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Record W4405397889 · doi:10.5267/j.jpm.2024.9.004

The transportation efficiency of cargo truck drivers from Thailand to Lao PDR

2024· article· en· W4405397889 on OpenAlexvenueno aff
Sukanya Sirimat, Sakkarin Nonthapot

Bibliographic record

VenueJournal of Project Management · 2024
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsnot available
FundersKhon Kaen UniversityChina Railway
KeywordsTruckTransport engineeringBusinessEngineeringAutomotive engineering

Abstract

fetched live from OpenAlex

The purposes of this study are to study (1) opinions on the driving performance of cargo truck drivers and (2) the factors that affect the efficiency of driving cargo trucks from Thailand to the Lao PDR by crossing the first Thai-Lao Friendship Bridge. The study was conducted with a sample of truck drivers who transport goods across the Thailand border to Lao PDR at the Nong Khai Customs Area, Nong Khai Province. 384 respondents were acquired by selection according to their convenience. They then completed a questionnaire with confidence values between 0.70 – 0.90. The statistical data analysis for this study included mean and standard deviation, and structural equation analysis. The results showed that: (1) Truck drivers have various opinions on the personal factors of truck drivers; truck driver performance factors and truck driver transportation efficiency indicators are as follows: speed, economy, safety, comfort and punctuality factors, which are at very high levels and (2) The personal factors of a truck driver have a positive influence on truck driver performance while the truckers’ transportation efficiency and the truck drivers’ performance have positive influences on the efficiency of truck drivers' transportation by 54 percent.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.472
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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 designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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