Empirical analysis and comparisons about time-allocation patterns across segments based on mode-specific preferences

A three-stage approach, i.e., factor-cluster-multi-group Structural Equation Modeling (SEM), is designed to explore the commonalities and diversities with respect to relationships between socio-demographic characteristics and time-use patterns across different segments. Factor-cluster analysis is conducted to extract meaningful factors from attitudinal statements, and then group the sample population into three segments, each with a unique combination of mode preferences for public transit, private car, and motorcycle. By virtue of multi-group SEM, the relationships between socio-demographics and time allocated to activities and travel are found to be significantly different across segments. This study highlights the importance of latent psychological factors in segmentation. For policy implication, specific population with unique psychological features must be targeted in order to efficiently and effectively design and implement transport measures.