Mobility-as-a-service: literature and tools review with a focus on personalization
Abstract
In the coming years, mobility initiatives should focus on sustainability, safety, and social equity. This can be achieved by introducing innovative transportation methods, implementing novel approaches for end-users, and optimizing the utilization of traditional modes of transport. To achieve this goal, it is essential to utilize pervasive sensing and computing technologies, along with intelligent information processing systems, to assist decision makers, managers, and transport operators. To effectively address unforeseen events and disruptions, mobility services should promptly adapt and improve their flexibility. Furthermore, these services should be adaptable to meet the unique needs and evolving demands of individuals. Current research focuses on understanding how individuals make decisions about when and where they engage in walking, driving, and travel activities. Therefore, it is important to develop reliable human mobility models in this context. Big data and Artificial Intelligence (AI) are important in this context as they enable data generators to identify individual patterns and quickly adapt solutions. This paper aims to conduct a literature review on Mobility-as-a-Service (MaaS), focusing on personalization, to identify gaps in current MaaS initiatives. This assessment is essential for creating inclusive, user-friendly, personalized, and customizable MaaS solutions. To conclude, the existing challenges have been addressed in comprehending the characteristics of MaaS in terms of personalization. Additionally, they have been proposed further research questions to delve deeper into this aspect.
First published online 26 February 2024
Keyword : mobility service, literature review, taxonomy, integration level, tools, personalization, human mobility data, gaps
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
Arnaoutaki, K.; Magoutas, B.; Bothos, E.; Mentzas, G. 2019. A hybrid knowledge-based recommender for mobility-as-a-service, in Proceedings of the 16th International Joint Conference on e-Business and Telecommunications, 26–28 July 2019, Prague, Czech Republic, 1: 95–103. https://doi.org/10.5220/0007921400950103
Banerjee, I.; Jittrapirom, P.; Dangschat, J. S. 2021. Data-driven urbanism, digital platforms, and the planning of MaaS in times of deep uncertainty: what does it mean for CAVs?, in M. Mitteregger, E. M. Bruck, A. Soteropoulos, A. Stickler, M. Berger, J. S. Dangschat, R. Scheuvens, I. Banerjee (Eds.). AVENUE21. Politische und planerische Aspekte der automatisierten Mobilität, 441–470. https://doi.org/10.1007/978-3-662-63354-0_20
Blom, J. 2000. Personalization: a taxonomy, in CHI’2000: Extended Abstracts on Human Factors in Computing Systems, 1–6 April 2000, Hague, Netherlands, 313–314. https://doi.org/10.1145/633292.633483
Burrows, A.; Bradburn, J.; Cohen, T. 2015. Journeys of the Future: Introducing Mobility as a Service. Atkins Ltd. 36 p.
Butler, L.; Yigitcanlar, T.; Paz, A. 2021. Barriers and risks of mobility-as-a-service (MaaS) adoption in cities: a systematic review of the literature, Cities 109: 103036. https://doi.org/10.1016/j.cities.2020.103036
Datson, J. 2016. Mobility as a Service: Exploring the Opportunity for Mobility as a Service in the UK. Catapult Transport Systems, Milton Keynes, UK. 52 p. Available from Internet: https://cp.catapult.org.uk/wp-content/uploads/2021/07/Exploring_the_Opportunity_for_Mobility.pdf
Dinko, A.; Yatskiv, I.; Budilovich, E. 2022. Sustainable trip planner enriched by trip reliability, Lecture Notes in Networks and Systems 410: 378–388. https://doi.org/10.1007/978-3-030-96196-1_35
Dinko, A.; Yatskiv (Jackiva), I.; Budilovich (Budiloviča), E. 2021. Data sources analysis for sustainable trip planner development for Riga City, Transport and Telecommunication Journal 22(3): 321–331. https://doi.org/10.2478/ttj-2021-0025
Diran, D.; Van Veenstra, A. F.; Timan, T.; Testa, P.; Kirova, M. 2021. Artificial Intelligence in Smart Cities and Urban Mobility. European Parliament (EP). Available from Internet: https://www.europarl.europa.eu/thinktank/en/document/IPOL_BRI(2021)662937
