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Household Mobility Tool Ownership: Modeling Interactions between Cars and Season Tickets

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  • Darren Scott
  • Kay Axhausen

Abstract

This paper moves beyond traditional models of car ownership in that we propose a framework for modeling household-level decisions to acquire specific types and numbers of mobility tools to fulfill the mobility needs of household members. The framework is applied to a data set collected during the winter and spring of 2000/2001 in the German city Karlsruhe via an interactive web-based stated response survey in which respondents could optimize their household mobility tool sets through on-line feedback concerning the estimated costs of the sets. In our analysis, bivariate ordered probit models are estimated for three combinations of mobility tools: season tickets (i.e., transit passes) and cars, season tickets and small cars and season tickets and large cars. In all instances, strong substitution effects are found – that is, as the number of season tickets increases, the number of cars decreases. This finding underscores the need to move beyond simple models of car ownership to comprehensive models of mobility tool ownership. As demonstrated by our research, failure to do so is likely to lead to biased results. Copyright Springer 2006

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  • Darren Scott & Kay Axhausen, 2006. "Household Mobility Tool Ownership: Modeling Interactions between Cars and Season Tickets," Transportation, Springer, vol. 33(4), pages 311-328, July.
    • Handle: RePEc:kap:transp:v:33:y:2006:i:4:p:311-328
    DOI: 10.1007/s11116-005-0328-7
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    References listed on IDEAS

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    1. Alois Stutzer & Bruno S. Frey, 2008. "Stress that Doesn't Pay: The Commuting Paradox," Scandinavian Journal of Economics, Wiley Blackwell, vol. 110(2), pages 339-366, June.
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    2. Ho, Chinh Q. & Hensher, David A. & Mulley, Corinne & Wong, Yale Z., 2018. "Potential uptake and willingness-to-pay for Mobility as a Service (MaaS): A stated choice study," Transportation Research Part A: Policy and Practice, Elsevier, vol. 117(C), pages 302-318.
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    9. Le Vine, Scott & Lee-Gosselin, Martin & Sivakumar, Aruna & Polak, John, 2013. "A new concept of accessibility to personal activities: development of theory and application to an empirical study of mobility resource holdings," Journal of Transport Geography, Elsevier, vol. 31(C), pages 1-10.
    10. Daniel Newman & Peter Wells & Ceri Donovan & Paul Nieuwenhuis & Huw Davies, 2014. "Urban, sub-urban or rural: where is the best place for electric vehicles?," International Journal of Automotive Technology and Management, Inderscience Enterprises Ltd, vol. 14(3/4), pages 306-323.
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    13. Astegiano, Paola & Akinc, Deniz & Himpe, Willem & Tampère, Chris M.J. & Vandebroek, Martina, 2017. "Quantifying the explanatory power of mobility-related attributes in explaining vehicle ownership decisions," Research in Transportation Economics, Elsevier, vol. 66(C), pages 2-11.
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    15. Konstadinos G. Goulias & Ram M. Pendyala, 2014. "Choice context," Chapters, in: Stephane Hess & Andrew Daly (ed.), Handbook of Choice Modelling, chapter 5, pages 101-130, Edward Elgar Publishing.
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    19. William H. Greene & David A. Hensher, 2008. "Modeling Ordered Choices: A Primer and Recent Developments," Working Papers 08-26, New York University, Leonard N. Stern School of Business, Department of Economics.
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