Smart urban mobility: Economic and social dimensions of sustainable development in times of digitalization

With accelerating urbanization, climate crises, and technological advancement, cities face increasing pressure on mobility systems, positioning digital transformation as a key driver of sustainable and inclusive urban development. This study evaluates various dimensions of the urban mobility system and how they are changing in the context of digitalization. First, we analyzed key digital solutions in city mobility and concluded that they increase the efficiency of transportation systems, reduce operating costs, and support environmental protection. Second, we examined partial operational and economic indicators of urban mobility and demonstrated the need for a comprehensive approach to assessing urban mobility quality. We then reviewed complex indices of city mobility and proposed a composite Index of Urban Mobility Quality, which combines both objective and experiential data, such as average trip time and user dissatisfaction with the transportation system. The practical part consists of two parts: (i) analysis of the relationship between transport inefficiency and key parameters of urban mobility, including travel time, carbon dioxide (CO2) emissions, and fares. The results revealed a strong empirical link between inefficient urban transport, prolonged travel times, and increased CO2 emissions, highlighting critical barriers to sustainable and inclusive mobility; (ii) calculation of the Index of Urban Mobility Quality for 137 cities, identifying those where targeted digital interventions are most urgently needed. The analysis also highlights cities whose experience can serve as benchmarks for smart mobility performance. Overall, the results provide a practical tool for prioritizing investments in transport digitalization and addressing inefficiencies often overlooked in conventional smart city rankings. Ultimately, the study contributes to bridging the persistent gap between technology-centric models of smart cities and citizen-centric approaches to mobility.
Acumen Research and Consulting. (2024). AI in Mobility Market Size to Reach USD 53.75 Billion by 2033. Available from: https://www.acumenresearchandconsulting.com/ press/releases/ai-in-mobility-market [Last accessed on 2025 Jul 01].
Albouq, S. S., Abi Sen, A. A., Almashfi, N., & Yamin, M. (2022). A survey of interoperability challenges and solutions for dealing with them in IoT environment. IEEE Access, 10:36416-36428. https://doi.org/10.1109/ACCESS.2022.3162219
Arenkov, I., Tsenzharik, M., & Vetrova, M. (2019). Digital technologies in supply chain management. In: Proceedings of the International Conference on Digital Technologies in Logistics and Infrastructure (ICDTLI 2019). France: Atlantis Press; p. 448-453. https://doi.org/10.2991/icdtli-19.2019.78
Ashwini, B., Savithramma, R., & Sumathi, R. (2022). Artificial intelligence in smart city applications: An overview. In: Proceedings of the Sixth International Conference on Intelligent Computing and Control Systems (ICICCS 2022). United States: IEEE; p. 986-993. https://doi.org/10.1109/ICICCS53718.2022.9788152
Baghersad, M., Gumus, G., Huang, C.D., & Behara, R. S. (2024). Regional policy coordination of pandemic responses using an iterative mobility-driven algorithm. Regional Studies, 58(2):393-408. https://doi.org/10.1080/00343404.2023.2220749
Balawi, M., & Tenekeci, G. (2024). Time series traffic collision analysis of London hotspots: Patterns, predictions and prevention strategies. Heliyon, 10:e25710. https://doi.org/10.1016/j.heliyon.2024.e25710
Boston Consulting Group (BCG). (2024). Moving Millions: Transforming Urban Mobility. Available from: https://www. bcg.com/publications/2024/transforming-urban-mobility [Last accessed on 2025 Jun 01].
Beijing Municipal Commission of Transport. (2024). Beijing Releases MaaS2.0 Work Plan: Beijing MaaS Moves to the 2.0 Stage. Available from: https://jtw.beijing.gov.cn/xxgk/ dtxx/202306/t20230629_3150511.html [Last accessed on 2025 Jan 02].
Bibri, S. E., Alexandre, A., Sharifi, A., & Krogstie, J. (2023). Environmentally sustainable smart cities and their converging AI, IoT, and big data technologies and solutions: An integrated approach to an extensive literature review. Energy Informatics, 6(9):9. https://doi.org/10.1186/s42162-023-00259-2
Brandajs, F., & Russo, A. P. (2023). Smarter city, less just destination? Mobilities and social gaps in Barcelona. Journal of Place Management and Development, 16(2):293-308. https://doi.org/10.1108/JPMD-03-2022-0020
Bunders, D. J., & Varró, K. (2019). Problematizing data-driven urban practices: Insights from five Dutch ‘smart cities. Cities, 93:145-152. https://doi.org/10.1016/j.cities.2019.05.004
Carbon Neutral Cities Alliance. (2024). Copenhagen, Denmark. Available from: https://carbonneutralcities.org/cities/ copenhagen [Last accessed on 2024 Dec 20].