EC. 2020. Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and the Committee of the Regions “Sustainable and Smart Mobility Strategy – Putting European Transport on track for the Future”. COM(2020) 789 Final. 9 December 2020. European Commission (EC), Brussels, Belgium. Available from Internet: https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX%3A52020DC0789
Esztergár-Kiss, D.; Kerényi, T.; Mátrai, T.; Aba, A. 2020. Exploring the MaaS market with systematic analysis, European Transport Research Review 12: 67. https://doi.org/10.1186/s12544-020-00465-z
Farooq, H.; Imran, A. 2017. Spatiotemporal mobility prediction in proactive self-organizing cellular networks, IEEE Communications Letters 21(2): 370–373. https://doi.org/10.1109/LCOMM.2016.2623276
Gambs, S.; Killijian, M.-O.; Del Prado Cortez, M. N. 2012. Next place prediction using mobility Markov chains, in MPM’12: Proceedings of the First Workshop on Measurement, Privacy, and Mobility, 10 April 2012, Bern Switzerland, 1–6. https://doi.org/10.1145/2181196.2181199
Ghanbari, A.; Alvarez O.; Markendahl J. 2016. MTC value network for smart city ecosystems, in 2016 IEEE Wireless Communications and Networking Conference, 3–6 April 2016, Doha, Qatar, 1–6. https://doi.org/10.1109/WCNC.2016.7564649
Gjoreski, H.; Ciliberto, M.; Wang, L.; Ordonez Morales, F. J.; Mekki, S.; Valentin, S.; Roggen, D. 2018. The university of Sussex-Huawei locomotion and transportation dataset for multimodal analytics with mobile devices, IEEE Access 6: 42592–42604. https://doi.org/10.1109/ACCESS.2018.2858933
Gonzalez-Feliu, J.; Pronello, C.; Salanova Grau, J. M. 2018. Multi-stakeholder collaboration in urban transport: state-of-the-art and research opportunities, Transport 33(4): 1079–1094. https://doi.org/10.3846/transport.2018.6810
Harris, S. 2018. Mobility as a Service in Australia: Customer Insights and Opportunities. ITS Australia. Available from Internet: https://infrastructuremagazine.com.au/2018/08/22/mobility-as-a-service-in-australia-customer-insights-and-opportunities/
Hasanzadeh, K.; Kyttä, M.; Lilius, J.; Ramezani, S.; Rinne, T. 2021. Centricity and multi-locality of activity spaces: the varying ways young and old adults use neighborhoods and extra-neighborhood spaces in Helsinki metropolitan area, Cities 110: 103062. https://doi.org/10.1016/j.cities.2020.103062
Heikkilä, S. 2014. Mobility as a Service – a Proposal for Action for the Public Administration, Case Helsinki. MSc Thesis. Aalto University, Finland. 94 p. Available from Internet: https://aaltodoc.aalto.fi/items/ecc44c8c-d2df-48f5-a615-73bd40ac8a32
Hensher, D. A.; Mulley, C.; Nelson, J. D. 2021. Mobility as a service (MaaS) – going somewhere or nowhere?, Transport Policy 111: 153–156. https://doi.org/10.1016/j.tranpol.2021.07.021
Hietanen, S. 2014. ‘Mobility as a service’ – the new transport model?, Eurotransport 12(2): 2–4.
ITF. 2021. The innovative mobility landscape: the case of mobility as a service, International Transport Forum (ITF), Organisation for Economic Co-operation and Development (OECD) Publishing, Paris, France. Available from Internet: https://www.itf-oecd.org/sites/default/files/docs/innovative-mobility-landscape-maas.pdf
Jannach, D.; Zanker, M.; Felfernig, A.; Friedrich, G. 2010. Recommender Systems: an Introduction. Cambridge University Press. 335 p. https://doi.org/10.1017/CBO9780511763113
Jiang, S.; Ferreira, J.; Gonzalez, M. C. 2017. Activity-based human mobility patterns inferred from mobile phone data: a case study of Singapore, IEEE Transactions on Big Data 3(2): 208–219. https://doi.org/10.1109/TBDATA.2016.2631141
Jittrapirom, P.; Caiati, V.; Feneri, A.-M.; Ebrahimigharehbaghi, S.; Alonso González, M. J.; Narayan, J. 2017. Mobility as a service: a critical review of definitions, assessments of schemes, and key challenges, Urban Planning 2(2): 13–25. https://doi.org/10.17645/up.v2i2.931
Johansson, E.; Winslott Hiselius, L.; Koglin, T.; Wretstrand, A. 2017. Evaluation of public transport: regional policies and planning practices in Sweden, Urban, Planning and Transport Research 5(1): 59–77. https://doi.org/10.1080/21650020.2017.1395291
Kamargianni, M.; Li, W.; Matyas, M. 2016. A comprehensive review of “mobility as a service” systems, in Transportation Research Board 95th Annual Meeting, 10–14 January 2016, Washington, DC, US, 1–16.
