Citation

Asgari H, Gupta R, Azimi G, Jin X. Transp. Res. Rec. 2022; 2676(3): 772-785.

Copyright

(Copyright © 2022, Transportation Research Board, National Research Council, National Academy of Sciences USA, Publisher SAGE Publishing)

DOI

10.1177/03611981211057530

PMID

unavailable

Abstract

This paper presents an investigation of the use and frequency of use of ride-hail services. In particular, we explored the role of generational effects and the heterogeneity involved in Millennials' decision making when it comes to ride-hail choices. Using an ordered logistic regression structure, different statistical models were developed and tested, including fixed-effects and random parameter models, as well as the inclusion of interaction effects and attitudinal factors. Initial results from the fixed-effects model showed that the younger cohorts, including Millennials and Generation Z, showed a significantly positive preference for more frequent ride-hail use, whereas the older cohorts' preferences (Generation X, Baby Boomers, and older) did not show any significant effects on ride-hail frequency. In the next step, the presence of heterogeneity among Millennials was tested using random parameters. The results confirmed that Millennials' usage of ride-hail was heterogeneous, and this was statistically significant at the 90% confidence interval ( )
To identify sources of heterogeneity, interaction effects were added to the model. Accordingly, use of ride-hail was more popular among middle-aged Millennials (30 to 34 years old) and Millennials with higher incomes. Likewise, attitudes such as cost sensitivity (toward private vehicle ownership), and being a rational user resulted in higher frequency ride-hail use across Millennials. On the contrary, unemployed Millennials were less likely to utilize ride-hail. The results from this study provide a more transparent picture of current ride-hail market segmentation, which could help predict the future market comprising autonomous vehicles and other emerging mobility options.

Keywords

behavior analysis; emerging; planning and analysis; traveler behavior and values