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Longer-term changes in mode choice decisions in Chennai: a comparison between cross-sectional and dynamic models

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  • Karthik Srinivasan

    ()

  • P. Bhargavi

    ()

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    Abstract

    The rapid and continuing changes in travel and mobility needs in India over the last decade necessitates the development and use of dynamic models for travel demand forecasting rather than cross-sectional models. In this context, this paper investigates mode choice dynamics among workers in Chennai city, India over a period of five years (1999–2004). Dynamics in mode choice is captured at four levels: exogenous variable change, state-dependence, changes in users’ sensitivity to attributes, and unobserved error terms. The results show that the dynamic models provide a substantial improvement (of over 500 log-likelihood points and ρ 2 increases from 44% to 68%) over the cross-sectional model. The performance was compared using two illustrative policy scenarios with important methodological and practical implications. The results indicate that cross-sectional models tend to provide inflated estimates of potential improvement measures. Improving the Level of Service (LOS) alone will not produce the anticipated benefits to transit agencies, as it fails to overcome the persistent inertia captured in the state-dependence factors. The results and models have important applications in the context of growing motorization and congestion management in developing countries. Copyright Springer Science+Business Media, LLC 2007

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    File URL: http://hdl.handle.net/10.1007/s11116-007-9116-x
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    Bibliographic Info

    Article provided by Springer in its journal Transportation.

    Volume (Year): 34 (2007)
    Issue (Month): 3 (May)
    Pages: 355-374

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    Handle: RePEc:kap:transp:v:34:y:2007:i:3:p:355-374

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    Web page: http://www.springerlink.com/link.asp?id=103007

    Related research

    Keywords: Dynamics; Mode choice; Mixed logit; Retrospective study; Reverse; State dependence;

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    1. Kitamura, Ryuichi, 1990. "Panel Analysis in Transportation Planning: An Overview," University of California Transportation Center, Working Papers qt86v0f7zh, University of California Transportation Center.
    2. Golob, Thomas F., 1990. "The Dynamics of Household Travel Time Expenditures and Car Ownership Decisions," University of California Transportation Center, Working Papers qt2t18b4q9, University of California Transportation Center.
    3. Golob, Thomas F., 1990. "The Dynamics of Household Travel Time Expenditures and Car Ownership Decisions," University of California Transportation Center, Working Papers qt1676t0bp, University of California Transportation Center.
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    Cited by:
    1. Cinzia Cirillo & Kay Axhausen, 2010. "Dynamic model of activity-type choice and scheduling," Transportation, Springer, vol. 37(1), pages 15-38, January.
    2. Kiron Chatterjee, 2011. "Modelling the dynamics of bus use in a changing travel environment using panel data," Transportation, Springer, vol. 38(3), pages 487-509, May.
    3. Elisabetta Cherchi & Francesco Manca, 2011. "Accounting for inertia in modal choices: some new evidence using a RP/SP dataset," Transportation, Springer, vol. 38(4), pages 679-695, July.

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