Modelling Passenger Satisfaction in Light Rail Transit Using an Integrated TAN Bayes and PLS-SEM Approach

Light rail transit (LRT) is seen as an environmentally friendly public transport alternative compared to other motorised modes due to reduced air pollution, lower energy consumption, and greenhouse gas emissions. This study aims to investigate regular users' perception of LRT and whether socio-demographic variables influence its use. A questionnaire with attitudinal statements categorised into six main themes, namely service quality, network and infrastructure, accessibility, user benefits, sustainability aspects, and socio-demographics, was piloted and distributed using online channels across the Tyne and Wear Metro catchment area. Using a combination of Tree Augmented Naïve (TAN) Bayes and Partial Least Square Structural Equation Modelling (PLS-SEM) techniques, the interrelationships between statistically significant perception variables affecting regular users' metro use were identified. The analysis emphasises the influential role of accessibility, direct benefits, policy implementation, reliability and availability, sustainability, and security and safety in enhancing user satisfaction. Notable interrelationships were also found, including positive associations between comfort-customer care and reliability-availability, and between safety-security and accessibility. Valuable insights into factors affecting metro use provide transport planners and policymakers with scientific evidence to make informed decisions on improving the metro system's efficiency and effectiveness, enabling cost-effective investments to make LRT more attractive and increase patronage.