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Recent disruptions in the transportation sector, such as the growing popularity of ridesourcing services, have substantially impacted traditional transportation services (such as taxis). However, the factors that determine usage rates of ridesourcing options are still not fully understood. The intent of the current paper is to develop a statistical model of individuals’ usage rates of ridesourcing services. Methods: Using a sample of recently collected data, a mixed logit model (multinomial logit model with random parameters) of ridesourcing-usage rate was estimated and, in addition to traditional socio-demographic factors, travel and health-related variables were also considered.

Besides some socio-demographic variables, the travel and health-related variables were found to play statistically significant roles in ridesourcing usage. Specifically, age, gender, income, household size, vehicle ownership …