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Driving Behavior Change: Modeling the Psychological Determinants of Sustainable Attendee Transportation to Special Events

2025· article· en· W4407071874 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEvent Management · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicUrban Transport and Accessibility
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTourismStructural equation modelingMarketingPsychologyBusinessAdvertisingEconomic geographyPolitical scienceEconomicsComputer science

Abstract

fetched live from OpenAlex

Characterized by extensive private-car use, attendee transportation represents the largest greenhouse gas contributor of special events, among numerous other environmental, social, and economic concerns. While travel demand management interventions have been implemented by event organizers to shift attendees towards more sustainable transportation alternatives, applications in practice have experienced varied success due to limited empirical evidence surrounding the cognitive mechanisms behind attendee mode choice. Through a survey of 500 special event attendees, this study set out to identify the psychological determinants of non-car use as expressed by the leading choice behavior theories. Key findings revealed that non-car use intentions were associated with attitudes, perceived behavioral control, role beliefs, normative beliefs, affect, and personal norms, while habits and intentions directly influenced non-car use behavior. The results underscored the need for future research to adopt a comprehensive approach towards applying the leading theories and exploring their transferability across contexts. Specific interventions are recommended.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.082
Threshold uncertainty score0.307

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.043
GPT teacher head0.375
Teacher spread0.333 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it