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Electronic Markets

, Volume 27, Issue 3, pp 267–282 | Cite as

Electronic mobility market platforms – a review of the current state and applications of business analytics

  • Christoph Willing
  • Tobias Brandt
  • Dirk Neumann
Research Paper

Abstract

In recent years, the number of urban travel modes has increased significantly and now includes services such as carsharing, e-hailing, ridesharing and bikesharing. This development potentially contributes to more sustainable urban mobility, but also creates complexity for the customer. To simplify customer offerings, so-called multimodal mobility platforms (MMPs) have emerged, bundling the different mobility services to find the best route for the user. These platforms also function as marketplaces where customers can purchase mobility services from different suppliers. As part of this process, data is being generated, which can be utilized to yield valuable insights for suppliers and platform operators. In this paper, we describe the business model of MMPs and provide an overview of currently active solutions. Subsequently we present specific use cases, showing how suppliers can leverage the analytics possibilities of MMPs and how this affects the business model.

Keywords

Intermodal mobility Multimodal mobility Mobility market platforms Spatial analytics Location-based services Sustainable mobility 

JEL classifications

L81 Retail and Wholesale Trade e-Commerce 

References

  1. Aditjandra, P. T., Nelson, J. D., & Wright, S. D. (2009). A multi-modal international journey planning system: a case study of WISETRIP. In 16th ITS World Congress and Exhibition on Intelligent Transport Systems and Services.Google Scholar
  2. Arnott, R., & Inci, E. (2006). An integrated model of downtown parking and traffic congestion. Journal of Urban Economics, 60(3), 418–442. doi: 10.1016/j.jue.2006.04.004.CrossRefGoogle Scholar
  3. Arnott, R., & Small, K. (1994). The Economics of traffic congestion. American Scientist, 82(5), 446–455.Google Scholar
  4. Ayed, H., Galvez-Fernandez, C., Habbas, Z., & Khadraoui, D. (2011). Solving time-dependent multimodal transport problems using a transfer graph model. Computers & Industrial Engineering, 61(2), 391–401. doi: 10.1016/j.cie.2010.05.018.CrossRefGoogle Scholar
  5. Baldwin, C. Y., & Woodard, C. J. (2009). The architecture of platforms: a unified view. In A. Gawer (Ed.), Platforms, markets, and innovation (pp. 19–44). Cheltenham and Northampton: Edward Elgar.Google Scholar
  6. Bardhi, F., & Eckhardt, G. M. (2012). Access-based consumption: the case of car sharing: Table 1. Journal of Consumer Research, 39(4), 881–898. doi: 10.1086/666376.CrossRefGoogle Scholar
  7. Barth, M., & Boriboonsomsin, K. (2008). Real-world carbon dioxide impacts of traffic congestion. Transportation Research Record: Journal of the Transportation Research Board, 2058, 163–171. doi: 10.3141/2058-20.CrossRefGoogle Scholar
  8. Belk, R. (2014). You are what you can access: sharing and collaborative consumption online. Journal of Business Research, 67(8), 1595–1600. doi: 10.1016/j.jbusres.2013.10.001.CrossRefGoogle Scholar
  9. Bertsimas, D., Bradlow, E., Gans, N., & Gupta, A. (2014). Introduction to the special issue on business analytics. Management Science, 60(6), 1351. doi: 10.1287/mnsc.2014.1990.CrossRefGoogle Scholar
  10. Beutel, M. C., Gokay, S., Kluth, W., Krempels, K.-H., Samsel, C., & Terwelp, C. (2014a). Product oriented integration of heterogeneous mobility services. In IEEE 17th International Conference on Intelligent Transportation Systems (ITSC) (pp. 1529–1534).Google Scholar
  11. Beutel, M. C., Samsel, C., Mensing, M., & Krempels, K.-H. (2014b). Business model framework to provide heterogeneous mobility services on virtual markets. In 11th International Conference on E-Business (pp. 145–151).Google Scholar
