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June 17, 2026Multimodal TransportationOpen Access

On Heterogeneity in Discrete Choice Modeling for Transportation

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Authors

JZJiajie ZhangQTQingyun Tian

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Overview

Methodological advances improve modeling user heterogeneity in transportation, highlighting new dimensions for analysis.

Key Points

  • To explore user heterogeneity in discrete choice modeling frameworks and its implications for transportation research.
  • Discussed traditional observable and latent heterogeneity alongside a new dimension of decision-mechanism heterogeneity.
  • Surveyed classical parametric models, distribution-free choice modeling, neural-embedded discrete choice models, and tree-structured models.
  • Synthesized findings into a comparison table for methodological advancements.
  • Introduced a perturbed-utility representation framework for understanding heterogeneity in decision-making.
  • Identified the importance of a learn-from-data paradigm over traditional specify-then-estimate approaches.
  • Outlined three future research directions to enhance transportation research through new methodologies.

Cite This Study

Zhang et al. (2026) studied this question.

synapsesocial.com/papers/6a3239c2d50b63ecad20510dhttps://doi.org/10.1016/j.multra.2026.100328
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