Customer Choice of Different Types of Non-Autonomous and Autonomous Transportation Network Company Services in the San Francisco Bay Area

In recent years, transportation network companies (TNCs) have grown rapidly. However, with the high intensity of competition caused by multi-homing and low switching costs, providers like Uber and Lyft have yet to achieve profitability. Following the winner-takes-all theory, providers fight for market dominance with price wars and incentives, expecting to achieve profitability once they gain market power. However, despite extensive research on why customers use TNCs instead of other modes, there is limited research on customer choice between competing TNCs. This study examines how customers choose among competing providers and service options for booking rides, considering the influence of service characteristics. The research questions are answered for the San Francisco Bay Area, various TNC and autonomous TNC (ATNC) services (Basic, Green, Premium, and Pool), and use cases based on time urgency and trip purpose. For this, we conducted a choice-based conjoint (CBC) analysis with 1,415 participants. Results indicate that an almost equal number of customers choose services based on loyalty or habit as those customers who switch services based on better waiting times or prices. The results confirm the importance of provider size on customer choice and indicate a high time- and price-sensitivity of customers. On average, Green services are most preferred, followed by Basic, Premium, and Pool. When comparing TNC and ATNC services, customers are positive toward autonomous services but require lower prices to switch. These findings contribute to the understanding of customer choice in competitive TNC and future ATNC markets, with relevance for both theory and practitioners.

Bogenberger, Klaus, Hanna Hottenrott, Pia Negro and Bernd Kaltenhäuser (2024), Customer Choice of Different Types of Non-Autonomous and Autonomous Transportation Network Company Services in the San Francisco Bay Area, Transportation Research Record