  12. Birth, O., Hoffmann, M., Strassberger, M., Roor, R., & Schlichter, J. (2015). Concept for an intermodal Traveller information system with real-time data using complex event processing. In IEEE 18th International Conference on Intelligent Transportation Systems (ITSC) (pp. 2293–2298).Google Scholar
  13. Bouwman, H., Vos, H. d., & Haaker, T. (2008). Mobile service innovation and business models. Berlin: Springer.CrossRefGoogle Scholar
  14. Bruglieri, M., Colorni, A., & Luè, A. (2014). The vehicle relocation problem for the one-way electric vehicle sharing: an application to the Milan case. Procedia - Social and Behavioral Sciences, 111, 18–27. doi: 10.1016/j.sbspro.2014.01.034.CrossRefGoogle Scholar
  15. Buchinger, U., Lindmark, S., & Braet, O. (2013). Business model scenarios for an open service platform for multi-modal electric vehicle sharing. In SMART. The Second International Conference on Smart Systems, Devices and Technologies (pp. 7–14).Google Scholar
  16. Buhalis, D., & Law, R. (2008). Progress in information technology and tourism management: 20 years on and 10 years after the internet—The state of eTourism research. Tourism Management, 29(4), 609–623. doi: 10.1016/j.tourman.2008.01.005.CrossRefGoogle Scholar
  17. Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: from big data to big impact. MIS Quarterly, 36(4), 1165–1188.Google Scholar
  18. Chorus, C. G., Arentze, T. A., & Timmermans, H. J. P. (2007). Information impact on quality of multimodal travel choices: conceptualizations and empirical analyses. Transportation, 34(6), 625–645. doi: 10.1007/s11116-007-9120-1.CrossRefGoogle Scholar
  19. Chorus, C., van Cranenburgh, S., & Dekker, T. (2014). Random regret minimization for consumer choice modeling: assessment of empirical evidence. Journal of Business Research, 67(11), 2428–2436. doi: 10.1016/j.jbusres.2014.02.010.CrossRefGoogle Scholar
  20. Ciari, F., Bock, B., & Balmer, M. (2014). Modeling Station-based and free-floating Carsharing demand. Transportation Research Record: Journal of the Transportation Research Board, 2416, 37–47. doi: 10.3141/2416-05.CrossRefGoogle Scholar
  21. Clemente, M., Fanti, M. P., Mangini, A. M., & Ukovich, W. (2013). The vehicle relocation problem in car sharing systems: modeling and simulation in a Petri net framework. In J.-M. Colom & J. Desel (Eds.), Application and theory of Petri Nets and concurrency: 34th international Conference, PETRI NETS 2013, Milan, Italy, June 24–28, 2013. Proceedings (pp. 250–269). Berlin, Heidelberg: Springer.CrossRefGoogle Scholar
  22. de Reuver, M., Verschuur, E., Nikayin, F., Cerpa, N., & Bouwman, H. (2015). Collective action for mobile payment platforms: a case study on collaboration issues between banks and telecom operators. Electronic Commerce Research and Applications, 14(5), 331–344. doi: 10.1016/j.elerap.2014.08.004.CrossRefGoogle Scholar
  23. Di Febbraro, A., Sacco, N., & Saeednia, M. (2012). One-way Carsharing. Transportation Research Record: Journal of the Transportation Research Board, 2319, 113–120. doi: 10.3141/2319-13.CrossRefGoogle Scholar
  24. Eisenmann, T., Parker, G., & van Alstyne, M. (2011). Platform envelopment. Strategic Management Journal, 32(12), 1270–1285. doi: 10.1002/smj.935.CrossRefGoogle Scholar
  25. El Sawy, O. A., & Pereira, F. (2013). Business modelling in the dynamic digital space: an ecosystem approach. Springer briefs in digital spaces. Berlin: Springer.CrossRefGoogle Scholar
  26. European Commission. (2013). Multimodal personal mobility. https://eu-smartcities.eu/sites/all/files/Multimodal%20personal%20mobility%20january.pdf. Accessed 30 Jun 2016.
