Key points are not available for this paper at this time.
Rapid urbanization and increasing demand for efficient public transportation have highlighted the need to understand public perceptions of service quality. Traditional evaluation methods may not fully capture user experiences and perceptions, and the emerging large-scale social media data offers dynamic user-generated information for new insights. To address this, this study explored the perceived service quality of the Shanghai metro system using a data-driven approach based on user-generated content from Dianping.com. We analyzed 52,087 online reviews by employing the structural topic model (STM) to identify key service quality attributes and their impact on user satisfaction. Our findings reveal eleven significant topics: 'Self-expression', 'Transfer', 'Amenity', 'Shopping Mall', 'Check-in', 'Operation', 'Security Check', 'Staff', 'Environment & Facility', 'Design', and 'Peak & Commuting'. Polarity analysis indicates that 'Self-expression', 'Check-in', and 'Design' are viewed positively, while 'Security check', 'Commuting', and 'Transfer' are perceived negatively. Temporal dynamics of topics demonstrated that the users prioritized and focused more on aesthetic and attitude than the physical environment of transport services. Furthermore, hierarchical clustering reveals distinct spatial patterns, with stations in residential areas emphasizing commuting and travel needs, business district stations focusing on design and operational aspects, and other stations highlighting cleanliness and security concerns. These findings provide practical insights into enhancing urban transport management by aligning service offerings more closely with user preferences and improving sustainable urban development.
Dou et al. (Tue,) studied this question.