Extending the Theory of Planned Behavior to Explore the Influence of Residents’ Dependence on Public Transport

Abstract

The accurate depiction and understanding of the influence mechanism of residents’ dependence on public transport (RDPT) is an important foundation for increasing the proportion of green trips and alleviating urban traffic congestion. To explore the influence mechanism of RDPT, this paper extends the theory of planned behavior (TPB) by introducing objective factors of attributes, environment, and travel characteristics. The agglomerative nesting clustering algorithm and multiple structural equation modeling (SEM) are then developed to identify the RDPT levels and analyze the influence relationships between the integrated influencing factors and RDPT based on travel survey data. The results indicate that the objective variables have indirect impacts on RDPT by influencing psychological variable attitudes, subjective norms and perceived control and travel intention. The residents’ self-selection (RSS) effects of different clusters are all detected under normal conditions, and the environment on RDPT is still significant after controlling for this effect. The findings reflect that the influence mechanisms of the three SEMs for different clusters are distinct, unlike those of the baseline model, and distinctive observation variables have dissimilar explanatory abilities for the travel intention of different residents. Therefore, some beneficial policy implications are proposed for residents, especially those who retain low and relatively low public transport dependence levels, to increase public transport usage while reduce the car usage based on the significant findings.

Keywords

• Public transport
• dependence
• theory of planned behavior
• agglomerative nesting algorithm
• structural equation modeling