  27. Farag, S., & Lyons, G. (2012). To use or not to use?: an empirical study of pre-trip public transport information for business and leisure trips and comparison with car travel. Transport Policy, 20, 82–92. doi: 10.1016/j.tranpol.2011.03.007.CrossRefGoogle Scholar
  28. Firnkorn, J., & Müller, M. (2011). What will be the environmental effects of new free-floating car-sharing systems?: The case of car2go in Ulm. Ecological Economics, 70(8), 1519–1528. doi: 10.1016/j.ecolecon.2011.03.014.CrossRefGoogle Scholar
  29. García-Palomares, J. C., Gutiérrez, J., & Latorre, M. (2012). Optimizing the location of stations in bike-sharing programs: a GIS approach. Applied Geography, 35(1–2), 235–246. doi: 10.1016/j.apgeog.2012.07.002.CrossRefGoogle Scholar
  30. Ghazawneh, A., & Henfridsson, O. (2015). A paradigmatic analysis of digital application marketplaces. Journal of Information Technology, 30(3), 198–208. doi: 10.1057/jit.2015.16.CrossRefGoogle Scholar
  31. Giannopoulos, G. A., Tsami, M. T., & Nathanail, E. G. (2015). Defining common goals for future intermodal mobility. In Transportation Research Board 94th Annual Meeting.Google Scholar
  32. Gonzalez, R., Chock, D. P., Zielinski, S., & Raichur, V. (2014). Modeling consumer decision in response to knowledge-based multi-modal transportation. In Transportation Research Board 93rd Annual Meeting.Google Scholar
  33. Greenwood, B. N., & Wattal, S. (2017). Show me the way to go home: an empirical investigation of ride-sharing and alcohol related motor vehicle fatalities. MIS Quarterly, 41(1), 163–187.CrossRefGoogle Scholar
  34. Grotenhuis, J.-W., Wiegmans, B. W., & Rietveld, P. (2007). The desired quality of integrated multimodal travel information in public transport: customer needs for time and effort savings. Transport Policy, 14(1), 27–38. doi: 10.1016/j.tranpol.2006.07.001.CrossRefGoogle Scholar
  35. Hensher, D. A. (1994). Stated preference analysis of travel choices: the state of practice. Transportation, 21(2), 107–133. doi: 10.1007/BF01098788.CrossRefGoogle Scholar
  36. Horn, M. E. (2003). An extended model and procedural framework for planning multi-modal passenger journeys. Transportation Research Part B: Methodological, 37, 641–660.CrossRefGoogle Scholar
  37. Hosack, B., Hall, D., Paradice, D., & Courtney, J. (2012). A look toward the future: decision support system research is alive and well. Journal of the Association for Information Systems, 13(5), 315–340.CrossRefGoogle Scholar
  38. Jäppinen, S., Toivonen, T., & Salonen, M. (2013). Modelling the potential effect of shared bicycles on public transport travel times in greater Helsinki: an open data approach. Applied Geography, 43, 13–24. doi: 10.1016/j.apgeog.2013.05.010.CrossRefGoogle Scholar
  39. Jorge, D., & Correia, G. (2013). Carsharing systems demand estimation and defined operations: a literature review. European Journal of Transport and Infrastructure Research, 13(3), 201–220.Google Scholar
  40. Kenyon, S., & Lyons, G. (2003). The value of integrated multimodal traveller information and its potential contribution to modal change. Transportation Research Part F: Traffic Psychology and Behaviour, 6(1), 1–21. doi: 10.1016/S1369-8478(02)00035-9.CrossRefGoogle Scholar
  41. Kuhnimhof, T., Buehler, R., Wirtz, M., & Kalinowska, D. (2012). Travel trends among young adults in Germany: increasing multimodality and declining car use for men. Journal of Transport Geography, 24, 443–450. doi: 10.1016/j.jtrangeo.2012.04.018.CrossRefGoogle Scholar
  42. Limtanakool, N., Dijst, M., & Schwanen, T. (2006). The influence of socioeconomic characteristics, land use and travel time considerations on mode choice for medium- and longer-distance trips. Journal of Transport Geography, 14(5), 327–341.CrossRefGoogle Scholar