Cattaneo, A., Adukia, A., Brown, D. L., Christiaensen, L., Evans, D. K., Haakenstad, A., et al. (2022). Economic and social development along the urban-rural continuum: New opportunities to inform policy. World Development, 157:105941. https://doi.org/10.1016/j.worlddev.2022.105941
Cervicorn Consulting. (2024). AI in Mobility Market Size, Share, Growth, Trends 2024-2033. Available from: https://www. cervicornconsulting.com/artificial-intelligence-in-mobility-market [Last accessed on 2025 Jan 08].
Chi, S., & Mazzer, S. (2022). Identifying MaaS schemes that maximise economic benefits through an economic appraisal. European Journal of Transport and Infrastructure Research, 22:1-24. https://doi.org/10.18757/ejtir.2022.22.4.6379
Country Cassette. (2024). Average Monthly Salary by Country 2024 (After Tax). Available from: https://countrycassette.com/average-monthly-salary-by-country-2023 [Last accessed on 2025 Jan 04].
Del Rio, M., Hargrove, W.L., Tomaka, J., & Korc, M. (2017). Transportation matters: A health impact assessment in rural New Mexico. International Journal of Environmental Research and Public Health, 14(6):629. https://doi.org/10.3390/ijerph14060629
Delaere, H., Basu, S., Macharis, C., & Keseru, I. (2024). Barriers and opportunities for developing, implementing and operating inclusive digital mobility services. European Transport Research Review, 16:67. https://doi.org/10.1186/s12544-024-00684-8
Deloitte. (2021). City Operations Through AI. Available from: https://www.deloitte.com/gh/en/Industries/government/public/perspectives/urban/future/with/a/purpose/city-operations-throuh-ai.html [Last accessed on 2025 Jun 03].
Elassy, M., Al-Hattab, M., Takruri, M., & Badawi, S. (2024). Intelligent transportation systems for sustainable smart cities. Transportation Engineering, 16:100252. https://doi.org/10.1016/j.treng.2024.100252
Eurocities. (2023). Sustainable Urban Mobility Indicator. Available from: https://eurocities.eu/projects/sustainable-urban-mobility-indicators [Last accessed on 2025 Jul 10].
Faliagka, E., Christopoulou, E., Ringas, D., Politi, T., Kostis, N., Leonardos, D., et al. (2024). Trends in digital twin framework architectures for smart cities: A case study in smart mobility. Sensors (Basel), 24(5):1665. https://doi.org/10.3390/s24051665
Gössling, S. (2013). Urban transport transitions: Copenhagen, city of cyclists. Journal of Transport Geography, 33:196-206. https://doi.org/10.1016/j.jtrangeo.2013.10.013
Guo, X., & Guo, X. (2023). A research on blockchain technology: Urban intelligent transportation systems in developing countries. IEEE Access, 11:40724-40740. https://doi.org/10.1109/ACCESS.2023.3270100
Hämäläinen, M. (2020). A framework for a smart city design: Digital transformation in the Helsinki smart city. In: Entrepreneurship and the Community. Berlin: Springer; p. 63-86. https://doi.org/10.1007/978-3-030-23604-5_5
Huawei. (2021). Intelligent Twins: A Bridge to All-Scenario Intelligence. Available from: https://www-file.huawei. com/-/media/corp2020/pdf/publications/communicate/ comm91-en2.pdf [Last accessed on 2024 Dec 25].
INRIX. (2025). Global Traffic Scorecard 2024. Available from: https://inrix.com/scorecard [Last accessed on 2025 Jan 05].
ISO. (2024). Intelligent Transportation Systems: Transforming Modern Mobility. Available from: https://www.iso.org/ transport/its-intelligent-transportation-systems [Last accessed on 2025 Jun 06].
Kolotouchkina, O., Ripoll, L., & Belabas, W. (2024). Smart cities, digital inequalities, and the challenge of inclusion. Smart Cities, 7(6):3355-3370. https://doi.org/10.3390/smartcities7060130
McKinsey. (2023). Solutions for Smart Mobility in Urban Areas. Available from: https://www.mckinsey.com/industries/infrastructure/our/insights/infrastructure/technologies/ challenges-and-solutions-for-smart-mobility-in-urban-areas [Last accessed on 2025 Jun 03].
Medium. (2024). Driving the Future: How AI is Powering Singapore’s Smart City Vision for 2030. Available from: https://medium.com/@dirsyamuddin29/driving/the/future/how/ai/is/ powering-singapores-smart-city-vision-for-2030-7d371db705fd [Last accessed on 2025 Jan 15].
