Latent Variable Models in Travel Behavior Analysis
Summary
Latent variable models offer a powerful framework for capturing the unobserved psychological and social factors that drive individual travel choices. By integrating structural equation modelling with discrete choice theory, these approaches reveal how attitudes, perceptions and social influences shape mode preferences, departure times and route decisions. Such models accommodate complex causal pathways, allowing latent constructs—such as environmental concern, perceived convenience or safety—to enter utility functions alongside observable attributes like travel time and cost. Advances in estimation techniques have improved the consistency and efficiency of parameter recovery, even when integrating large‐scale household surveys or panel data. Globally, this research informs transport policy by quantifying thresholds at which improvements in service quality will shift commuters towards sustainable modes, guiding infrastructure investment, fare strategies and behavioural interventions. The interplay between latent factors and travel behaviour continues to evolve through methodological innovations that enhance predictive accuracy and real‐world applicability.
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Latent Variable Models in Travel Behavior Analysis publication trend
The graph below shows the total number of articles in latent variable models in travel behavior analysis across all publications each year (not limited to Nature Index journals).
Technical terms
Latent variable: Unobserved construct inferred indirectly through multiple observed indicators, capturing attitudes, perceptions or social norms.
Structural equation model (SEM): Statistical framework that specifies relationships between observed variables and latent constructs, and among latent constructs themselves.
Discrete choice model: Quantitative method for predicting individual decisions among a finite set of alternatives by maximising a utility function.
Hybrid choice model: Integrated approach that combines discrete choice modelling with latent variable estimation to account for unobserved psychological or attitudinal factors.
Psychological network model: Analytical technique representing psychological indicators and behaviours as a network of interrelated nodes, enabling examination of dynamic causal links without latent constructs.
References
- A new perspective on the role of attitudes in explaining travel behavior: A psychological network model. Transportation Research Part A Policy and Practice (2020).
- Incorporating social interaction into hybrid choice models. Transportation (2014).
- Research on Passenger’s Travel Mode Choice Behavior Waiting at Bus Station Based on SEM-Logit Integration Model. Sustainability (2018).
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