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A conceptual analysis of the impact of travel demand management on private car use

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Author Info

  • Gärling, Tommy
  • Eek, Daniel
  • Loukopoulos, Peter
  • Fujii, Satoshi
  • Johansson-Stenman, Olof
  • Kitamura, Ryuichi
  • Pendyala, Ram
  • Vilhelmson, Bertil

Abstract

A conceptual framework is presented that may be utilized when analyzing changes in household travel arising from the range of potential measures available to policy makers. The proposed framework draws on goal setting theory in order to understand how travel is influenced by the impact various travel demand management (TDM) measures have on time, cost, and convenience of travel options. Travel is understood from a perspective assuming that it is controlled by negative feedback functioning to minimize deviations from goals nested at different levels. The conceptual framework, with its basis in goal setting and control theories, is then applied to understanding strategic and operational choice related to travel as well as habitual travel. Finally, the proposed conceptual framework is used to highlight and focus attention on key research issues that ought to be addressed if our understanding of the impact of TDM measures on household travel, and private car use in particular, is to improve.

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Bibliographic Info

Article provided by Elsevier in its journal Transport Policy.

Volume (Year): 9 (2002)
Issue (Month): 1 (January)
Pages: 59-70

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Handle: RePEc:eee:trapol:v:9:y:2002:i:1:p:59-70

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References

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  1. Goodwin, Phil, 1996. "Simple arithmetic," Transport Policy, Elsevier, vol. 3(3), pages 79-80, July.
  2. Wright, C. & Egan, J., 2000. "De-marketing the car," Transport Policy, Elsevier, vol. 7(4), pages 287-294, October.
  3. R M Pendyala & R Kitamura & D V G Prasuna Reddy, 1998. "Application of an activity-based travel-demand model incorporating a rule-based algorithm," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 25(5), pages 753-772, September.
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  5. Kitamura, R. & Nakayama, S. & Yamamoto, T., 1999. "Self-reinforcing motorization: can travel demand management take us out of the social trap?," Transport Policy, Elsevier, vol. 6(3), pages 135-145, July.
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  7. Gärling, Tommy & Gärling, Anita & Johansson, Anders, 2000. "Household choices of car-use reduction measures," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(5), pages 309-320, June.
  8. Cecilia Jakobsson & Satoshi Fujii & Tommy Gärling, 2002. "Effects of economic disincentives on private car use," Transportation, Springer, vol. 29(4), pages 349-370, November.
  9. Jakobsson, C. & Fujii, S. & Gärling, T., 2000. "Determinants of private car users' acceptance of road pricing," Transport Policy, Elsevier, vol. 7(2), pages 153-158, April.
  10. Pendyala, Ram M. & Kitamura, Ryuichi & Chen, Cynthia & Pas, Eric I., 1997. "An activity-based microsimulation analysis of transportation control measures," Transport Policy, Elsevier, vol. 4(3), pages 183-192, July.
  11. Gärling, Tommy & Kwan, Mei-Po & Golledge, Reginald G., 1994. "Computational-process modelling of household activity scheduling," Transportation Research Part B: Methodological, Elsevier, vol. 28(5), pages 355-364, October.
  12. Kitamura, Ryuichi & Fujii, Satoshi & Pas, Eric I., 1997. "Time-use data, analysis and modeling: toward the next generation of transportation planning methodologies," Transport Policy, Elsevier, vol. 4(4), pages 225-235, October.
  13. Hensher, David A., 1998. "The imbalance between car and public transport use in urban Australia: why does it exist?," Transport Policy, Elsevier, vol. 5(4), pages 193-204, October.
  14. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
  15. Mark Paich & John D. Sterman, 1993. "Boom, Bust, and Failures to Learn in Experimental Markets," Management Science, INFORMS, vol. 39(12), pages 1439-1458, December.
  16. R H M Emmerink & P Nijkamp & P Rietveld, 1995. "Is congestion pricing a first-best strategy in transport policy? A critical review of arguments," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 22(5), pages 581-602, September.
  17. Tommy Gärling & Robert Gillholm & William Montgomery, 1999. "The role of anticipated time pressure in activity scheduling," Transportation, Springer, vol. 26(2), pages 173-191, May.
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Citations

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Cited by:
  1. Choo, Sangho & Mokhtarian, Patricia L, 2008. "How do people respond to congestion mitigation policies? A multivariate probit model of the individual consideration of three travel-related strategy bundles," University of California Transportation Center, Working Papers qt53s553tn, University of California Transportation Center.
  2. Sunitiyoso, Yos & Matsumoto, Shoji, 2009. "Modelling a social dilemma of mode choice based on commuters' expectations and social learning," European Journal of Operational Research, Elsevier, vol. 193(3), pages 904-914, March.
  3. Löfgren, Åsa, 2003. "The Effect of Addiction on Environmental Taxation in a First and Second-best world," Working Papers in Economics 91, University of Gothenburg, Department of Economics.
  4. Yu, Biying & Zhang, Junyi & Fujiwara, Akimasa, 2011. "Representing in-home and out-of-home energy consumption behavior in Beijing," Energy Policy, Elsevier, vol. 39(7), pages 4168-4177, July.
  5. Clay, Michael J. & Mokhtarian, Patricia L., 2004. "Personal Travel Management: The Adoption and Consideration of Travel-Related Strategies," University of California Transportation Center, Working Papers qt3mw6d5hj, University of California Transportation Center.
  6. Bamberg, Sebastian & Fujii, Satoshi & Friman, Margareta & Gärling, Tommy, 2011. "Behaviour theory and soft transport policy measures," Transport Policy, Elsevier, vol. 18(1), pages 228-235, January.

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