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Substitution and complementarity patterns between traditional transport means and car sharing: a person and trip level analysis

  • Riccardo CeccatoEmail author
  • Marco Diana
Article
  • 287 Downloads

Abstract

Car sharing is a new transport mode which combines characteristics of private and collective traditional transport means. Understanding the relationship of this mode with existing ones is very important for policy makers to create an efficient transport system and to properly address public resources. This paper aims to analyze the interaction of car sharing with the existing offer of competing modes, using data from a specific travel survey administered in the city of Turin, where both free-floating and one-way station based car sharing services are offered. All transport modes operating in the study area were considered. Bivariate models were estimated to study the propensity to have a car sharing subscription and the substitution patterns between different travel means for a representative random sample of trips taken by the Turin population. Results show that the current car sharing system is perceived as efficient and useful; car sharing members are young males, living in high-income and low-size household with, in particular, a high number of workers and low number of available cars; moreover, the presence of private parking near home has a strong negative impact. There is evidence that car sharing can substitute car driving trips, while the evidence that the same can happen with biking and walking trips is not supported by models but only marginally seen from descriptive statistics. There is also some complementarity between car sharing and public transport and a strong complementarity between car sharing and bike sharing, so that policy makers should jointly promote those modes.

Keywords

Car sharing Sustainability Public transport Multimodality Car ownership 

Notes

Acknowledgements

This research has been partly financed through a “Ricerca dei Talenti” Grant from Fondazione CRT.

Author contributions

Riccardo Ceccato analysed the data, performed the literature review and wrote the manuscript. Marco Diana designed the survey and the analysis method, interpreted the results and contributed in writing the manuscript.

Compliance with ethical standards

Conflict of interest

Both authors declare that they have no conflict of interest.

