Autonomous Taxi Adoption: A Real-World Analysis
Analysis
This paper is significant because it moves beyond hypothetical scenarios and stated preferences to analyze actual user behavior with operational autonomous taxi services. It uses Structural Equation Modeling (SEM) on real-world survey data to identify key factors influencing adoption, providing valuable empirical evidence for policy and operational strategies.
Key Takeaways
- •The study uses real-world data from Baidu's Apollo Robotaxi service in Wuhan, China.
- •Structural Equation Modeling (SEM) is used to analyze survey data.
- •Key factors influencing adoption include Cost Sensitivity and Behavioral Intention.
- •Findings provide empirical evidence for policymaking, fare design, and public outreach.
Reference
“Cost Sensitivity and Behavioral Intention are the strongest positive predictors of adoption.”