  43. Lisson, C., Michalk, W., & Görlitz, R. (2015). Evaluating services in mobility markets: a business model approach. In R. Görlitz, V. Bertsch, S. Caton, N. Feldmann, P. Jochem, M. Maleshkova, & M. Reuter-Oppermann (Eds.), KIT scientific reports: Vol. 7692. Proceedings of the first Karlsruhe service summit workshop - advances in service research, Karlsruhe, Germany, February 2015 (pp. 43–49). Karlsruhe: KIT Scientific Publishing.Google Scholar
  44. Marx, R., Mello, A. M. D., Zilbovicius, M., & Lara, F. F. D. (2015). Spatial contexts and firm strategies: applying the multilevel perspective to sustainable urban mobility transitions in Brazil. Journal of Cleaner Production, 108(Part A), 1092–1104. doi: 10.1016/j.jclepro.2015.09.001.CrossRefGoogle Scholar
  45. Masuch, N., Lützenberger, M., & Keiser, J. (2013). An open extensible platform for intermodal mobility assistance. Procedia Computer Science, 19, 396–403. doi: 10.1016/j.procs.2013.06.054.CrossRefGoogle Scholar
  46. Motta, G., Sacco, D., Ma, T., You, L., & Liu, K. (2015). Personal mobility service system in urban areas: The IRMA project. In IEEE Symposium on Service-Oriented System Engineering (SOSE) (pp. 88–97).Google Scholar
  47. Müller, J., & Bogenberger, K. (2015). Time series analysis of booking data of a free-floating Carsharing system in Berlin. Transportation Research Procedia, 10, 345–354. doi: 10.1016/j.trpro.2015.09.084.CrossRefGoogle Scholar
  48. Nobis, C. (2007). Multimodality: facets and causes of sustainable mobility behavior. Transportation Research Record: Journal of the Transportation Research Board, 2010, 35–44. doi: 10.3141/2010-05.CrossRefGoogle Scholar
  49. Osterwalder, A. (2004). The business model ontology: a proposition in a design science approach. Lausanne: University of Lausanne.Google Scholar
  50. Parker, G., van Alstyne, M., & Jiang, X. (2017). Platform ecosystems: how developers invert the firm. MIS Quarterly, 41(1), 255–266.CrossRefGoogle Scholar
  51. Remane, G., Hildebrandt, B., Hanelt, A., & Kolbe, L.M. (2016). Discovering New Digital Business Model Types – A Study of Technology Startups from the Mobility Sector. PACIS 2016 Proceedings, Paper 289.Google Scholar
  52. Rifkin, J. (2000). The age of access: the new culture of hypercapitalism, where all of life is a paid-for experience. New York: J.P. Tarcher/Putnam.Google Scholar
  53. Rochet, J.-C., & Tirole, J. (2006). Two-sided markets: a progress report. The Rand Journal of Economics, 37(3), 645–667. doi: 10.1111/j.1756-2171.2006.tb00036.x.CrossRefGoogle Scholar
  54. Scharl, A., & Brandtweiner, R. (1998). A conceptual research framework for analyzing the evolution of electronic markets. Electronic Markets, 8(2), 39–42. doi: 10.1080/10196789800000026.CrossRefGoogle Scholar
  55. Schmöller, S., Weikl, S., Müller, J., & Bogenberger, K. (2015). Empirical analysis of free-floating carsharing usage: the Munich and Berlin case. Transportation Research Part C: Emerging Technologies, 56, 34–51. doi: 10.1016/j.trc.2015.03.008.CrossRefGoogle Scholar
  56. Shaheen, S. A., & Cohen, A. P. (2013). Carsharing and personal vehicle services: worldwide market developments and emerging trends. International Journal of Sustainable Transportation, 7(1), 5–34. doi: 10.1080/15568318.2012.660103.CrossRefGoogle Scholar
  57. Shaheen, S., Guzman, S., & Zhang, H. (2010). Bikesharing in Europe, the Americas, and Asia. Transportation Research Record: Journal of the Transportation Research Board, 2143, 159–167. doi: 10.3141/2143-20.CrossRefGoogle Scholar
  58. Sørensen, C., de Reuver, M., & Basole, R. C. (2015). Mobile platforms and ecosystems. Journal of Information Technology, 30(3), 195–197. doi: 10.1057/jit.2015.22.CrossRefGoogle Scholar
  59. Spickermann, A., Grienitz, V., & von der Gracht, H. A. (2014). Heading towards a multimodal city of the future? Technological Forecasting and Social Change, 89, 201–221. doi: 10.1016/j.techfore.2013.08.036.CrossRefGoogle Scholar