References

  1. Barth, M., Shaheen, S.: Shared-use vehicle systems: framework for classifying carsharing, station cars, and combined approaches. Transp. Res. Rec. J. Transp. Res. Board. (2002).  https://doi.org/10.3141/1791-16 Google Scholar
  2. Becker, H., Ciari, F., Axhausen, K.W.: Comparing car-sharing schemes in Switzerland: user groups and usage patterns. Transp. Res. Part A Policy Pract. (2017a).  https://doi.org/10.1016/j.tra.2017.01.004 Google Scholar
  3. Becker, H., Ciari, F., Axhausen, K.W.: Modeling free-floating car-sharing use in Switzerland: a spatial regression and conditional logit approach. Transp. Res. Part C Emerg. Technol. (2017b).  https://doi.org/10.1016/j.trc.2017.06.008 Google Scholar
  4. Becker, H., Loder, A., Schmid, B., Axhausen, K.W.: Modeling car-sharing membership as a mobility tool: a multivariate Probit approach with latent variables. Travel Behav. Soc. (2017c).  https://doi.org/10.1016/j.tbs.2017.04.006 Google Scholar
  5. Cervero, R., Golub, A., Nee, B.: City CarShare: longer-term travel demand and car ownership impacts. Transp. Res. Rec. J. Transp. Res. Board. (2007).  https://doi.org/10.3141/1992-09 Google Scholar
  6. Chen, T.D., Kockelman, K.M.: Carsharing’s life-cycle impacts on energy use and greenhouse gas emissions. Transp. Res. Part D Transp. Environ. (2016).  https://doi.org/10.1016/j.trd.2016.05.012 Google Scholar
  7. Ciari, F., Axhausen, K.W.: Choosing carpooling or carsharing as a mode: Swiss stated choice experiments. In: 91st Annual Meeting the Transportation Research Board, Washington, USA (2012)Google Scholar
  8. Ciari, F., Bock, B., Balmer, M.: Modeling station-based and free-floating carsharing demand. Transp. Res. Rec. J. Transp. Res. Board. (2014).  https://doi.org/10.3141/2416-05 Google Scholar
  9. Clewlow, R.R.: Carsharing and sustainable travel behavior: results from the San Francisco Bay area. Transp. Policy (2016).  https://doi.org/10.1016/j.tranpol.2016.01.013 Google Scholar
  10. Clewlow, R.R., Mishra, G.S.: Disruptive transportation: the adoption, utilization, and impacts of ride-hailing in the United States. Institute of Transportation Studies, University of California, Davis, Research. Report UCD-ITS-RR-17-07 (2017)Google Scholar
  11. Coll, M.H., Vandersmissen, M.H., Thériault, M.: Modeling spatio-temporal diffusion of carsharing membership in Québec City. J. Transp. Geogr. (2014).  https://doi.org/10.1016/j.jtrangeo.2014.04.017 Google Scholar
  12. Cooper, G., Hower, D.A., Mye, P.: The missing link: an evaluation of CarSharing Portland Inc. Portland, Oregon. Master of Urban and Regional Planning Workshop Projects, Paper 74 (2000)Google Scholar
  13. Costain, C., Ardron, C., Habib, K.N.: Synopsis of users’ behaviour of a carsharing program: a case study in Toronto. Transp. Res. Part A Policy Pract. (2012).  https://doi.org/10.1016/j.tra.2011.11.005 Google Scholar
  14. de Luca, S., Di Pace, R.: Modelling users’ behaviour in inter-urban carsharing program: a stated preference approach. Transp. Res. Part A Policy Pract. (2015).  https://doi.org/10.1016/j.tra.2014.11.001 Google Scholar
  15. Diana, M.: Making the “primary utility of travel” concept operational: a measurement model for the assessment of the intrinsic utility of reported trips. Transp. Res. Part A Policy Pract. (2008).  https://doi.org/10.1016/j.tra.2007.12.005 Google Scholar
  16. Diana, M.: From mode choice to modal diversion: a new behavioural paradigm and an application to the study of the demand for innovative transport services. Technol. Forecast. Soc. Change (2010).  https://doi.org/10.1016/j.techfore.2009.10.005 Google Scholar
  17. Dias, F.F., Lavieri, P., Garikapati, V.M., Astroza, S., Pendyala, R.M., Bhat, C.R.: A behavioral choice model of the use of car-sharing and ride-sourcing services. Transportation (2017).  https://doi.org/10.1007/s11116-017-9797-8 Google Scholar
  18. Efthymiou, D., Antoniou, C.: Modeling the propensity to join carsharing using hybrid choice models and mixed survey data. Transp. Policy (2016).  https://doi.org/10.1016/j.tranpol.2016.07.001 Google Scholar
  19. Efthymiou, D., Antoniou, C., Waddell, P.: Factors affecting the adoption of vehicle sharing systems by young drivers. Transp. Policy (2013).  https://doi.org/10.1016/j.tranpol.2013.04.009 Google Scholar
  20. Ettema, D., Gärling, T., Olsson, L.E., Friman, M.: Out-of-home activities, daily travel, and subjective well-being. Transp. Res. Part A Policy Pract. (2010).  https://doi.org/10.1016/j.tra.2010.07.005 Google Scholar
  21. Ettema, D., Gärling, T., Eriksson, L., Friman, M., Olsson, L.E., Fujii, S.: Satisfaction with travel and subjective well-being: development and test of a measurement tool. Transp. Res. Part F Traffic Psychol. Behav. (2011).  https://doi.org/10.1016/j.trf.2010.11.002 Google Scholar
  22. Habib, K.M.N., Morency, C., Islam, M.T., Grasset, V.: Modelling users’ behaviour of a carsharing program: application of a joint hazard and zero inflated dynamic ordered probability model. Transp. Res. Part A Policy Pract. (2012).  https://doi.org/10.1016/j.tra.2011.09.019 Google Scholar
  23. Huwer, U.: Public transport and car-sharing—benefits and effects of combined services. Transp. Policy (2004).  https://doi.org/10.1016/j.tranpol.2003.08.002 Google Scholar
  24. Kopp, J., Gerike, R., Axhausen, K.W.: Status Quo and perspectives for carsharing systems: the example of DriveNow. In: Hülsmann, F., Gerike, R. (eds.) Strategies for Sustainable Mobilities: Opportunities and Challenges, pp. 207–226. Taylor and Francis, Routledge (2013)Google Scholar
