Exploring the Macro Economic and Transport Influencing Factors of Urban Public Transport Mode Share: A Bayesian Structural Equation Model Approach

Abstract

The public transportation priority strategy is a significant way to alleviate urban traffic congestion, and the urban public transport mode share (UPTMS) is a crucial indicator to measure the performance of public transportation priority strategies. To explore the influence factors of UPTMS, this study hypothesized that UPTMS is influenced by factors such as population, economy, road operation performance, public transport infrastructure, and private transport facilities, and tested the hypotheses using structural equation modeling (SEM) and Bayesian structural equation modeling (BSEM) based on urban macro economic and transport data in Guangzhou and Beijing, China. The results showed that, in the case of a small sample, BSEM is more adept at examining the correlation between the UPTMS and its influencing factors than SEM; in the Guangzhou and Beijing models, public transport infrastructure has the greatest positive and most significant impact on the UPTMS, and road operation performance has the greatest negative and most significant impact. Moreover, road operation performance is significantly improved by public transport infrastructure, while private transport facilities have a significant negative influence on road operation performance.