Skip to main content
Intended for healthcare professionals
Restricted access
Research article
First published online January 1, 2016

Modeling Mode Choice of Low-Income Commuters with Sociodemographics, Activity Attributes, and Latent Attitudinal Variables: Case Study in Fushun, China

Abstract

Low-income residents are dependent on fewer options for travel and have restricted mobility. This study examines the mode choice of low-income commuters based on an activity-based travel survey in Fushun, China. A model of integrated choice and latent variables was utilized to construct and test the significance of sociodemographics, activity attributes, and latent attitudinal variables. More specifically, a “multiple indicators, multiple causes” model was used to construct the latent variables postulated to be important for travel mode choice, and a multinomial logit model was employed to test the significance of explanatory variables. Results indicate that gender, age, and driving license possession play an important role in the formation of these underlying factors: comfort, convenience, reliability, flexibility, safety, and environmental preferences. On several accounts the latent-variable-enriched choice model outperforms the traditional choice model and provides insights into the importance of unobservable variables in the choice process. Preferences for the latent variables except flexibility are found to exert a significant influence on the mode choice of low-income commuters. Reliability is shown to be helpful in increasing the likelihood that low-income commuters will choose public transit. The sociodemographics and activity attributes also have important effects on the choice process. Findings should provide useful information to policy makers and transportation planners to improve the mobility of low-income commuters.

Get full access to this article

View all access and purchase options for this article.

References

1. Behrens R. Understanding Travel Needs of the Poor: Towards Improved Travel Analysis Practices in South Africa. Transport Reviews, Vol. 24, 2004, pp. 317–336.
2. Srinivasan S., and Roger P. Travel Behavior of Low-Income Residents: Studying Two Contrasting Locations in the City of Chennai, India. Journal of Transport Geography, Vol. 13, 2005, pp. 265–274.
3. Salon D., and Gulyani S. Mobility, Poverty, and Gender: Travel ‘Choices’ of Slum Residents in Nairobi, Kenya. Transport Reviews, Vol. 30, 2010, pp. 641–657.
4. Ortuzar J. de D., and Willumsen L. G. Modeling Transport, 2nd ed. John Wiley & Sons, Inc., New York, 1999.
5. McFadden D. The Theory and Practice of Disaggregate Demand Forecasting for Various Modes of Urban Transportation. U.S. Department of Transportation, 1978.
6. Jensen M. Passion and Heart in Transport: A Sociological Analysis on Transport Behavior. Transport Policy, Vol. 6, 1999, pp. 19–33.
7. Hagman O. Mobilizing Meaning of Mobility: Car Users’ Constructions of the Goods and Bads of Car Use. Transportation Research Part D: Transport and Environment, Vol. 8, 2003, pp. 1–9.
8. Verplanken B., Walker I., Davis A., and Jurasek M. Context Change and Travel Mode Choice: Combining the Habit Discontinuity and Self-activation Hypotheses. Journal of Environmental Psychology, Vol. 28, 2008, pp. 121–127.
9. Grdzelishvili I., and Sathre R. Understanding the Urban Travel Attitudes and Behavior of Tbilisi Residents. Transport Policy, Vol. 18, 2011, pp. 38–45.
10. Recker W., and Stevens R. Attitudinal Models of Modal Choice: The Multinomial Case for Selected Nonwork Trips. Transportation, Vol. 5, 1976, pp. 355–375.
11. Paulssen M., Temme D., Vij A., and Walker J. L. Values, Attitudes and Travel Behavior: A Hierarchical Latent Variable Mixed Logit Model of Travel Mode Choice. Transportation, Vol. 41, 2014, pp. 873–888.
12. Johansson M. V., Heldt T., and Johansson P. The Effects of Attitudes and Personality Traits on Mode Choice. Transportation Research Part A: Policy and Practice, Vol. 40, 2006, pp. 507–525.
13. Heinen E., Maat K., and Wee B. The Role of Attitudes Toward Characteristics of Bicycle Commuting on the Choice to Cycle to Work Over Various Distances. Transportation Research Part D: Transport and Environment, Vol. 16, 2011, pp. 102–109.
14. Golob T. F. Joint Models of Attitudes and Behavior in Evaluation of the San Diego I-15 Congestion Pricing Project. Transportation Research Part A: Policy and Practice, Vol. 35, 2001, pp. 495–514.
15. Galdames C., Tudela A., and Carrasco J.-A. Exploring the Role of Psychological Factors on Mode Choice Models by Using a Latent Variables Approach. In Transportation Research Record: Journal of the Transportation Research Board, No. 2230, Transportation Research Board of the National Academies, Washington, D.C., 2011, pp. 68–74.
16. Golob T. F., and Hensher D. A. Greenhouse Gas Emissions and Australian Commuters’ Attitudes and Behavior Concerning Abatement Policies and Personal Involvement. Transportation Research Part D: Transport and Environment, Vol. 3, 1998, pp. 1–18.
17. Sakano R., and Benjamin J. M. A Structural Equations Analysis of Revealed and Stated Travel Mode and Activity Choices. Transportmetrica, Vol. 4, 2008, pp. 97–115.
18. Mok T. K. Poverty and Social Security in Hong Kong. Chung Hwa Book Company, Hong Kong, 1993.
19. Nunnally J. C. Psychometric Theory, 2nd ed. McGraw-Hill, New York, 1978.
20. Morikawa T., Ben-Akiva M., and McFadden D. Discrete Choice Models Incorporating Revealed Preferences and Psychometric Data. Econometric Models in Marketing Advances in Econometrics: A Research Annual, Vol. 16, 2002.
21. Schumacker R. E., and Lomax R. G. A Beginner’s Guide to Structural Equation Modeling, 3rd ed. Taylor & Francis Group, New York, 2010.
22. Bhat C. R., and Lockwood A. On Distinguishing Between Physically Active and Physically Passive Episodes and Between Travel and Activity Episodes: An Analysis of Weekend Recreational Participation in the San Francisco Bay Area. Transportation Research Part A: Policy and Practice, Vol. 38, 2004, pp. 573–592.

