Contribution of Scientific Production to Air Logistics: A Bibliometric Analysis from the 70s to the Present
Bibliographic record
Abstract
With increased performance expectations based on speed and agility in logistics flow and supply chain processes, air logistics has gained popularity as a research area. Although more and more papers are published each year on this subject, to the best of our knowledge, a comprehensive bibliometric academic publication review has not been presented so far to contribute to the intellectual structure of the literature. Therefore, this study aims to investigate the last 5 decades’ intellectual basis of air logistics studies that can be evaluated in the field of social sciences. For this purpose, a total of 398 articles have been accessed to be used in the bibliometric analysis of studies published in the literature of air logistics, and these data have been provided from the Core Collection Database of Web of Science (WOS). The research data consists of articles published in English in the WOS database between 1971 and 2019. Books and papers published in all other languages were not included in the research. The Bibliometrix (Biblioshiny) package of the statistical software program R was used for the analysis and visualization of the data. Research findings indicate that air logistics research has increased greatly, especially in the last 10 years. The most productive countries are the United States, China, and Canada, respectively, while the most published journal is the Journal of Air Transport Management, which has continued to increase its number of publications since 1995. Although there are no tear restrictions in this study, the number of publications on air logistics in the field of social sciences is still insufficient.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.069 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.167 | 0.233 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".