From commute to contentment: Evaluating service quality in Lisbon’s rapid transit system through non-solicited user feedback

Abstract

This study explores citizen satisfaction with Lisbon’s public transportation system by analyzing 3,230 user comments from Google Maps on 50 Subway and Train Stations (STSs). This study identifies key strengths and areas for improvement in public transportation services by utilizing Sentiment Analysis (SA) and the SERVQUAL model as a framework for analysis through a mixed-method approach. Our findings highlight the predominance of tangibles, such as cleanliness and modern facilities, in shaping user experiences. Reliability and empathy also emerged as significant factors influencing satisfaction. The innovative integration of SA with SERVQUAL dimensions as an analytical framework for analysis provides a comprehensive assessment of user feedback, offering practical contributions for urban managers to enhance service quality and theoretical implications for scholars. Despite limitations related to user-generated content and manual data collection, our study underscores the potential of SA in urban management and calls for further research with larger datasets and automated methods.