Kamargianni, M.; Matyas, M. 2017. The business ecosystem of mobility-as-a-service, in Transportation Research Board 96th Annual Meeting, 8–12 January 2017, Washington, DC, US, 1–13.
Kamargianni, M.; Matyas, M.; Li, W.; Schäfer, A. 2015. Feasibility Study for “Mobility as a Service” Concept in London. FS-MaaS Project – Final Deliverable. Energy Institute, University College London (UCL), London, UK, 84 p. Available from Internet: https://discovery.ucl.ac.uk/id/eprint/1469872/
Klinger, T.; Lanzendorf, M. 2016. Moving between mobility cultures: what affects the travel behavior of new residents?, Transportation 43(2): 243–271. https://doi.org/10.1007/s11116-014-9574-x
Komninos, N. 2008. Intelligent Cities and Globalisation of Innovation Networks. Routledge. 320 p. https://doi.org/10.4324/9780203894491
König, D.; Eckhardt, J.; Aapaoja, A.; Sochor, J. L. Karlsson, M. 2016. Business and Operator Models for MaaS. Deliverable No 3. Conference of European Directors of Roads (CEDR). 81 p. Available from Internet: https://publications.lib.chalmers.se/records/fulltext/239795/local_239795.pdf
Kuang, L.; Hao, F.; Yang, L. T.; Lin, M.; Luo C.; Min, G. 2014. A tensor-based approach for big data representation and dimensionality reduction, IEEE Transactions on Emerging Topics in Computing 2(3): 280–291. https://doi.org/10.1109/TETC.2014.2330516
Lättman, K.; Olsson, L. E.; Friman, M. 2018. A new approach to accessibility – examining perceived accessibility in contrast to objectively measured accessibility in daily travel, Research in Transportation Economics 69: 501–511. https://doi.org/10.1016/j.retrec.2018.06.002
Li, X.; Zhang, D.; Lv, Q.; Xiong, J.; Li, S.; Zhang, Y.; Mei, H. 2017. IndoTrack: device-free indoor human tracking with commodity Wi-Fi, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 1(3): 72. https://doi.org/10.1145/3130940
Liu, X.; Dijk, M. 2022. The role of data in sustainability assessment of urban mobility policies, Data & Policy 4: e2. https://doi.org/10.1017/dap.2021.32
Lopes, A. S.; Orozco-Fontalvo, M.; Moura, F.; Vale, D. 2023. Mobility as a service and socio-territorial inequalities: a systematic literature review, Journal of Transport and Land Use 16(1): 215–240. https://doi.org/10.5198/jtlu.2023.2273
Lopez-Carreiro, I.; Monzon, A.; Lopez, E. 2023. MaaS implications in the smart city: a multi-stakeholder approach, Sustainability 15(14): 10832. https://doi.org/10.3390/su151410832
Lyons, G.; Hammond, P.; Mackay, K. 2019. The importance of user perspective in the evolution of MaaS, Transportation Research Part A: Policy and Practice 121: 22–36. https://doi.org/10.1016/j.tra.2018.12.010
Ma, Z.; Zhang, P. 2022. Individual mobility prediction review: data, problem, method and application, Multimodal Transportation 1(1): 100002. https://doi.org/10.1016/j.multra.2022.100002
MaaS Alliance. 2017. Guidelines & Recommendations to Create the Foundations for a Thriving MaaS Ecosystem: MaaS Alliance White Paper. 22 p. Available from Internet: https://maas-alliance.eu/wp-content/uploads/2017/09/MaaS-WhitePaper_final_040917-2.pdf
MaaS Alliance. 2019a. Main Challenges Associated with MaaS & Approaches for Overcoming Them: Study of MaaS Alliance Governance & Business Models Working Group. 7 p. Available from Internet: https://maas-alliance.eu/wp-content/uploads/2019/02/Main-challenges-pdf.pdf
MaaS Alliance. 2019b. Recommendations on a User-Centric Approach for MaaS: Vision Paper of the MaaS Alliance Users & Rules Working Group. 9 p. Available from Internet: https://maas-alliance.eu/wp-content/uploads/2019/04/Recommendations-on-a-User-Centric-Approach-for-MaaS-FINAL-180419.pdf
MaaS Alliance. 2016. The European Mobility as a Service Alliance. Available from Internet: https://maas-alliance.eu/2016/06/01/european-mobility-service-alliance/
MaaS Alliance. 2023. What is MaaS?. Available from Internet: https://maas-alliance.eu/homepage/what-is-maas/
Manzini, E. 2022. Livable Proximity: Ideas for the City that Cares. EGEA Spa – Bocconi University Press. 172 p.
