Relationships between commitments to the organization, the superior and the colleagues, and the intention to leave among truckers
Bibliographic record
Abstract
Purpose The purpose of this study is to use three foci of commitment (to the organization, to the colleagues, and to the superior) to improve employee retention in high turnover work environments. Design/methodology/approach In this study, survey questionnaires measuring affective commitment to the organization, the supervisor‐dispatcher and colleagues were administered to 294 truckers. The two‐step approach was used. While the first step involved a confirmatory factor analysis, the second step used structural equation modeling to test hypotheses. Findings Findings show that the model that best fits the data is the one in which both affective commitments to the dispatcher and to the colleagues affects the intention to leave the organization through affective commitment to the organization. Originality/value Existing research on trucker turnover has neglected to examine the role of psychological variables such as employee commitment. Using field theory premises, this research contributes to the literature on trucker turnover by demonstrating the relevance of using several foci of commitment to predict intention to leave the organization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".