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Behavioral response to congestion: identifying patterns and socio-economic differences in adoption

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  • Mokhtarian, Patricia L.
  • Raney, Elizabeth A.
  • Salomon, Ilan

Abstract

An understanding of how individuals perceive congestion and the range of coping strategies they adopt is crucial for the development of relevant, effective policies. This study empirically tested two hypotheses: (1) that responses to unsatisfactory conditions, such as a congested commute, are a function of previously adopted adjustments; and (2) that responses to congestion are distributed differently across various socio-economic segments. Coping strategies were classified into tiers according to their similarity in implementation cost and effort: lower-effort strategies which increase the comfort in maintaining existing travel patterns; moderate-effort strategies which tend to reduce travel; and major lifestyle/location change strategies such as job or residence changes. Findings confirm that lower-effort strategies tend to be adopted first, with higher-effort strategies adopted if dissatisfaction persists. The adoption of most types of strategies, especially the more costly ones, appears to fall disproportionately to women. Additionally differences were identified by family status, income level, employment status, and household type. These results illustrate the need for further study into patterns of behavioral response to congestion, with the goals of improving forecasts of the effects of congestion mitigation policies and identifying distributional inequities in those effects.

Suggested Citation

  • Mokhtarian, Patricia L. & Raney, Elizabeth A. & Salomon, Ilan, 1997. "Behavioral response to congestion: identifying patterns and socio-economic differences in adoption," University of California Transportation Center, Working Papers qt2v5869bd, University of California Transportation Center.
  • Handle: RePEc:cdl:uctcwp:qt2v5869bd
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    References listed on IDEAS

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    1. P L Mokhtarian & I Salomon, 1996. "Modeling the Choice of Telecommuting: 2. A Case of the Preferred Impossible Alternative," Environment and Planning A, , vol. 28(10), pages 1859-1876, October.
    2. Salomon, Ilan & Mokhtarian, Patricia L., 1997. "Coping with Congestion: Understanding the Gap Between Policy Assumptions and Behavior," University of California Transportation Center, Working Papers qt4bh3b670, University of California Transportation Center.
    3. David Levinson & Ajay Kumar, 1994. "The Rational Locator: Why Travel Times Have Remained Stable," Working Papers 199402, University of Minnesota: Nexus Research Group.
    4. P L Mokhtarian & I Salomon, 1994. "Modeling the Choice of Telecommuting: Setting the Context," Environment and Planning A, , vol. 26(5), pages 749-766, May.
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    Cited by:

    1. Cao, Xinyu & Mokhtarian, Patricia L., 2005. "How do individuals adapt their personal travel? A conceptual exploration of the consideration of travel-related strategies," Transport Policy, Elsevier, vol. 12(3), pages 199-206, May.
    2. Salomon, Ilan & Mokhtarian, Patricia, 1998. "What Happens When Mobility-Inclined Market Segments Face Accessibility-Enhancing Policies?," Institute of Transportation Studies, Working Paper Series qt2x75525j, Institute of Transportation Studies, UC Davis.
    3. Mokhtarian, Patricia L. & Salomon, Ilan, 2001. "How derived is the demand for travel? Some conceptual and measurement considerations," Transportation Research Part A: Policy and Practice, Elsevier, vol. 35(8), pages 695-719, September.
    4. Michael J. Clay * & Patricia L. Mokhtarian, 2004. "Personal travel management: the adoption and consideration of travel-related strategies," Transportation Planning and Technology, Taylor & Francis Journals, vol. 27(3), pages 181-209, June.
    5. Sangho Choo & Patricia Mokhtarian, 2008. "How do people respond to congestion mitigation policies? A multivariate probit model of the individual consideration of three travel-related strategy bundles," Transportation, Springer, vol. 35(2), pages 145-163, March.
    6. Tanzina Afrin & Nita Yodo, 2020. "A Survey of Road Traffic Congestion Measures towards a Sustainable and Resilient Transportation System," Sustainability, MDPI, vol. 12(11), pages 1-23, June.
    7. Irene Casas & Mei‐Po Kwan, 2007. "The Impact of Real‐Time Information on Choices During the Commute Trip: Evidence from a Travel Simulator," Growth and Change, Wiley Blackwell, vol. 38(4), pages 523-543, December.
    8. Mokhtarian, Patricia L. & Ye, Liang & Yun, Meiping, 2010. "The Effects of Gender on Commuter Behavior Changes in the Context of a Major Freeway Construction," Institute of Transportation Studies, Working Paper Series qt86c4v6cr, Institute of Transportation Studies, UC Davis.
    9. Dogterom, Nico & Ettema, Dick & Dijst, Martin, 2018. "Behavioural effects of a tradable driving credit scheme: Results of an online stated adaptation experiment in the Netherlands," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 52-64.
    10. Collantes, Gustavo O. & Mokhtarian, Patricia L., 2002. "Determinants of Subjective Assessments of Personal Mobility," Institute of Transportation Studies, Working Paper Series qt07t1q8cm, Institute of Transportation Studies, UC Davis.
    11. Redmond, Lothlorien S. & Mokhtarian, Patricia L., 2001. "Modeling Objective Mobility: The Impact of Travel-Related Attitudes, Personality and Lifestyle on Distance Traveled," Institute of Transportation Studies, Working Paper Series qt05d352fr, Institute of Transportation Studies, UC Davis.
    12. Choo, Sangho & Mokhtarian, Patricia L, 2004. "Modeling the Individual Consideration of Travel-Related Strategy Bundles," Institute of Transportation Studies, Working Paper Series qt3123v46c, Institute of Transportation Studies, UC Davis.
    13. Lisa Schweitzer & Brian Taylor, 2008. "Just pricing: the distributional effects of congestion pricing and sales taxes," Transportation, Springer, vol. 35(6), pages 797-812, November.
    14. Jin, Jangik & Rafferty, Peter, 2017. "Does congestion negatively affect income growth and employment growth? Empirical evidence from US metropolitan regions," Transport Policy, Elsevier, vol. 55(C), pages 1-8.

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