Heterogeneity in passenger satisfaction of bus rapid transit system among age and gender groups: A PLS-SEM Multi-group analysis

Abstract

Public transport is a promising way to solve urban mobility problems such as traffic congestion and vehicular emissions. However, in order to encourage commuters to use the public transport facility, operators need to provide a high level of service to ensure their satisfaction, which is one of the crucial factors influencing the mode choice of commuters. Despite this, there is limited understanding of the factors influencing passenger satisfaction in public transportation, especially in developing countries like India. To address this gap in knowledge, the present study explores the factors affecting passenger satisfaction on bus rapid transit system (BRTS), and examines the differences in the perception of satisfaction for passengers of different age and gender groups. The present study utilizes Principal component analysis (PCA) and Partial Least Square Structural Equation Modelling (PLS-SEM) to explore passengers' satisfaction based on 26 key attributes of the BRTS. PCA uncovers six dimensions explaining the overall satisfaction of passengers, i.e., connectivity, comfort & convenience, safety, cleanliness, station facilities, and operations and the results of PLS-SEM reveal that all these dimensions positively influence passenger satisfaction. The results of multigroup analysis reveal that there exist heterogeneity in the perception of satisfaction for passengers of different gender and age groups. Unlike female passengers, who perceived connectivity and comfort & convenience higher, male passengers perceived operations and station facilities higher. Furthermore, it was found that passengers with age ≥ 40 perceived station facilities and cleanliness higher than passengers with age <40. Taking into account the heterogeneity among passengers of different groups. the study suggests various measures to ensure passenger satisfaction on the BRTS based on Importance Performance Map analysis (IPMA). © 2023 Elsevier Ltd