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Sustainable commute in a car-dominant city: Factors affecting alternative mode choices among university students

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  • Zhou, Jiangping

Abstract

This paper studies university students’ commute and housing behaviors using samples from Los Angeles, a place notorious for car dependence and dominance. It finds that being embedded in this place does not make university students drive alone more than their peers in other places. Being multimodal and having a discounted transit pass increase the odds of alternative modes while holding a parking permit reduces the odds of these modes. Commute distance is positively related to carpool and telecommuting. Gender, status (undergraduate vs. gradate) and age are significantly correlated to biking, walking or public transit. Students living alone are more likely to commute by driving alone than other students. Having friends and classmates living nearby increases the odds of taking public transit. Due to data constraints, this study cannot prove whether there is any correlation between information contagion and the effects of living alone and having friends and classmates living nearby on alternative mode choice. But it proposes that the issue be worthwhile of further investigations. Base on the above, the paper recommends a comprehensive travel demand management program, utilization of information contagion effects of students and promotion of multimodal commute to better promote alternative mode of commute among university students.

Suggested Citation

  • Zhou, Jiangping, 2012. "Sustainable commute in a car-dominant city: Factors affecting alternative mode choices among university students," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(7), pages 1013-1029.
  • Handle: RePEc:eee:transa:v:46:y:2012:i:7:p:1013-1029
    DOI: 10.1016/j.tra.2012.04.001
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    References listed on IDEAS

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    1. Zhou, Jiangping & Wang, Yin & Schweitzer, Lisa, 2012. "Jobs/housing balance and employer-based travel demand management program returns to scale: Evidence from Los Angeles," Transport Policy, Elsevier, vol. 20(C), pages 22-35.
    2. P.B. Goodwin, 1977. "Habit and Hysteresis in Mode Choice," Urban Studies, Urban Studies Journal Limited, vol. 14(1), pages 95-98, February.
    3. McFadden, Daniel, 1980. "Econometric Models for Probabilistic Choice among Products," The Journal of Business, University of Chicago Press, vol. 53(3), pages 13-29, July.
    4. Ajzen, Icek, 1991. "The theory of planned behavior," Organizational Behavior and Human Decision Processes, Elsevier, vol. 50(2), pages 179-211, December.
    5. Balsas, Carlos J. L., 2003. "Sustainable transportation planning on college campuses," Transport Policy, Elsevier, vol. 10(1), pages 35-49, January.
    6. Jen-Jia Lin & Hsiao-Te Chang, 2010. "Built Environment Effects on Children’s School Travel in Taipai: Independence and Travel Mode," Urban Studies, Urban Studies Journal Limited, vol. 47(4), pages 867-889, April.
    7. Arthur, W. Brian & Lane, David A., 1993. "Information contagion," Structural Change and Economic Dynamics, Elsevier, vol. 4(1), pages 81-104, June.
    8. Shannon, Tya & Giles-Corti, Billie & Pikora, Terri & Bulsara, Max & Shilton, Trevor & Bull, Fiona, 2006. "Active commuting in a university setting: Assessing commuting habits and potential for modal change," Transport Policy, Elsevier, vol. 13(3), pages 240-253, May.
    9. Alistair Kerr & Alexia Lennon & Barry Watson, 2010. "The call of the road: factors predicting students’ car travelling intentions and behaviour," Transportation, Springer, vol. 37(1), pages 1-13, January.
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    Citations

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    Cited by:

    1. Cattaneo, Mattia & Malighetti, Paolo & Paleari, Stefano & Redondi, Renato, 2016. "The role of the air transport service in interregional long-distance students’ mobility in Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 93(C), pages 66-82.
    2. Rotaris, Lucia & Danielis, Romeo, 2015. "Commuting to college: The effectiveness and social efficiency of transportation demand management policies," Transport Policy, Elsevier, vol. 44(C), pages 158-168.
    3. Zhou, Jiangping, 2014. "From better understandings to proactive actions: Housing location and commuting mode choices among university students," Transport Policy, Elsevier, vol. 33(C), pages 166-175.
    4. repec:eee:transa:v:103:y:2017:i:c:p:172-184 is not listed on IDEAS
    5. Zhan, Guangjun & Yan, Xuedong & Zhu, Shanjiang & Wang, Yun, 2016. "Using hierarchical tree-based regression model to examine university student travel frequency and mode choice patterns in China," Transport Policy, Elsevier, vol. 45(C), pages 55-65.
    6. Mattia Cattaneo & Paolo Malighetti & Stefano Paleari & Renato Redondi, 2015. "Evolution of long distance students? mobility: the role of transport infrastructures in Italy," ERSA conference papers ersa15p1231, European Regional Science Association.
    7. repec:eee:transa:v:104:y:2017:i:c:p:209-220 is not listed on IDEAS
    8. Özlem Şimşekoğlu & Trond Nordfjærn & Torbjørn Rundmo, 2017. "Predictors of car use habit strength in an urban Norwegian public," Transportation, Springer, vol. 44(3), pages 575-588, May.
    9. Rotaris, Lucia & Danielis, Romeo, 2014. "The impact of transportation demand management policies on commuting to college facilities: A case study at the University of Trieste, Italy," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 127-140.

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