Analyzing Factors Influencing the Adoption of Shared Car Services: A Causal Inference Approach

Understanding the factors that influence people's decisions to use shared automobile services is crucial, given the rising popularity of this creative and environmentally friendly mode of transportation. This paper explores the adoption of shared car-sharing services by applying meta-learners to estimate treatment effects and understand the causal relationships between different variables. The findings show that the travel purpose and distance greatly influence t he choice o f shared a utomobile services. The X-learner is the most accurate in predicting when we evaluate the predictive performance of various meta-learners. Based on this methodology, future studies could expand to include additional influencing factors or compare the relationships between different services and influencing factors.