Latent variables and route choice behavior

Carlo Giacomo Prato, Shlomo Bekhor, Cristina Pronello

    Research output: Contribution to journalJournal articleResearchpeer-review

    Abstract

    In the last decade, a broad array of disciplines has shown a general interest in enhancing discrete choice models by considering the incorporation of psychological factors affecting decision making. This paper provides insight into the comprehension of the determinants of route choice behavior by proposing and estimating a hybrid model that integrates latent variable and route choice models. Data contain information about latent variable indicators and chosen routes of travelers driving regularly from home to work in an urban network. Choice sets include alternative routes generated with a branch and bound algorithm. A hybrid model consists of measurement equations, which relate latent variables to measurement indicators and utilities to choice indicators, and structural equations, which link travelers’ observable characteristics to latent variables and explanatory variables to utilities. Estimation results illustrate that considering latent variables (i.e., memory, habit, familiarity, spatial ability, time saving skills) alongside traditional variables (e.g., travel time, distance, congestion level) enriches the comprehension of route choice behavior.
    Original languageEnglish
    JournalTransportation
    Volume39
    Pages (from-to)299-319
    ISSN0049-4488
    DOIs
    Publication statusPublished - 2012

    Keywords

    • Latent variables
    • Path size correction logit
    • Hybrid model
    • Measurement and structural equations
    • Route choice behavior

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