041
11. Khanji, S., and Assaf, S. (2019, June). Boosting ridesharing efficiency through blockchain: Greenride application case study. In 2019 10th International Conference on Information and Communication Systems (ICICS) (pp. 224–229). IEEE.
12. Münzel, K., Boon, W., Frenken, K., Blomme, J., and Van Der Linden, D. (2019). Explaining carsharing supply across Western European cities. International Journal of Sustainable Transportation, 14(4), 243–254. https://doi.org/10.1080/15568318.2018.1542756
13. Orecchini, F., and Santiangeli, A. (2011). Beyond smart grids – The need of intelligent energy networks for a higher global efficiency through energy vectors integration. International Journal of Hydrogen Energy, 36(13), 8126–8133. https://doi.org/10.1016/j.ijhydene.2011.01.160
14. Perätalo, S., Ahokangas, P., and Iivari, M. (2023). Smart city business model approach: the role of opportunities, values, and advantages. Innovation: The European Journal of Social Science Research, 1–25. https://doi.org/10.1080/13511610.2023.2286439
15. Rahman, M. A., Rashid, M., Hossain, M. S., Hassanain, E., Alhamid, M. F., and Guizani, M. (2019). Blockchain and IoT-Based Cognitive Edge framework for sharing economy services in a smart City. IEEE Access, 7, 18611–18621. https://doi.org/10.1109/access.2019.2896065
16. Reynen, E., Robson, R., Ivory, J., Hwee, J., Straus, S. E., Pham, B., and Tricco, A. C. (2018). A retrospective comparison of systematic reviews with same-topic rapid reviews. Journal of Clinical Epidemiology, 96, 23–34. https://doi.org/10.1016/j.jclinepi.2017.12.001
17. Sun, J., Xiao, L., Tian, J., Zhou, H., and Roveda, J. (2016). Surrogating circuit design solutions with robustness metrics. Integration, 52, 1–9. https://doi.org/10.1016/j.vlsi.2015.07.015
18. Tranfield, D., Denyer, D., and Smart, P. (2003). Study on and instrument to assess knowledge supply chain systems using advanced kaizen activity in SMEs. British Journal of Management, 14, 207–222. https://doi.org/10.1080/16258312.2014.11517339
19. Wirtz, B. W., Pistoia, A., Ullrich, S., and Göttel, V. (2016). Business Models: origin, development and future research perspectives. Long Range Planning, 49(1), 36–54. https://doi.org/10.1016/j.lrp.2015.04.001