A text mining study of online reviews to understand intercity bus service quality

Abstract

Promoting urban and intercity public transport (PT) by enhancing its service quality (SQ) is essential for reducing problems like pollution, traffic congestion, and accidents associated with reliance on private vehicles. However, SQ has been mostly studied in urban PT, with only a few studies focusing on intercity PT. Moreover, the few studies dealing with the subject have mainly relied on the survey method. In contrast, the current research attempts to study intercity bus service quality (BSQ) by using information-rich user-generated content (UGC) in the form of online reviews as a data source. Reviews for the terminals of the largest intercity bus network of Pakistan have been scraped from Google Maps. Techniques like topic modelling, sentiment analysis, and regression analysis have been applied to identify dimensions of intercity BSQ and evaluate their impact on customer satisfaction. The results show that Timeliness, Ticketing, Staff, Bus Condition, Waiting Area, Terminal Location, Travel Experience, Terminal Shop and Other Terminal Facilities are the important dimensions of intercity BSQ. The results also show that Timeliness, Ticketing, Bus Condition, and Terminal Shop act as dissatisfiers, whereas Travel Experience, Terminal Location, Waiting Area, and Staff dimensions act as satisfiers while, Other Terminal Facilities could not be classified. The study adds novel insights to the theory and provides the basis for policymaking to improve intercity BSQ.