E-hail (rideshare) knowledge, use, reliance, and future expectations among older adults

Jonathon M. Vivoda, Annie C. Harmon, Ganesh M. Babulal, Brian J. Zikmund-Fisher

Research output: Contribution to journalArticle

16 Scopus citations

Abstract

The goals of this study were to explore e-hail (e.g., Uber/Lyft) knowledge, use, reliance, and future expectations among older adults. Specifically, we aimed to identify factors that were related to e-hail, and how older adults view this mode as a potential future transportation option. Data were collected from a sample of older adults using a pencil-and-paper mailed survey. Univariate, bivariate, and regression techniques were used to assess the relationships among e-hail and several demographic and other factors. Almost three-quarters of the sample (74%) reported no e-hail knowledge. Only 1.7% had used e-hail to arrange a ride, and only 3.3% reported that they relied on e-hail for any of their transportation needs. Younger age, male gender, more education, higher transportation satisfaction, and discussing transportation options with others were all independently associated with greater e-hail knowledge. Male gender also predicted e-hail use. E-hail was the mode least relied upon by older adults. Current e-hail knowledge was the biggest predictor of anticipated future use. E-hail may be a viable future option for older adults who have limited or stopped driving. More exposure to e-hail and continued evolution of these services is required to overcome older adults’ lower internet/smartphone use. Policies could be implemented at departments of motor vehicles to pair information or training on transportation alternatives (like e-hail) with elimination of driving privileges, or at doctors’ offices, senior centers, or hospitals. Potential underlying reasons for the findings are also discussed.

Original languageEnglish
Pages (from-to)426-434
Number of pages9
JournalTransportation Research Part F: Traffic Psychology and Behaviour
Volume55
DOIs
StatePublished - May 2018

Keywords

  • Aging
  • Driving
  • Technology
  • Uber/Lyft

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