Time-Series Analysis of the Causal Effects Among Perceived Quality, Satisfaction, Loyalty, and Frequency of Public Transportation Use

• Published in: Frontiers in built environment Vol. 6
• Main Authors: Kawabata, Yuichiro, Ryo, Takuya, Friman, Margareta, Olsson, Lars E., Lättman, Katrin, Fujii, Satoshi
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 17.09.2020
• Subjects: psychological modification; Psychology; Psykologi; public transport recommendation; public transport satisfaction; public transport user frequency; time-series analysis; vector auto regressive modeling; public transport recommendation; public transport satisfaction; public transport user frequency; behavioral modification; psychological modification; vector auto regressive modeling; time-series analysis
• ISSN: 2297-3362; 2297-3362
• DOI: 10.3389/fbuil.2020.00137

How to drive modal shift is one of the primary issues in creating a sustainable society. By encouraging people to migrate from private car use to public transport, city planners can prepare for a super-aged society, reduce greenhouse gas emissions, and mitigate negative externalities of private car use such as congestion, accidents, and noise. To achieve these goals, city planners are required to understand whether public transport usage can be increased by improving the service quality and what roles user satisfaction and loyalty play in the process. The relations between service quality, user satisfaction, loyalty, and user frequency have been studied for a long time. However, most of the studies are based on cross-sectional analysis. Cross-sectional analysis is less powerful in detecting causality as it does not show pre-post relations or lagged effects between variables. To investigate causal and non-simultaneous relations among quality, satisfaction, loyalty, and user frequency of public transport, we used data of theBenchmarking in European Service of Public Transportsurvey from 2001 to 2015 in four European cities, and applied vector auto regressive (VAR) analysis. The result shows that improvement of service quality has positive effects on user's satisfaction, loyalty, and user frequency and that better satisfaction leads to higher loyalty and user frequency. More importantly, the result also shows that behavioral modification (change in user frequency) occurs with time lag while psychological modifications (changes in satisfaction and loyalty) occur immediately after changes in service quality. The findings suggest that city/transport planners ought to keep improving the service quality of public transport and monitoring the achievement from a long-term perspective.