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The generators of paratransit trips by persons with disabilities

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  • Deka, Devajyoti
  • Gonzales, Eric J.

Abstract

Identifying the generators of paratransit trips by persons with disabilities is important to comprehend the current demand patterns and forecast future demand. Only a handful of studies have been conducted so far to identify the generators of paratransit trips and most focused on the home end of the trips. Given some of the inconsistencies in past studies and the scarcity of studies on the generators of trips away from home, this study attempts to identify the generators of paratransit trips beginning and ending at clients’ homes and away from home. It uses an extremely large dataset consisting of 1.91 million trips made by NJ TRANSIT’s Access Link clients, socioeconomic data from the American Community Survey, employment data from the Longitudinal Employer-Household Dynamics, and establishment data from Dun and Bradstreet. The analytical methods include an ordinary least squares model (OLS) and several spatial generalized linear mixed models (GLMM) to identify the characteristics of census block groups associated with Access Link trip generation at home and away from home, Geographic Information System (GIS) analysis to identify the types of establishments located in the immediate vicinity of drop-offs, and a multinomial logit model (MNL) to examine the relationship between the characteristics of the establishments in the vicinity of drop-offs and the characteristics of the dropped-off clients. Together, the various analyses provide useful insights about paratransit trip generators at the macro and micro levels. Some implications of the findings are discussed.

Suggested Citation

  • Deka, Devajyoti & Gonzales, Eric J., 2014. "The generators of paratransit trips by persons with disabilities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 70(C), pages 181-193.
    • Handle: RePEc:eee:transa:v:70:y:2014:i:c:p:181-193
    DOI: 10.1016/j.tra.2014.10.018
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    References listed on IDEAS

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    5. Gupta, Diwakar & Chen, Hao-Wei & Miller, Lisa A. & Surya, Fajarrani, 2010. "Improving the efficiency of demand-responsive paratransit services," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(4), pages 201-217, May.
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    Cited by:

    1. Rahimi, Mahour & Amirgholy, Mahyar & Gonzales, Eric J., 2018. "System modeling of demand responsive transportation services: Evaluating cost efficiency of service and coordinated taxi usage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 112(C), pages 66-83.
    2. Wang, Yiyuan & Shen, Qing & Abu Ashour, Lamis & Dannenberg, Andrew L., 2022. "Ensuring equitable transportation for the disadvantaged: Paratransit usage by persons with disabilities during the COVID-19 pandemic," Transportation Research Part A: Policy and Practice, Elsevier, vol. 159(C), pages 84-95.
    3. Darcy, Simon & Burke, Paul Francis, 2018. "On the road again: The barriers and benefits of automobility for people with disability," Transportation Research Part A: Policy and Practice, Elsevier, vol. 107(C), pages 229-245.
    4. Márquez, Luis & Pineda, Laura X. & Poveda, Juan C., 2022. "Mobility-impaired people’s preferences for a specialized paratransit service as BRT’s feeder: The role of autonomy, relatedness, and competence," Transportation Research Part A: Policy and Practice, Elsevier, vol. 165(C), pages 172-185.
    5. Daniel Y. Mo & H. Y. Lam & Weikun Xu & G. T. S. Ho, 2020. "Design of Flexible Vehicle Scheduling Systems for Sustainable Paratransit Services," Sustainability, MDPI, vol. 12(14), pages 1-18, July.

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