|
Abstract:
|
Ride-hailing services have become an important mobility option. This paper examines ride-hailing usage of various socio-economic groups, including women, the elderly, race minorities, etc. Sample of seven states from the 2017 national household travel survey are analyzed (n = 183,447). For each state, mixed logit model is developed to investigate the effects of socio-economic characteristics on ride-hailing usage. According to Bayesian theorem, we calculate posterior compensating variation (CV) for each socio-demographic group. The CV, which measures the level of disparity in ride-hailing usage, represents the additional money needed for a group (e.g., females) to gain the same utility from using ride-hailing as another socio-demographic group (e.g., males). Results suggest significant variation in CV across counties, indicating that the severeness of disparities vary spatially. Lastly, multiple linear regression models are developed to explore factors that are related to variations in CVs across counties. Findings help better understand the disparities in ride-hailing usage and thus inform policy-making for a more inclusive ride-hailing services for all travelers.
|
