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Market research evaluation of actions to reduce suburban traffic congestion: Commuter travel behavior and response to demand reduction actions

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  • Koppelman, Frank S.
  • Bhat, Chandra R.
  • Schofer, Joseph L.

Abstract

This research paper is directed toward obtaining a better understanding of current work trip mode choice of commuters in suburban areas and the effectiveness of alternate demand reduction actions in alleviating congestion, based on a Chicago area study. The paper is particularly concerned with an evaluation of the effectiveness of demand reduction actions that encourage the use of ridesharing modes (carpool, vanpool and transit) and/or discourage the use of drive-alone auto for the work trip. A conceptual framework of current mode-choice behavior and behavioral response to demand reduction actions is developed. The empirical analysis suggests that in the midwest suburban setting, any substantial increase in ridesharing propensity appears to require a combination of ridesharing incentives in the form of improved service characteristics and direct auto-use disincentives in the form of substantially increased parking costs. Our analysis also suggests that ridesharing propensity is greater for women and individuals in households with fewer autos. Individuals who have a great need for independence, make additional trips on their way to and from work, frequently stay late at work, and have a high income tend to be less inclined to use ridesharing modes.

Suggested Citation

  • Koppelman, Frank S. & Bhat, Chandra R. & Schofer, Joseph L., 1993. "Market research evaluation of actions to reduce suburban traffic congestion: Commuter travel behavior and response to demand reduction actions," Transportation Research Part A: Policy and Practice, Elsevier, vol. 27(5), pages 383-393, September.
    • Handle: RePEc:eee:transa:v:27:y:1993:i:5:p:383-393
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    Cited by:

    1. Dacko, Scott G. & Spalteholz, Carolin, 2014. "Upgrading the city: Enabling intermodal travel behaviour," Technological Forecasting and Social Change, Elsevier, vol. 89(C), pages 222-235.
    2. Van Malderen, Laurent & Jourquin, Bart & Thomas, Isabelle & Vanoutrive, Thomas & Verhetsel, Ann & Witlox, Frank, 2012. "On the mobility policies of companies: What are the good practices? The Belgian case," Transport Policy, Elsevier, vol. 21(C), pages 10-19.
    3. Bhat, Chandra R. & Castelar, Saul, 2002. "A unified mixed logit framework for modeling revealed and stated preferences: formulation and application to congestion pricing analysis in the San Francisco Bay area," Transportation Research Part B: Methodological, Elsevier, vol. 36(7), pages 593-616, August.
    4. Xiao, Ling-Ling & Liu, Tian-Liang & Huang, Hai-Jun, 2016. "On the morning commute problem with carpooling behavior under parking space constraint," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 383-407.
    5. Abrahamse, Wokje & Keall, Michael, 2012. "Effectiveness of a web-based intervention to encourage carpooling to work: A case study of Wellington, New Zealand," Transport Policy, Elsevier, vol. 21(C), pages 45-51.
    6. Jun Guan Neoh & Maxwell Chipulu & Alasdair Marshall, 2017. "What encourages people to carpool? An evaluation of factors with meta-analysis," Transportation, Springer, vol. 44(2), pages 423-447, March.
    7. Can, Vo Van, 2013. "Estimation of travel mode choice for domestic tourists to Nha Trang using the multinomial probit model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 49(C), pages 149-159.
    8. Zixuan Peng & Wenxuan Shan & Peng Jia & Bin Yu & Yonglei Jiang & Baozhen Yao, 2020. "Stable ride-sharing matching for the commuters with payment design," Transportation, Springer, vol. 47(1), pages 1-21, February.
    9. Lazarus, Jessica R. & Caicedo, Juan D. & Bayen, Alexandre M. & Shaheen, Susan A., 2021. "To Pool or Not to Pool? Understanding opportunities, challenges, and equity considerations to expanding the market for pooling," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 199-222.
    10. Zhao, Yan & Guo, Xiaolei & Liu, Henry X., 2021. "The impact of autonomous vehicles on commute ridesharing with uncertain work end time," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 221-248.
    11. Xiao, Ling-Ling & Liu, Tian-Liang & Huang, Hai-Jun & Liu, Ronghui, 2021. "Temporal-spatial allocation of bottleneck capacity for managing morning commute with carpool," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 177-200.
    12. Xiping Yang & Zhixiang Fang & Ling Yin & Junyi Li & Yang Zhou & Shiwei Lu, 2018. "Understanding the Spatial Structure of Urban Commuting Using Mobile Phone Location Data: A Case Study of Shenzhen, China," Sustainability, MDPI, vol. 10(5), pages 1-14, May.
    13. Maurizio Faccio & Serena Finco & Ilenia Zennaro, 2021. "Sustainable People Home-Work Logistics: An Integrated Model of Circular Economy in the Chiampo Valley," Sustainability, MDPI, vol. 13(21), pages 1-13, October.
    14. Tsao, H. S. Jacob, 1996. "Constraints On Initial Ahs Deployment And The Concept Definition Of A Shuttle Service For Ahs Debut," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt7rx3w3m2, Institute of Transportation Studies, UC Berkeley.
    15. Sarah-Anne de Kremer & Tracy Ross & Marcus Paul Enoch & Fredrik Monsuur, 2024. "Factors Affecting Propensity to Lift-Share for Children’s Activities," Sustainability, MDPI, vol. 16(5), pages 1-21, March.

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