Mitropoulos, L.; Kortsari, A.; Ayfantopoulou, G. 2021. A systematic literature review of ride-sharing platforms, user factors and barriers, European Transport Research Review: 13: 61. https://doi.org/10.1186/s12544-021-00522-1
Mitropoulos, L.; Kortsari, A.; Mizaras, V.; Ayfantopoulou, G. 2023. Mobility as a service (MaaS) planning and implementation: challenges and lessons learned, Future Transportation 3(2): 498–518. https://doi.org/10.3390/futuretransp3020029
Mirzaee, S.; Wang, Q. 2020. Urban mobility and resilience: exploring Boston’s urban mobility network through twitter data, Applied Network Science 5: 75. https://doi.org/10.1007/s41109-020-00316-9
Mukhtar-Landgren, D.; Karlsson, M.; Koglin, T.; Kronsell, A.; Lund, E.; Sarasini, S.; Smith, G.; Sochor, J.; Wendle, B. 2016. Institutional Conditions for Integrated Mobility Services (IMS): Towards a Framework for Analysis. K2 Centrum, Lund, Sweden. 25 p. Available from Internet: https://www.k2centrum.se/sites/default/files/institutional_conditions_for_integrated_mobility_services_ims_wp_2016-16_1.pdf
Pagoni, I.; Gatto, M.; Tsouros, I.; Tsirimpa, A.; Polydoropoulou, A.; Galli, G.; Stefanelli, T. 2022. Mobility-as-a-service: insights to policymakers and prospective MaaS operators, Transportation Letters: the International Journal of Transportation Research 14(4): 356–364. https://doi.org/10.1080/19427867.2020.1815141
Polydoropoulou, A.; Pagoni, I.; Tsirimpa, A. 2020. Ready for mobility as a service? Insights from stakeholders and end-users, Travel Behaviour and Society 21: 295–306. https://doi.org/10.1016/j.tbs.2018.11.003
Pot, F. J.; Koster, S.; Tillema, T. 2023. Perceived accessibility and residential self-selection in the Netherlands, Journal of Transport Geography 108: 103555. https://doi.org/10.1016/j.jtrangeo.2023.103555
Pot, F. J.; Van Wee, B.; Tillema, T. 2021. Perceived accessibility: What it is and why it differs from calculated accessibility measures based on spatial data, Journal of Transport Geography 94: 103090. https://doi.org/10.1016/j.jtrangeo.2021.103090
Saxena, D.; Muzellec, L.; Trabucchi, D. 2020. BlaBlaCar: value creation on a digital platform, Journal of Information Technology Teaching Cases 10(2): 119–126. https://doi.org/10.1177/2043886919885940
Schaffers, H.; Komninos, N.; Pallot, M.; Trousse, B.; Nilsson, M.; Oliveira, A. 2011. Smart cities and the future internet: towards cooperation frameworks for open innovation, Lecture Notes in Computer Science 6656: 431–446. https://doi.org/10.1007/978-3-642-20898-0_31
Schikofsky, J.; Dannewald, T.; Kowald, M. 2020. Exploring motivational mechanisms behind the intention to adopt mobility as a service (MaaS): insights from Germany, Transportation Research Part A: Policy and Practice 131: 296–312. https://doi.org/10.1016/j.tra.2019.09.022
Servou, E.; Behrendt, F.; Horst, M. 2023. Data, AI and governance in MaaS – leading to sustainable mobility?, Transportation Research Interdisciplinary Perspectives 19: 100806. https://doi.org/10.1016/j.trip.2023.100806
Smith, G.; Hensher, D. A. 2020. Towards a framework for mobility-as-a-service policies, Transport Policy 89: 54–65. https://doi.org/10.1016/j.tranpol.2020.02.004
Smith, G.; Sochor, J.; Karlsson, M. 2017. Procuring mobility as a service: exploring dialogues with potential bidders in West Sweden, in ITS World Congress 2017: Integrated Mobility Driving Smart Cities, 29 October – 2 November 2017, Montreal, Canada, 1–12. Available from Internet: https://publications.lib.chalmers.se/records/fulltext/249640/local_249640.pdf
