Subjective variables in travel behavior models

A critical review and Standardized Transport Attitude Measurement Protocol (STAMP)

Bibliographic Data

ID19337449
AuthorsMatthew Conway (0000-0002-1210-2982, University of North Carolina at Chapel Hill, corresponding author), Laura Mirtich (0000-0002-0467-2934, Arizona State University), Deborah Salon (0000-0002-2240-8408, Arizona State University), Nathan Harness (Arizona State University), Alexis Consalvo (Arizona State University), Shuyao Hong (0000-0001-7289-2229, Arizona State University)
Year2024
Volume51
Issue1
Pages155-191
Publication date2024-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueTransportation (JOURNAL)
Journal identifiersISSN: 0049-4488 • E-ISSN: 1572-9435
PublisherSpringer Science and Business Media LLC (PUBLISHER)
DOI10.1007/s11116-022-10323-7
PMID36196062
OpenAlexW4297973774
LanguageEN
Citations received10
References cited153

Understanding people's travel behavior is necessary for achieving goals such as increased bicycling and walking, decreased traffic congestion, and adoption of clean-fuel vehicles. To understand underlying motivations, researchers increasingly are adding subjective variables to models of travel behavior. This article presents a systematic review of 158 such studies. Nearly every reviewed article finds subjective variables to be predictive of transport outcomes. However, the 158 reviewed studies include 2864 distinct subjective survey questions. This heterogeneity makes it difficult to reach definitive conclusions about which subjective variables are most important for which transport outcomes. In addition to heterogeneity, challenges of this literature also include an unclear direction of causality and tautological relationships between some subjective variables and behavior. Within the constraints imposed by these challenges, we attempt to evaluate the explanatory power of subjective variables, which subjective variables matter most for which transport choices, and whether the answers to these questions vary between continents. To reduce heterogeneity in future studies, we introduce the Standardized Transport Attitude Measurement Protocol, which identifies a curated set of subjective questions. We have also developed an open-access database of the reviewed studies, including all subjective survey questions and models, with an interactive, searchable interface

Causality (physics) · Econometrics · Economics · Explanatory power · Machine learning · Predictive power · Protocol (science) · Set (abstract data type) · Transport engineering · Travel behavior · Variable (mathematics) · Variables · Applied Psychology · Computer Science · Economic and Environmental Valuation · Engineering · Mathematics · Medicine · Psychology · Transportation Planning and Optimization · Urban Transport and Accessibility

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