  25. Kopp, J., Gerike, R., Axhausen, K.W.: Do sharing people behave differently? An empirical evaluation of the distinctive mobility patterns of free-floating car-sharing members. Transportation (2015).  https://doi.org/10.1007/s11116-015-9606-1 Google Scholar
  26. Lane, C.: PhillyCarShare: First-year social and mobility impacts of carsharing in Philadelphia, Pennsylvania. Transp. Res. Rec. J. Transp. Res. Board (2005).  https://doi.org/10.3141/1927-18 Google Scholar
  27. Le Vine, S., Lee-Gosselin, M., Sivakumar, A., Polak, J.: A new approach to predict the market and impacts of round-trip and point-to-point carsharing systems: case study of London. Transp. Res. Part D Transp. Environ. (2014).  https://doi.org/10.1016/j.trd.2014.07.005 Google Scholar
  28. Martin, E., Shaheen, S.: Impacts of car2go on vehicle ownership, modal shift, vehicle miles travelled, and greenhouse gas emissions: an analysis of five North American cities. http://innovativemobility.org/wp-content/uploads/2016/07/Impactsofcar2go_FiveCities_2016.pdf (2016). Accessed 7 May 2018
  29. Martin, E., Shaheen, S.: The impact of carsharing on public transit and non-motorized travel: an exploration of North American carsharing survey data. Energies (2011a).  https://doi.org/10.3390/en4112094 Google Scholar
  30. Martin, E., Shaheen, S.A.: Greenhouse gas emissions impacts of carsharing in North America. Trans. Intell. Transp. Syst. (2011b).  https://doi.org/10.1109/TITS.2011.2158539 Google Scholar
  31. Martin, E., Shaheen, S., Lidicker, J.: Impact of carsharing on household vehicle holdings. Transp. Res. Rec. J. Transp. Res. Board (2010).  https://doi.org/10.3141/2143-19 Google Scholar
  32. Ministero dell’Ambiente: Decreto 27 marzo 1998—Mobilità sostenibile nelle aree urbane, Gazzetta Ufficiale Serie Generale n.179 del 03-08-1998 (1998)Google Scholar
  33. Mishra, G.S., Clewlow, R.R., Mokhtarian, P.L., Widaman, K.F.: The effect of carsharing on vehicle holdings and travel behavior: a propensity score and causal mediation analysis of the San Francisco Bay Area. Res. Transp. Econ. (2015).  https://doi.org/10.1016/j.retrec.2015.10.010 Google Scholar
  34. Mishra, G.S., Mokhtarian, P.L., Clewlow, R.R., Widaman, K.F.: Addressing the joint occurrence of self-selection and simultaneity biases in the estimation of program effects based on cross-sectional observational surveys: case study of travel behavior effects in carsharing. Transportation (2017).  https://doi.org/10.1007/s11116-017-9791-1 Google Scholar
  35. Morency, C., Trépanier, M., Agard, B., Martin, B., Quashie, J.: Car sharing system: what transaction datasets reveal on users’ behaviors. In: The 10th International IEEE Conference on Intelligent Transportation Systems—ITSC 2007, pp. 284–289. Seattle, Washington, USA (2007)Google Scholar
  36. Murphy, C.: Shared mobility and the transformation of public transit. TCRP J-11/TASK 21. American Public Transportation Association (2016)Google Scholar
  37. Nobis, C.: Carsharing as key contribution to multimodal and sustainable mobility behavior: carsharing in Germany. Transp. Res. Rec. (2006).  https://doi.org/10.3141/1986-14 Google Scholar
  38. Osservatorio Nazionale della Sharing Mobility: 1° rapporto nazionale. La sharing mobility in Italia: numeri, fatti e potenzialità. http://osservatoriosharingmobility.it/wp-content/uploads/2016/11/Rapporto-Nazionale-SM_DEF_23_11_2016.pdf (2016). Accessed 7 May 2018
  39. R Core Team: R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria, https://www.r-project.org/ (2017)
  40. Rodier, C.R., Shaheen, S.: Carsharing and carfree housing: predicted travel, emission and economic benefits. In: 83th Annual Meeting of Transportation Research Board, Washington, USA (2004)Google Scholar
  41. Schmöller, S., Weikl, S., Müller, J., Bogenberger, K.: Empirical analysis of free-floating carsharing usage: the munich and berlin case. Transp. Res. Part C Emerg. Technol. (2015).  https://doi.org/10.1016/j.trc.2015.03.008 Google Scholar
  42. Shaheen, S., Chan, N.: Mobility and the sharing economy-potential to facilitate the first and last mile public transit connections. Built Environ. (2016).  https://doi.org/10.2148/benv.42.4.573 Google Scholar
  43. Steg, L.: Car use: lust and must. Instrumental, symbolic and affective motives for car use. Transp. Res. Part A Policy Pract. (2005).  https://doi.org/10.1016/j.tra.2004.07.001 Google Scholar
  44. Stillwater, T., Mokhtarian, P., Shaheen, S.: Carsharing and the built environment. Transp. Res. Rec. J. Transp. Res. Board (2009).  https://doi.org/10.3141/2110-04 Google Scholar
  45. Urbi: Car sharing facts—overview Settembre 2016—Febbraio 2017, Urbi infographic (2017)Google Scholar
  46. Wagner, S., Brandt, T., Neumann, D.: Data analytics in free-floating carsharing: evidence from the city of Berlin. In: 48th Hawaii International Conference on System Sciences (HICSS), pp. 897–907. IEEE (2015)Google Scholar
  47. Wagner, S., Brandt, T., Neumann, D.: In free float: developing business analytics support for carsharing providers. Omega (2016).  https://doi.org/10.1016/j.omega.2015.02.011 Google Scholar
  48. Zheng, J., Scott, M., Rodriguez, M., Sierzchula, W., Platz, D., Guo, J., Adams, T.: Carsharing in a university community. Transp. Res. Rec. J. Transp. Res. Board (2009).  https://doi.org/10.3141/2110-03 Google Scholar
  49. Zhou, B., Kockelman, K.M.: Opportunities for and impacts of carsharing: a survey of the Austin, Texas market. Int. J. Sustain. Transp. (2011).  https://doi.org/10.1080/15568311003717181 Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Environment, Land and Infrastructure EngineeringPolitecnico di TorinoTurinItaly

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