  60. Stillwater, T., Mokhtarian, P., & Shaheen, S. (2009). Carsharing and the built environment. Transportation Research Record: Journal of the Transportation Research Board, 2110, 27–34. doi: 10.3141/2110-04.CrossRefGoogle Scholar
  61. Strasser, M., Weiner, N., & Albayrak, S. (2015). The potential of interconnected service marketplaces for future mobility. Computers and Electrical Engineering, 45, 169–181. doi: 10.1016/j.compeleceng.2015.06.008.CrossRefGoogle Scholar
  62. Teubner, T., & Flath, C. M. (2015). The Economics of multi-hop ride sharing. Business & Information Systems Engineering, 57(5), 311–324. doi: 10.1007/s12599-015-0396-y.CrossRefGoogle Scholar
  63. Tirachini, A., Hensher, D. A., & Rose, J. M. (2014). Multimodal pricing and optimal design of urban public transport: the interplay between traffic congestion and bus crowding. Transportation Research Part B: Methodological, 61, 33–54. doi: 10.1016/j.trb.2014.01.003.CrossRefGoogle Scholar
  64. TomTom. (2016). Amsterdam and TomTom join forces to create a smarter city. http://corporate.tomtom.com/releasedetail.cfm?ReleaseID=1000874. Accessed 10 Dec 2016.
  65. van Nes, R., & Bovy, P. (2004). Multimodal traveling and its impact on urban transit network design. Journal of Advanced Transportation, 38(3), 225–241. doi: 10.1002/atr.5670380302.CrossRefGoogle Scholar
  66. Verplanken, B., Walker, I., Davis, A., & Jurasek, M. (2008). Context change and travel mode choice: combining the habit discontinuity and self-activation hypotheses. Journal of Environmental Psychology, 28(2), 121–127. doi: 10.1016/j.jenvp.2007.10.005.CrossRefGoogle Scholar
  67. Vredin Johansson, M., Heldt, T., & Johansson, P. (2006). The effects of attitudes and personality traits on mode choice. Transportation Research Part A: Policy and Practice, 40(6), 507–525. doi: 10.1016/j.tra.2005.09.001.CrossRefGoogle Scholar
  68. Wagner, S., Willing, C., Brandt, T., & Neumann, D. (2015). Data analytics for location-based services: enabling user-based relocation of Carsharing vehicles. In Proceedings of the 36th International Conference on Information Systems.Google Scholar
  69. Wagner, S., Brandt, T., & Neumann, D. (2016). In free float: developing business analytics support for carsharing providers. Omega, 59, 4–14. doi: 10.1016/j.omega.2015.02.011.CrossRefGoogle Scholar
  70. Weikl, S., & Bogenberger, K. (2013). Relocation strategies and algorithms for free-floating car sharing systems. IEEE Intelligent Transportation Systems Magazine, 5(4), 100–111. doi: 10.1109/MITS.2013.2267810 .CrossRefGoogle Scholar
  71. Weikl, S., & Bogenberger, K. (2015). Integrated relocation model for free-floating Carsharing systems. Transportation Research Record: Journal of the Transportation Research Board, 2536, 19–27. doi: 10.3141/2536-03.CrossRefGoogle Scholar
  72. Wicke, G. A. (1999). Electronic markets - a key to mobility. Electronic Markets, 9(3), 162–168. doi: 10.1080/101967899359058.CrossRefGoogle Scholar
  73. Willing, C., Gust, G., Brandt, T., Schmidt, S., & Neumann, D. (2016). Enhancing municipal analytics capabilities to enable sustainable urban transportation. In Proceedings of the 24th European Confrence on Information Systems (ECIS).Google Scholar
  74. Zhang, J., Liao, F., Arentze, T., & Timmermans, H. (2011). A multimodal transport network model for advanced traveler information systems. Procedia - Social and Behavioral Sciences, 20, 313–322. doi: 10.1016/j.sbspro.2011.08.037.CrossRefGoogle Scholar

Copyright information

© Institute of Applied Informatics at University of Leipzig 2017

Authors and Affiliations

  1. 1.Abteilung für WirtschaftsinformatikAlbert-Ludwigs-Universität FreiburgFreiburg im BreisgauGermany
  2. 2.Rotterdam School of ManagementErasmus UniversityRotterdamThe Netherlands

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