The Evaluation of User Satisfaction and Prospects Analysis of Shared Bicycle Services

Abstract

Since their introduction, shared bicycle services have rapidly expanded across Chinese cities and have become a key component of urban micro-mobility. By 2025, with the integration of AI-powered dispatch systems, smart parking, and green transport policies, shared bicycles are increasingly embedded within smart city frameworks. This study investigates user satisfaction and its influencing factors to support service optimization and sustainable development. A stratified three-stage unequal probability sampling method was used to survey 1,080 residents in urban and suburban areas of Beijing. Data analysis incorporated descriptive statistics, logistic regression, principal component analysis, fuzzy comprehensive evaluation, and text mining. Results indicate strong market penetration of shared bicycles, with dynamic pricing, deposit systems, and smart parking emerging as key user concerns. Age, occupation, and income remain significant determinants of usage frequency. While users express high satisfaction with app functionality and bicycle hardware, cost-effectiveness and safety continue to affect overall experience. Sentiment analysis reveals increasing expectations for environmentally friendly and intelligent mobility solutions. Based on the findings, the study recommends flexible pricing models, safety enhancements, and targeted service strategies to expand user engagement and support the evolution of shared mobility in urban China.