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Journal Article

Citation

Hyun K, Subedi R, Lee K, Harwerth J, Gibson NO, Krejci C. Adv. Transp. Stud. 2022; 56: 107-126.

Copyright

(Copyright © 2022, Arcane Publishers)

DOI

unavailable

PMID

unavailable

Abstract

Mobility disparities among older adults affect their ability to travel and access services. This study sought to understand what forms of assistance or educational strategies can fill the varying mobility gaps and meet the mobility needs of low income older adults by investigating their transportation activities and perceived barriers in Dallas, Texas. This study characterized older adults' use of existing and potential transportation options, including conventional transit, paratransit, and ride-hailing systems, based on surveys collected from 146 low income older adults in Dallas, Texas. Using the survey data, we conducted a Latent Class Cluster Analysis to understand low income older adults' mode choice decisions, which included current uses and adoption likelihoods based on their perceived barriers to existing mobility options and socioeconomic characteristics.

RESULTS characterized three distinct mode choice patterns including car-dependent, transit-dependent, and private mixed modes users. Those who drive showed their heavy reliance on a personal vehicle with little to no interest in other transportation modes. The transit-dependent group indicated financial difficulties and lacked knowledge of technology while demonstrating a very low adoption likelihood for ride-hailing services. The private mixed mode group representing those who either drive or rely on their family or friends for a ride exhibited a variety of barriers and concerns about the existing modes but were open to adopt public and para-transit. Based on the findings, we discussed several strategies that can potentially reduce observed barriers and challenges, and enhance mobility to ultimately increase social equity across transportation-disadvantaged populations, particularly among low income older adults.


Language: en

Keywords

Case Study; Driver; Driver Behaviour

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