Smith, G.; Sochor, J.; Karlsson, I. C. M. 2019. Public–private innovation: barriers in the case of mobility as a service in West Sweden, Public Management Review 21(1): 116–137. https://doi.org/10.1080/14719037.2018.1462399
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 & Management 27: 3–14. https://doi.org/10.1016/j.rtbm.2018.12.003
Tiihonen, J.; Felfernig, A. 2017. An introduction to personalization and mass customization, Journal of Intelligent Information Systems 49(1): 1–7. https://doi.org/10.1007/s10844-017-0465-4
Tschanz, N.; Zimmermann, H.-D. 1996. The Electronic mall bodensee as platform for the development of travel services, in S. Klein, B. Schmid, A. M. Tjoa, H. Werthner (Eds.). Information and Communication Technologies in Tourism: Proceedings of the International Conference in Innsbruck, 17–19 January 1996, Innsbruck, Austria, 200–210. https://doi.org/10.1007/978-3-7091-7598-9_23
UITP. 2011. Becoming a Real Mobility Provider Combined Mobility Public Transport in Synergy with Other Modes Like Car-Sharing, Taxi and Cycling. International Association of Public Transport (UITP). Available from Internet: https://www.uitp.org/
UITP. 2022. Mobility As A Service (MaaS): Global Landscape. International Association of Public Transport (UITP). Available from Internet: https://www.uitp.org/
Utriainen, R.; Pöllänen, M. 2018. Review on mobility as a service in scientific publications, Research in Transportation Business & Management 27: 15–23. https://doi.org/10.1016/j.rtbm.2018.10.005
Van Audenhove, F.-J.; Arby, H.; Rominger, G.; Tauvel, M. 2021. Beyond MaaS: How to Realize the Promise of Mobility-as-a-Service. Arthur D. Little Inc., Brussels, Belgium. 24 p. Available from Internet: https://www.adlittle.com/sites/default/files/reports/ADL_Beyond_MaaS_Report_0.pdf
Wang, H.; Yang, Y. 2019. Neighbourhood walkability: a review and bibliometric analysis, Cities 93: 43–61. https://doi.org/10.1016/j.cities.2019.04.015
Wang, P.; Yang, L. T.; Li, J.; Chen, J.; Hu, S. 2019. Data fusion in cyber-physical-social systems: state-of-the-art and perspectives, Information Fusion 51: 42–57. https://doi.org/10.1016/j.inffus.2018.11.002
Wong, Y. Z.; Hensher, D. A. 2021. Delivering mobility as a service (MaaS) through a broker/aggregator business model, Transportation 48(4): 1837–1863. https://doi.org/10.1007/s11116-020-10113-z
Wu, J.; Zhou, L.; Cai, C.; Shen, J.; Lau, S. K.; Yong, J. 2018. Data Fusion for MaaS: opportunities and Challenges, in 2018 IEEE 22nd International Conference on Computer Supported Cooperative Work in Design (CSCWD), 9–11 May 2018, Nanjing, China, 642–647. https://doi.org/10.1109/CSCWD.2018.8465224
Xu, X.; Xie, L.; Li, H.; Qin, L. 2018. Learning the route choice behavior of subway passengers from AFC data, Expert Systems with Applications 95: 324–332. https://doi.org/10.1016/j.eswa.2017.11.043
Yang, Y.; Xie, X.; Fang, Z.; Zhang, F.; Wang, Y.; Zhang, D. 2022. VeMo: enable transparent vehicular mobility modeling at individual levels with full penetration, IEEE Transactions on Mobile Computing 21(7): 2637–2651. https://doi.org/10.1109/TMC.2020.3044244
Zhang, B.; Chen, S.; Ma, Y.; Li, T.; Tang, K. 2020. Analysis on spatiotemporal urban mobility based on online car-hailing data, Journal of Transport Geography 82: 102568. https://doi.org/10.1016/j.jtrangeo.2019.102568
Zhou, Y.; Lau, B. P. L.; Yuen, C.; Tuncer, B.; Wilhelm, E. 2018. Understanding urban human mobility through crowdsensed data, IEEE Communications Magazine 56(11): 52–59. https://doi.org/10.1109/MCOM.2018.1700569
Zijlstra, T.; Durand, A.; Hoogendoorn-Lanser, S.; Harms, L. 2020. Early adopters of mobility-as-a-service in the Netherlands, Transport Policy 97: 197–209. https://doi.org/10.1016/j.tranpol.2020.07.019