A dual-analytic approach to reveal core determinants of public transport modal share and policy priorities

Public transportation offers a key means of alleviating urban congestion and pollution in the face of climate change. However, simply enhancing transit services often fails to increase modal share if critical bottlenecks remain unresolved. To address this by distinguishing between what is sufficient and what is necessary, this study combines partial least squares structural equation modeling (PLS-SEM) and necessary condition analysis (NCA), integrating local governments’ ex post transportation evaluation systems, to identify both the sufficient bundles and the necessary prerequisites affecting public transportation modal share. The analysis reveals that key transit attributes, including bus frequency and user satisfaction are pivotal in increasing modal share and thus serve as bottleneck indicators. Conversely, high levels of automobile usage negatively affect the modal share of public transportation, indicating that these must be curtailed to reach medium and high targets. We also find that falling below certain safety and environmental benchmarks significantly constrains any improvement in transit use. Moreover, results suggest a positive feedback loop: municipalities with higher shares of public transportation tend to receive larger transportation budgets in the following year, implying that effective transit policies can yield tangible fiscal benefits. By quantifying both sufficiency and necessity, this study introduces a policy-feedback diagnostic, combining PLS-SEM and NCA, that provides empirical guidance for local governments to set funding gates (minimum standards) and a sequenced investment order for the most impactful interventions.