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Record W3081649496 · doi:10.1155/2020/8848741

Psychological Influences on Bus Travel Mode Choice: A Comparative Analysis between Two Chinese Cities

2020· article· en· W3081649496 on OpenAlexvenueno aff
Jian Chen, Qi Chen, Heping Li

Bibliographic record

VenueJournal of Advanced Transportation · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTransportation Planning and Optimization
Canadian institutionsnot available
FundersNational Social Science Fund of China
KeywordsTheory of planned behaviorMode (computer interface)Sample (material)Travel behaviorMode choiceTransport engineeringPsychologyControl (management)EconometricsComputer sciencePublic transportMathematicsEngineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Psychological factors give an important influence on the behavior of travel mode choice, but the effects vary from different cities. To identify and explain the differences, this study makes a comparative analysis between two Chinese cities, Chongqing and Chengdu: a typical mountain city and a typical plain city. The sample is obtained by questionnaires containing 401 and 450 valid records of the two cities, respectively. The model used in this study is established based on the framework of the theory of planned behavior. The main work of this study has three aspects: (1) define the measured variables based on the combination of bus travel characteristics and the theory of planned behavior; (2) verify the model validity in both two cities; (3) make a comparative analysis on the two cities. According to the results, the validity of the theory framework and measured variables is verified; the perceived behavioral control plays the most important role in affecting the behavior of traveling by bus in both two cities; significant differences between the two cities are presented and explained.

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.

How this classification was reachedexpand

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.047
GPT teacher head0.400
Teacher spread0.353 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2020
Admission routes1
Has abstractyes

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