Javad Jomehpour: Listen to Scooter Riders

In this study, app store reviews from two major micro-mobility companies are investigated using machine learning techniques to identify the factors that influence rider satisfaction. The Latent Dirichlet Allocation model is applied to over 12,000 rider-generated reviews to identify twelve topics discussed within the reviews. These topics cover areas such as pricing, safety, customer service, refund, payment, app interface, and ease of use, to name a few. Using logistic regression, the most significant factors influencing rider satisfaction were identified. Moreover, name-based gender prediction analysis is employed to identify rider gender and then discover differences in review content and factors of satisfaction across gender. Findings contribute to the existing literature by demonstrating the use of app store reviews in a transportation mobility study. The development of a method to assess factors contributing to user or rider satisfaction offers the ability to evaluate e-scooter rider needs and barriers to access and participation.