Cite article

Cite article

Cite article

OR

Download to reference manager

If you have citation software installed, you can download article citation data to the citation manager of your choice

Share options

Share

Share this article

Share with email
EMAIL ARTICLE LINK
Share on social media

Share access to this article

Sharing links are not relevant where the article is open access and not available if you do not have a subscription.

For more information view the Sage Journals article sharing page.

Information, rights and permissions

Information

Published In

Article first published online: January 1, 2016
Issue published: January 2016

Rights and permissions

© 2016 National Academy of Sciences.
Request permissions for this article.

Authors

Affiliations

Long Cheng
Jiangsu Key Laboratory of Urban Intelligent Transport Systems, Southeast University, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Si Pai Lou No. 2, Nanjing 210096, China
Xuewu Chen
Jiangsu Key Laboratory of Urban Intelligent Transport Systems, Southeast University, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Si Pai Lou No. 2, Nanjing 210096, China
Shuo Yang
Jiangsu Key Laboratory of Urban Intelligent Transport Systems, Southeast University, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Si Pai Lou No. 2, Nanjing 210096, China
Haixiao Wang
Jiangsu Key Laboratory of Urban Intelligent Transport Systems, Southeast University, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Si Pai Lou No. 2, Nanjing 210096, China
Jingxian Wu
Jiangsu Key Laboratory of Urban Intelligent Transport Systems, Southeast University, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Si Pai Lou No. 2, Nanjing 210096, China

Notes

Metrics and citations

Metrics

Journals metrics

This article was published in Transportation Research Record: Journal of the Transportation Research Board.

VIEW ALL JOURNAL METRICS

Article usage*

Total views and downloads: 89

*Article usage tracking started in December 2016


Altmetric

See the impact this article is making through the number of times it’s been read, and the Altmetric Score.
Learn more about the Altmetric Scores



Articles citing this one

Receive email alerts when this article is cited

Web of Science: 0

Crossref: 12

  1. Drivers’ willingness to shift towards electronic toll collection syste...
    Go to citation Crossref Google Scholar
  2. What would it take for the people of Riyadh city to shift from their c...
    Go to citation Crossref Google Scholar
  3. Comparison of station-based and free-floating bikeshare systems as fee...
    Go to citation Crossref Google Scholar
  4. Estimation of rider’s shifting intention for electric bike adoption: A...
    Go to citation Crossref Google Scholar
  5. Investigating the determinants of travel mode choice across age classe...
    Go to citation Crossref Google Scholar
  6. Determining mode shift elasticity based on household income and travel...
    Go to citation Crossref Google Scholar
  7. Design and optimisation of multimodal traffic strategy for low‐mobilit...
    Go to citation Crossref Google Scholar
  8. Predicting the use frequency of ride-sourcing by off-campus university...
    Go to citation Crossref Google Scholar
  9. Transit Route Network Design for Low-Mobility Individuals Using a Hybr...
    Go to citation Crossref Google Scholar
  10. Structural equation models to analyze activity participation, trip gen...
    Go to citation Crossref Google Scholar
  11. Transportation Demands of Low-Mobility Individuals: Case Study in Wenl...
    Go to citation Crossref Google Scholar
  12. Improving Travel Quality of Low-Income Commuters in China...
    Go to citation Crossref Google Scholar

Figures and tables

Figures & Media

Tables

View Options

Get access

Access options

If you have access to journal content via a personal subscription, university, library, employer or society, select from the options below:


Alternatively, view purchase options below:

Purchase 24 hour online access to view and download content.

Access journal content via a DeepDyve subscription or find out more about this option.

View options

PDF/ePub

View PDF/ePub