Mihalj, T., Li, H., Babic, D., Lex, C., Jeudy, M., Zovak, G., et al. (2022). Road infrastructure challenges faced by automated driving: A review. Applied Sciences, 12:3477 https://doi.org/10.3390/app12073477
Moghayedi, A., & Awuzie, B. O. (2023). Towards a net-zero carbon economy: A sustainability performance assessment of innovative prefabricated construction methods for affordable housing in Southern Africa. Sustainable Cities and Society, 99:104907. https://doi.org/10.1016/j.scs.2023.104907
Netov, N., & Lomev B. (2022). Impact of digitalization of public transport and city mobility on traffic structure and on-road emissions. In: 2022 6th European Conference on Electrical Engineering & Computer Science (ELECS). United States: IEEE; p. IO71-IO74. https://doi.org/10.1109/ELECS55825.2022.00019
Numbeo. (2025). Traffic Index by City 2025. Available from: https://www.numbeo.com/traffic/rankings.jsp [Last accessed on 2025 Jan 20].
Odeck, J., & Welde, M. (2010). Economic evaluation of intelligent transportation systems strategies: The case of the Oslo toll cordon. IET Intelligent Transport Systems, 4:221-228. https://doi.org/10.1049/iet-its.2010.0027
OliverWymanForum. (2024). Urban Mobility Readiness Index. Available from: https://www.oliverwymanforum.com/ mobility/urban-mobility-readiness-index/about.html [Last accessed on 2025 Jul 10].
Rahman, M., Polunsky, S., & Jones, S. (2022). Transportation policies for connected and automated mobility in smart cities. In: Smart Cities Policies and Financing: Approaches and Solutions. Netherlands: Elsevier Science; p. 97-116. https://doi.org/10.1016/B978-0-12-819130-9.00008-5
Richter, M. A., Hagenmaier, M., Bandte, O., Parida, V., & Wincent, J. (2022). Smart cities, urban mobility and autonomous vehicles: How different cities need different sustainable investment strategies. Technological Forecasting and Social Change, 184:121857. https://doi.org/10.1016/j.techfore.2022.121857
Rodrigues, M., & Franco, M. (2019). Measuring cities’ performance: Proposal of a Composite Index for the intelligence dimension. Measurement, 139:112-121. https://doi.org/10.1016/j.measurement.2019.03.008
Sochor, J., Arby, H., Karlsson, I. C. M., & Sarasini, S. (2018). A topological approach to mobility as a service: A proposed tool for understanding requirements and effects, and for aiding the integration of societal goals. Research in Transportation Business and Management, 27:3-14. https://doi.org/10.1016/j.rtbm.2018.12.003
Tomadon, L., Do Couto, E., De Vries, W., & Moretto, Y. (2024). Smart city and sustainability indicators: A bibliometric literature review. Discover Sustainability, 5(1):1-21. https://doi.org/10.1007/s43621-024-00328-w
UITP. (2021). Urban Mobility Innovation Index 2021. Available from: https://www.uitp.org/publications/urban-mobility-innovation-index-2021 [Last accessed on 2025 Jul 10].
UITP. (2022). Global Urban Mobility Indicators 2022. Available from: https://www.uitp.org/publications/global-urban-mobility-indicators-2022 [Last accessed on 2025 Jul 10].
United Nations. (2024). World Population Prospects 2024. Available from: https://population.un.org/wpp [Last accessed on 2024 Dec 25].
UN.ESCAP. (2017). Assessment of Urban Transport Systems. Available from: https://repository.unescap.org/items/ ee3020d0-3f5e-4a93-b979-f52c57c47f36 [Last accessed on 2025 Jul 10].
Velasco, A., & Gerike, R. (2024). A composite index for the evaluation of sustainability in Latin American public transport systems. Transportation Research Part A: Policy and Practice, 179:103939. https://doi.org/10.1016/j.tra.2023.103939
Wolniak, R., & Stecuła, K. (2024). Artificial intelligence in smart cities - applications, barriers, and future directions: A review. Smart Cities, 7:1346-1389. https://doi.org/10.3390/smartcities7030057
Yusuf, J. A. (2024). Economic evaluation of smart traffic management systems in reducing carbon emissions. Journal of Economics, Business, and Commerce, 1(1):30-35. https://doi.org/10.69739/jebc.v1i1.82
Zhao, X., Andruetto, C., Vaddadi, B., & Pernestål, A. (2021). Potential values of MaaS impacts in future scenarios. Journal of Urban Mobility, 1:100005. https://doi.org/10.1016/j.urbmob.2021.100005