Recent developments in urban transportation services are rapidly transforming the way people make their trips. Around the world, the most controversial and rapidly growing mobility services in recent years are ride-hailing services (RHS) offered by transportation network companies (TNCs) such as Uber and Ola. This research estimates the demand for RHS vis-à-vis other modes and further expands to estimate usage propensity of RHS in the capital city of India, New Delhi. A discrete choice modeling framework is developed based on a household travel surveys (N = 426) conducted in 2019. Two models were developed, a multinomial logit (MNL) model, to estimate the factors that lead to the adoption of RHS, and an ordered logit (OL) model, to estimate the frequency of usage of RHS. The results reveal a comprehensive set of socio-demographic and behavioral factors which leads to greater adoption of RHS. The variables such as household income, vehicle ownership, and use of smartphone are found to be important predictors (with a 95% significance level) of service adoption of RHS. The model results also suggest that RHS are likely to be used infrequently, and when it is being used, they are more likely to be used by the younger population and during the weekends. Overall, this research brings valuable and novel insights into the adoption and usage of RHS in India.     «

Recent developments in urban transportation services are rapidly transforming the way people make their trips. Around the world, the most controversial and rapidly growing mobility services in recent years are ride-hailing services (RHS) offered by transportation network companies (TNCs) such as Uber and Ola. This research estimates the demand for RHS vis-à-vis other modes and further expands to estimate usage propensity of RHS in the capital city of India, New Delhi. A discrete choice modeling...     »